RUNNING HEAD: THESIS JESSICA KOOIJMAN, How do you choose? 1-JUNI-2015

Transcription

1 RUNNING HEAD: THESIS JESSICA KOOIJMAN, How do you choose? influence of wine labels on the Dutch consumer 1-JUNI-2015 INTERNATIONAL COMMUNICATION AND MEDIA: INSTITUTE OF COMMUNICATION, HOGESCHOOL UTRECHT, THE NETHERLANDS Supervisor: Anjali Brito Barbosa Jessica Kooijman,

2 Acknowledgments This thesis was written as an assignment for graduating the Bachelor Communication Management, within the specialisation International Commercial Communications at the University of Applied Sciences Utrecht in the Netherlands. research that has been carried out, in order to create this report, is based on desk research, an online survey, ten interviews and a content analysis. process of the thesis has been guided by Anjali Brito Barbosa, who has been a great mentor and supporter for the subject. A special thank you goes out to Roxana Zaharia and Daphne Bal, who gave me time and helped me with my thesis during my internship in Malta. Rick van Esch for keeping a close watch on the correct spelling and grammar. Jakeline Kooijman for being my patient mother and making me see perspective from another angle and Atie de Ruiter and Minou de Ruiter for a professional check, first read of my thesis. Another thank you goes out to everyone that has been using me as a soundboard about good wines, without you I would not have had this thesis subject. Jessica Kooijman 2

3 Summary This thesis is written about the effectiveness of wine labels in the Dutch supermarkets. aim of the research was to find elements of wine labels that have effect on consumers. following main question was formed: What aspects of wine labels, sold in supermarkets, are important for the Dutch wine consumer when they buy wine? This question is answered with the following sub questions: 1. What aspects are important in brand design? 2. What are the findings from current research on wine labels? 3. What are Dutch regulations on wine labels? 4. What aspects of a wine label do Dutch consumers look at? 5. Which aspects are presented on wine labels currently sold in supermarkets? first three sub questions were researched by use of desk research. information found has been summarized in the oretical framework. fourth sub question is researched by the quantitative exploratory research, by the use of an online survey. To validate these results an additional qualitative exploratory research has been carried out by the use of in-depth interviews. last questions has been researched by doing field research. results of this research have been summarized in a content analysis of three supermarkets in the Netherlands. results show that there are similarities with the results of the desk research and the survey, interviews and content analysis. se are found in the preference in design for a light coloured background and an elegant serif styled font. For information the desk research, the survey and interviews all show that recognition of a brand name takes precedence over other elements. participants of the research will choose a wine they recognize before trying out a new wine. desk research and the interviews show that recognition of grape varietal and place of origin can also trigger the decision. differences that have been found is that the male and female respondents do not prefer the same labels and elements. Women depend on a larger variety of elements than men. survey results showed that an illustration can be an important element of preference, but the participants of the interviews did not like irrelevant and dominant illustrations on the label. y preferred small illustrations like logos or illustrations that are relevant to either the name, grape varietal or place of origin. results of the field research show that the most labels in supermarkets have a white background and a bold serif styled font. 80% of the labels have an illustration and the most found type of illustration are landscapes. This is in line with what is found during the desk research. analysis also showed that the most information found on the label are the brand name, grape/type of wine and the place of origin. following elements are most important for Dutch wine labels: Colour of the background (white) Style of the font (serif, bold) Imagery (only when relevant and not too prominent) Brand name Grape varietal Region of origin 3

4 Content Acknowledgments... 2 Summary... 3 Chapter 1: Introduction Main question & sub questions... 5 Chapter 2: oretical framework Chapter 3: Methodology Desk research Quantitative exploratory research Qualitative exploratory research Field research Chapter 4: Results Survey results Interview results Content analysis Conclusions Conclusions Recommendations Limitations References Appendix

5 Chapter 1: Introduction subject of this thesis is the effectiveness of wine labels in Dutch supermarkets. This subject was chosen as scouring wine shelves in supermarkets for great wines is one of my favourite pastimes. Also several friends often send me pictures of wines, asking me whether they should buy it. This made me realize, that thanks to my wine certificate, I have a big advantage when buying wine with respect to people who don t have a wine certificate. When searching for a thesis subject in literature, I started looking more closely at labelling. In supermarkets I watched other people pick out wine in the supermarkets and saw almost no one look at the back label. When they did look at it they already had the bottle in their hands and they almost never put it back on the shelf after they read it. That is what made me wonder: How do Dutch consumers pick wines from the shelves with only the information from the front label? Putting my personal reasons aside; the results of my research and the conclusion of my thesis could really add value to the overall knowledge about wine marketing. wine industry is still a very closed community in my opinion, they do little for the consumers with limited knowledge about wines. Even though these are responsible for a large part, 77% (Driessen & Morren, 2015), of the consumption of wine. So information about the perception of consumers without wine knowledge could be very valuable for wine consumers. main interest in this research is providing a clear picture of how a consumer picks a wine in a store without any guidance of a store clerk. In my research I will focus on the wine buying process and create a list of criteria that are present in the mind-set of the consumer, before buying a new wine. After the mind-set is clear, I want to research the choice of wine labels by giving examples of two wines with the same price, grape and comparable region. In order to get a clear preference list I will make a check list out of the elements that need to be on the label according to the Dutch consumer. 1.1 Main question & sub questions research targets are Dutch wine consumers that do not have any substantial wine knowledge. y can be wine lovers, but they do not have a certificate, nor have followed a course of any kind. This specific group is important for the research, because consumers with more knowledge about wine have a different mind-set in buying wines than non-wine experts. This information was gained from own experience. People who have followed a wine course will know certain specifics of a grape or a region and know what the wine will taste like. When they are picking out a wine in the supermarket they will look for regions and grapes first before looking at the elements on the label. By observing and talking to people without much knowledge of wines I found that they select their wines very differently. Some of them have no idea about what wine they like and just go for something that sounds familiar or has a nice picture. y convince themselves that they are buying a good wine based on the looks of the label. That is why these people are targeted, because the looks of the labels could be more important to them. goal of the research is to gain insight in the effectiveness of certain aspects presented on wine labels. That way it can be used for targeting the Dutch wine consumer. results of this research will be interesting for wine companies that produce wines for supermarkets, wine import companies that sell wine to supermarkets and supermarkets that put wines on shelves in stores without employees that give advice on wines. central question in this research is: 5

6 What aspects of wine labels, sold in supermarkets, are important for the Dutch wine consumer when they buy wine? In order to answer the central question; the following sub questions have been formulated: What aspects are important in brand design? This question answers what literature is written about brand design. Literature research was carried out to find important aspects of brand design and specifically labels, or packaging that are relevant for wine labels. What are the findings from current research on wine labels? answer to this question will show an overview of at least five studies that researched elements of wine labels. results of these studies will be compared to the results of the survey. What are Dutch regulations on wine labels? This question is answered by doing desk research. In order to give an answer to the main question, the requirements by the Dutch law needed to be clear, so that any restriction of labels are taken into account. What aspects of a wine label do Dutch consumers look at? This answers what aspects on wine labels trigger the Dutch consumer to buy a wine. se aspects can be defined by, for example: background, colours, font, visuals. Quantitative exploratory research was carried out to answer this question. research was done by setting out an online survey. Further research into the qualitative motivations of Dutch consumers was done by having minute interviews into their thought process while selecting a wine. Which aspects are presented on wine labels currently sold in supermarkets? This question answers if the current assortment in the supermarkets is in line with the preference of the Dutch consumer. A content analysis has been carried out in three supermarkets in the Netherlands. This gives an overview of the wine label aspects that are currently sold in the supermarkets. With these aims in mind, the thesis is structured as follows. next chapter will give an overview of the theoretical analysis of the literature and theory available on the subject of wine labelling and the regulations. Third will be the complete methodology of my research, followed by the results, discussion and the conclusion in chapter four and five. 6

7 Chapter 2: oretical framework. Statistics To start researching the wine industry, it is important to know how relevant the Netherlands is for the industry. International Organisation of Vine and Wine (OIV) keeps track on the international wine sales and publish a report with their findings each year. In comparison to the size of other countries in the European Union the Netherlands is very small. However, in 2012, the Dutch population drank an average of 21,8 litres the person (Productschap wijn, 2013). In the 2014 OIV report, the Netherlands was number seven on their list of countries that spend money on importing wine. In 2013 the Netherlands spend a rough on import wines which translates to litres. Netherlands are number seven on the list of spending money on importing wine and they are number eight in volume. This means the Dutch spend more on wines, while France and Russia pay less for wine, but import more in volume. reason for the difference can have various causes. It could mean the Netherlands import from countries that are further away, so they have to pay more for transport, or they import more expensive wines. Japan spends the most on wine and gets the least in volume. Based on this information, the Netherlands is important for the worldwide import of wine. For the size of the country they do import large quantities and are willing to pay for it. Van den Berk and Mathijssen (2014) work for GfK and wrote a report commissioned by the Royal Dutch association of Wine traders. In their report they show the statistics of the imported wine sold in stores in the Netherlands. Dutch import most wines from France, South Africa, Germany and Chile. ir conclusion was that French wines are still the best sold but they are getting more pressure from Germany that produces good wine for a lower price. Furthermore, due to the increase in excise, van den Berk and Mathijssen (2014) see that the quantity of wine sold has decreased, but that the amount spent on wines is still high. y do foretell that this might change and think that there will be a decrease in sales in the years to come. Brand design principles Netherlands is an important country when it comes to wine import (Productschap wijn, 2013). Before looking at current research on the subject, an overview will be made of the marketing principles and theories on packaging. Wine labels do not only consist out of the information that is necessary to explain the wine inside. look of the label itself is often more important in convincing consumers to buy a wine. For designing a label one needs to look at brand design. Specifically packaging design is important for wine producers looking to sell their wines on the jam-packed shelves. Wheeler (2013) gives some interesting suggestions on criteria a label designer should take a look at: - Logotype and signature: se consist out of the brand mark and the logotype. se need to be used consistently on packaging in order to make a proper reference to the company. 7

8 - Look and feel of the label: This is important to enhance the brand image impression, also for wine labels important for the perception of quality. Colours, Imagery, typography and composition all support the look and feel. - Colour: Colours can evoke emotion and express personality. se can be used to create recognition for the consumer. For instance: Red for red wine, green/yellow for white wines and pink for rosé wines. - Typography: This is the type of font you can use on the label to write out information on the label. type of font can give an impression to the reader on what kind of information you are trying to send. Boer (2007), who wrote Brand Design, describes sensorial characterization for creating a visual brand identity. He states that being relevant in your brand identity is the most important aspect of your product designs. This theory can be translated into criteria for designing a wine label. way the consumers get in touch with your product and which senses they use, is important for creating a brand design. sense seeing is one of the most important for the consumer when they are buying a wine. Elements of packaging that are important for this sense are: - Colour; - Colour combinations; - Colour contrast; - Shapes (of the label or on the label); - Fonts and letters; - Imagery: Pictures, Illustrations and logo s; - Size of the label and of the elements used. Feeling is also an important sense when consumers are picking out wines. y touch the bottle and hold it in their hands. So for this the label can be made of a certain type of paper in order to trigger associations. For example: rough paper might trigger biological associations, while smooth labels might trigger more sophisticated associations (Boer, 2007). author also describes the importance of the shelf value of a product of service. He describes two categories of shelf value: - Active shelf value: Ask for the customers attention by setting yourself apart from all the other products. - Passive shelf value: Having enough recognition for the consumer who wants to find his/her favourite brand on the shelf without a lot of effort. Like on the shelves of a supermarket. In this is colour the most important aspect of a label. To summarize Boer s theory: it is important to communicate active shelf value on your packaging if you are still an unknown brand. Once you are known you can have a passive shelf value, as long as your brand loyals can still easily recognize your product. Packaging should be visually attractive to the consumer, but should also correctly inform them about the product. If there isn t any valuable basic information on the label this could result in annoyance and irritations with your brand or product. se feelings could erase all the previously built positive attributes and associations. following basic information should be provided to the consumer in order to take away any uncertainties (Boer, 2007): - Brand name 8

9 - Product name, flavour designation, vivacity, origin - Image of the product (photo, illustration or window) - Specifics aspects like: biological, contains sulphite, etc. - Weight, amount and content - Ingredients - Use of product, preparation, recipe and tips - Shelf life, or other symbols - Way of opening, reclosability - Promotions Packaging is important Today, a lot of wines are sold in the supermarkets on overcrowded shelves. packaging is one of the important marketing aspects to get the customers attention. However, the store shelves are also the most competitive marketing environment in existence (Wheeler, 2013). In order to affect the consumer way of thinking and acting, it is important to first figure out what drives the consumer to buy a certain product (Kotler & Armstrong, 2012). best way to research this is to ask consumers why they bought a wine, when they picked it solely based on the label. Thomas and Pickering (2003) also state this in their research on the Importance of Wine Label Information. aim of their paper was to discover what aspects of wine labels are most important in the decision making process of the consumer. y say it is important to take away as much uncertainty as possible by the customer. In order to do that you need to provide enough information. theory was tested by using a questionnaire in which they showed multiple labels with or without one of the seven information positioning statements. With a seven point scale the respondent could scale the importance of each statement. following positioning statements were used in the survey (Thomas & Pickering, 2003): - Attributes: Gives information about the character of the wine in terms of how it appears or tastes. - Nonpareil: Reflection of quality that the wine is unique. - Parentage: Reflection of history of the region or wine maker (or brand, company or person). - Manufacture: Gives information about how the wine was made (process, ingredients or design). - Target end user: Identifies who the wine was made for (person type). - Target end use: Types of situations for use. - Endorsements: Expert opinions/awards/medals. conclusion of the study was that both front and back label of wines are important, but the front was slightly more influential on the consumer. respondents even gave indications on other information they value on a wine label, like: grape variety, vintage, region, bottle colour, cellar information, bottle shape and additional advice. Wine label research No recent research has been done in the Netherlands on the perception of wine labels. In other countries certain research has been carried out. In Austria, Köning and Lick (2014), did a content analysis on red wines on the shelves in five different supermarkets. y collected quantitative data on all front labels of red wines on the shelves. y made a list of the following aspects: 9

10 - Background colours (first and second) - Visual text and design (symbols, logo s, pictures, font types) - Verbal text (wine producers name + position, brand name, languages) aim of their paper was to find out which semiotic codes are used by Austrian wine producers that sell their wines in the Austrian supermarkets. ir research concluded that wine labels are multimodal texts. This means that various semiotic codes are used on the labels. y state that a mix of colours, visual texts and verbal texts all play a role for the customer in selecting a wine. An important note on this research is that they only looked at the wines that were on the shelves and the conclusion is based only on their content analysis. For Austrian stores a lot of the labels had a clear country-of-origin look and feel to them. y used images of the landscape where the grapes grew and that the favoured background colour is either white or beige. A lot of the wine producers use their name on the label and in most cases this was also the brand name. y found it remarkable that the colour red was almost never used as a dominant background colour on labels. This showed that the wine producers rarely opt to promote their product by using a visual-to-taste approach (Köning & Lick, 2014). Another research (Tang & Cohen, 2014) has been carried out in the retail stores in Hong Kong. China is a new player when it comes to importing wine and selling them in retail stores. Until 2008 there was a wine duty tax and since then the import of wines increased with 80 percent. Also the consumption of wines has been increasing. last numbers were from 2006 to 2009 and they saw an increase of 144 percent in the consumption per capita. However, the knowledge about wines is not yet largely spread, so much Chinese consumers have no idea what kind of wine they are buying. look of the label is therefore very important in the buying process. Tang and Cohen s (2014) aim of their paper was to find out what aspects and information of the wine label drives a customer of Hong Kong retail store to buy a wine. y did this by first interviewing 20 customers of a chain supermarket that has multiple stores in Hong Kong. y asked them about the reasons why they chose a particular wine, the information they looked at on the label and for what occasion they were buying wine. Secondly they sent out a structured questionnaire. This survey was sent to people that were over 18 and that had bought at least one bottle of wine in the past three months. questions of the questionnaire were based on the literature review beforehand and on the answers of the interviews. attributes Tang and Cohen (2014) asked about were: - Brand - Grape varietal - Vintage year - Origin of the wine - Alcohol content - Label colour - Label design Tang and Cohen s (2014) conclusion was that consumers that buy wine in retail stores mostly look at the origin of the wine, the grape variety and look for food and wine pairing information. However, the label design and colour do assist in the purchase decision. One might argue that there would be a difference in how women select wines versus how men make their choice. However, in a study done by Christina Lombardo in 2012, the results show the opposite is true. She tested this by sending out an online survey. Both men and women prefer wine labels that are 10

11 colourful and unique. Her study also confirmed that consumers are more likely to buy a wine that they know or have heard of (Lombardo, 2012). Quality perception In Australia, Schamel and Anderson (2003), researched the price perception of the consumer. y wanted to know if there was a difference in the price consumers are willing to pay for rated wines. y assumed that consumers perceive quality differently when critics have rated the wines, than when they had not. y first looked into the aspects that consumers perceive as quality. In their theoretical framework they looked at different studies on the aspects that are perceived as quality by the consumer. y found that reputations of the region, grape variety and the individual reputations of the wineries were important. In their empirical study they used the following quality indications (Schamel & Anderson, 2003): - Experts quality ratings - Individual winery reputation - Grape varietal reputations - Regional reputations - Classic wine ratings ir conclusion was that consumers in Australia and New Zealand are willing to pay more for wines that have vintage ratings by independent writers, critics and judges. However, this is only after the consumer has made their own assessment of the reputation of the grape and regions by looking at discounts for these wines. This means that regions and grape variety are important aspects on which consumers decide whether or not to buy a wine. In Schamel and Anderson s (2003) research there was proof of this shown in the difference between New Zealand and Australia. Australia has far more regions with a premium classification than New Zealand and has a longer history in wine producing. In the results it showed that the respondents from New Zealand cared a little less about the reputation of regions and grape variety than the respondents from Australia did (Schamel & Anderson, 2003). A study by Bruwer, Lesschaeve, Gray and Sottini (2013) went a little deeper into the subject of region reputations. aim of their study was to review how important the wine regional setting is in order to promote wine tourism. At first instance this has nothing to do with the region on the label, but their study showed that they can both be complementing each other. Marketing a wine region can both be beneficial to promote wine tourism and individual wines from that region. A well-known region will draw more attention on the shelf than a unknown region. Consumers will recognize these quicker and favour these above lesser known regions. research was limited to the region Finger Lakes in New York, but the results clearly state that all people that came to visit specifically came to buy and taste wine. Which mean they have some attachment to the region and will have strengthened association if they enjoyed their visit (Bruwer et al, 2013). A Chilean study by Troncoso and Aguirre (2006) also researched the price people are willing to pay for certain wines by using hedonic price calculating formulas. y selected a couple Chilean of wines that were criticized by an esteemed wine magazine. Out of this magazine they got the criteria that were most important to look at. y found that the year the wine was harvested, the grape variety and the region reputations were most important for the value of the wine. critics gave a higher value to those wines that had a good harvest year, a well-known grape variety and that were from a famous region (Troncoso & Aguirre, 2006). 11

12 De Mello and Pires (2009) also looked in the quality perceptions of consumers. studies were focussed on the perception of colour and the shapes of the wine labels. y wanted to find out what shapes and colours get what perception by the consumers. For the research they developed two questionnaires. In the surveys they asked the respondents about thirteen shapes and ten colour hues. results show that colour alone does not provoke any preferences or perception of quality. However, shapes do when they are valued separately. Rectangular and hexagonal patterns for labels are preferred more when they have a colour hue such as: brown, yellow, black and green (De Mello & Pires, 2009). That showed that information is not the only important aspect of wine labels. design of the label is also important. Another survey, by Sherman and Tuten (2011), investigated how much influence the design of a label and a brand name have on a customer s decision making process. y showed three fictional front labels in which they differentiated in the design and brand name. After the labels were shown they measured the attitude of the different attributes. results of their study shows that other factors are more important than the design and brand name of a wine label. Sherman and Tuten (2011) conclude that it all really depends on the occasion you buy the wine for. brand name and design do give an indication of quality to the consumer. Traditional label designs are associated with desirable wines and were preferred slightly more often than non-traditional labels (Sherman &Tuten, 2011). A similar study by Boudreaux and Palmer (2007) was done, see what impact is of three basic layout elements. For their questionnaire they created a fictional label in which they varied the image, page, size and place of the elements on the label. online survey showed each respondent ten images with questions about their preference. results showed that having a recognizable layout is the key to a successful brand personality. Brand personality specifically showed to be important as well to a lot of respondents. So it is wise to make your other products recognizable as well by using the same design for the label. In wines this could mean that if a consumer had a good experience with your red wine and the next time they are looking for a white wine, they are more likely to choose your brand if you have a recognizable label for your brand (Boudreaux & Palmer, 2007) Regulations on wine labels Packaging regulation can become a serious threat to wine labels. It is seen already in the tobacco industry. Moodie (2013) wrote an insightful commentary on tobacco packaging: Tobacco companies do not have a free rein over packaging, however. In a growing number of markets they are banned from using certain potentially misleading descriptors on packs (e.g. Light, Low-tar ) and from selling packs containing less than a predefined number of cigarettes (usually 10 or 20). y are also required, in most of the world, to display tax stamps, information on emissions and health warnings on packs. For the latter, tobacco companies are now legally required to display pictorial health warnings on packs in more than 60 countries [14] a figure that will rise to at least 80 by 2016 given that the revised Tobacco Products Directive announced by the European Commission in 2012 stipulates the use of pictorial health warnings in all European Union member countries [15]. From a public health perspective the use of pictorial warnings on packs helps to enhance warning salience, reduce pack appeal and disrupt the ability of tobacco companies to communicate with consumers [16]. y do not, however, prevent packaging innovation.( ) re is a possibility that this could also be the case for wines in a couple of years. Turkey already signed a couple of laws that restrict wine brands. Every bottle of wine, either domestic or imported, that s sold in Turkey must include this graphic on the label. Turkish words translate to Alcohol is not your friend (Huyghe, 2014). graphic on the label is not the only restriction the Turkish government put 12

13 on the wine industry. y also cannot have a website, print brochures and do consumer wine tastings. Also journalists cannot write about wines anymore. Ultimately, these restrictions caused a lot of commotion in the Turkish wine industry and makes a lot less money than before. Dutch government has a couple of rules when it comes to advertisement and alcoholic beverages. Most of these rules mostly apply to advertisement, but it is also important to take this into account by designing a wine label. Dutch institute STIVA, is an initiative of Dutch producers and importers of alcoholic beverages. y keep track of the rules that apply to advertisement for alcoholic beverages. On their website they give an overview of the rules and give examples of brands that have either violated the rules, or have gotten away with it. Here is an overview of the important rules on advertisement (STIVA, 2013): 1. Advertise irresponsible consumption of alcohol. 2. Do not shed a negative light on the abstinence of alcohol or the moderate consumption of alcohol. 3. Do not cause any misconceptions about the alcoholic contents and the alcohol percentage of the beverage. You cannot give any indication that an alcoholic is anything other than that. 4. Do not suggest that the amount of alcohol is a positive attribute. 5. Advertisement of alcoholic beverages cannot be contrary to good taste, decency or undermine human dignity and integrity. 6. Advertisement for alcoholic beverages cannot suggest that it has a distress function, suggest that it can have a healthy effect, suggest that it gives an improved performance mentally and physically or suggest that sports performances will improve. 7. Advertisement for alcoholic beverages cannot suggest that it will improve your functionality on your job. 8. Advertisement for alcoholic beverages cannot suggest social or sexual success. 9. Advertisement for alcoholic beverages cannot be focused on pregnant women. 10. Advertisement for alcoholic beverages cannot be aimed at people that are underage, y can also not show people on advertisement that might be perceived as underage. 11. Advertisement for alcoholic beverages cannot suggest that consumption is a sign of adulthood. 12. Advertisement for alcoholic beverages cannot show situations that might provoke any risky behaviour, violent or assaulting behaviour. Or support that behaviour. 13. Advertisement for alcoholic beverages cannot show acceptance or associate with illegal drugs. 14. Advertisement for alcoholic beverages cannot connect consumption with an active traffic participation. se rules need to be taken into consideration if advertisement is going to be placed on a wine label. Further rules and regulation come from the Dutch Food & Wares authority (NVWA). According to Dutch law labels on wine bottles need to contain the following information (Productschap wijn, 2013): 1. Name of the product 2. Name every substance that can cause allergies or intolerances that are used by making the product 3. amount of each ingredient used 4. amount of substance inside the bottle 5. minimum shelf life or the ultimate consumption date 6. Special storage conditions/user conditions 7. Name and the address of the importer 13

14 8. Country of origin or place of origin 9. effective alcohol percentage se last regulations are most important for the design of a wine label. se rules are almost the same as the basic information Boer (2007) advices to be put on packaging. Conclusion In conclusion, wine labels are important in retail stores. Several studies show that the consumer s taste is changing all the time. Some studies say that a traditional logo is the best way to go (Sherman & Tuten, 2011), while others say that a colourful and unique label is better (Lombardo, 2012). In Austria they seem to prefer white labels with a landscape image (Köning & Lick, 2014) and in America they prefer a modern and recognizable look on their labels (Boudreaux & Palmer, 2007). However, they all state that you have to be recognizable on the shelves, especially if you want to get the consumer to be a repeat customer. A combination between visual design and information on the label seem to be the key to trigger the consumer. Information can take away any uncertainties the consumer might have, also some information needs to be presented in order to abide by Dutch law. This can cause an overload of information and so a selection of information needs be made. Lots of the information can be put on the back label, but as wine can be dangerous to health some information needs to be put clearly on the front label. In order to not cause the consumer to get confused, the visual design needs to complement the information given, so the consumers know what they are buying. Since so many different studies have been done with different conclusions on what a label needs to look like, it shows that it really differs per crowd you have. To know what Dutch consumers like it should be tested by designing and sending out a questionnaire just like many other studies did (Boudreaux & Palmer, 2007; De Mello & Pires, 2009; Lombardo, 2012; Schamel & Anderson, 2003; Sherman & Tuten, 2011; Tang & Cohen, 2014; Thomas & Pickering, 2003). 14

15 Chapter 3: Methodology Four types of research have been carried out to answer the main question and sub questions. types of research that were carried out are: Desk research Quantitative exploratory research Qualitative exploratory research Field research 3.1 Desk research Desk research was carried out to answer the sub questions: 1. What aspects are important in brand design? 2. What are the findings from current research on wine labels? 3. What are Dutch regulations on wine labels? Instruments school library provided current literature on brand design and packaging. Dutch regulations were found by searching online in the Dutch advertisement law and the Dutch law on alcoholic beverages. Lastly other research conducted on wine labels were found by using the online database called LUCAS and Google Scholar. Procedure literature was first summarized and the acquired information was used for the theoretical framework. advantage of the literature research is that it gave criteria for packaging that are useful for wine labels. se criteria formed the base of the questions for the online survey. disadvantage of the literature was that there was no official literature specifically on wine label design. studies that have been done on wine labels were outdated, localized or actively included the back label information into their studies. 3.2 Quantitative exploratory research This type of research was used to answer the following sub question: 4. What aspects of a wine label do Dutch consumers look at? Quantitative research was used to gain information about what elements on wine labels influences the consumer to buy a wine. objective of the research was to find out what elements on a wine label trigger a consumer to buy a wine in the supermarket. Instruments quantitative research was gained by using an online survey through enquetesmaken.com. survey consisted out of 35 questions. questions were formulated by using the elements that were found during the desk research and based to answer the sub question. following elements were concluded as the most important for wine labels: - colour of the background; - colour of the font; - style of the font; - brand name; - shape of the label; - colours that are used on the label; 15

16 - illustration; - place of origin; - grape variety. following questions were formed for the first part of the survey: o Are you a man or a woman? o What is your age? o Do you buy wine in the supermarket? o Did you ever follow a (official) wine course? questions were included in the survey to qualify the respondent into a gender category, age category and to qualify them for the target audience. following questions were about the wine labels. Ten sets of labels were shown and each had the following three questions: o Which one of these labels would you choose? o What element attracts you the most to this label? o Are there other elements on the label of influence? (Multiple choice) se questions were asked to find out if the elements given were relevant for the respondents. As for the sets of labels, they were picked by using the current selection of wines in the different supermarkets. Between the labels was always at least one similarity and one point of difference. differences and similarities were in the background, font, colours, shape of the label, brand name, illustration, place of origin and the grapes. Each set was different from the other to see if the respondents would pick answers consistently or if the important aspects would vary per set. Design is a very important aspect for a consumers decision making process, but for wines design doesn t always represent the quality of the wine (Boer, 2007; Boudreaux & Palmer, 2007; De Mello & Pires, 2009; Kotler & Armstrong, 2012; Lombardo, 2012; Schamel & Anderson, 2003; Sherman & Tuten, 2011; Tang & Cohen, 2014; Thomas & Pickering, 2003; Wheeler, 2013). This was the set for the first question. se labels were picked because they come from the same region, have the same grapes and are made in a similar way. difference between is the qualification represented on the label. y all have the same quality: Denominazione di Origine Controllata, but label 2 says: Classico Superiore and label 3 says: Superiore. In way of taste these qualifications say very little about difference in taste of the wine and is mostly used as a marketing technique to make the wine seem more special (Thomas & Pickering, 2003). Also the shape and colours on the labels were significantly different. second set of labels were all made from the same grape and had a big illustration on the label. difference in these were the region, the colours on the label, the font and the information available on the front label. This set was designed to show if the respondents would have a preference for region or design. 16

17 third set contained three labels of wine with the grape albariño. This wine is known for its salty taste and is produced in the Spanish region Rias Baixas. All three labels have this information on them, only the designs and colours of the labels are completely different. Label 1 one and 2 both have an illustration while label three sets itself apart by using multiple colours for the background. This set was compiled to see if the consumer is triggered by the different background colours and the information presented on the label. Set four has three labels with the same grape, extra wine information and with the same colours used on the labels. Label one sets itself apart with the illustration and the white background. Label two is different, because the wine is from a different region and has a well-known brand name. third label is different in the blue background and the small illustration that is part of the logo. This set was designed to see if brand name triggers the consumer or if they rather look at design. Set five has the same grapes on the labels. difference is in the region the labels come from and the design of the label. Label one has a very simple and straightforward design and the region it comes from is the south eastern of Australia. Label two sets itself apart with its shape and the colour of the background. origin of the wine is from the Pays d oc. Label three has the biggest size of label and has an illustration. wine is from Chile. This set was made to see what design would be most preferable for the consumer. sixth set was compiled of yellow labels which all had the same grape. y also all have a different shape for their label. Label one sets itself apart with the colours for the font and the region presented on the label is Pays d oc. Label two is different because it has an extra sticker. Most wines with extra stickers by the labels mean they are rated wines. sticker on this label says it is a wine from France. region is Grand sud. third label is different as it has the qualification Clássico on the label. wine is from Argentina. This set was designed to see what would trigger the consumer when the colours used on the label are mostly the same. seventh set were three labels of merlot wines. first label was very simple with simply the name, slogan and the grape. whole colour of the bottle is green. second label has a black background and uses a gold font. It also has an illustration and shows the location of the winery on the front label. third label is a biological wine called Eco. It is from Chili and has a couple of stamps on the label to show its quality. set was compiled to see if the information on the label trigger the consumer or if the design is more important. 17

18 Set eight was a set of three red wines with a white background on the label and an illustration with a touch of humour. All three wines had a different grape and are from different regions. Also the designs and colours used on the label are very different. Label one is a merlot and the name of the wine is I heart Merlot with a heart illustration to replace the love. Label two is called Kangarook and has a surfing kangaroo as an illustration. label indicates that the grape used is Shiraz and is from the south eastern part of Australia. Label three is the label for Fat bastard which has a Hippo on top of the label. wine is produced out of Cabernet Sauvignon grapes and has a stamp on the label. This sets was compiled to see how the respondents react to comical illustrations/names on the label. ninth set were similar in type of grape and they all have an illustration on the label. differences are in the colours used, font and region of origin. Label one is from Coonawarra, Australia and has a black and white design with an illustration of a winery. Label two is more elegant in the font and has an elephant on the letter e for an illustration. wine comes from South Africa. third label is red, comes from the south eastern part of Australia and has an illustration of a penguin. This set is designed to see what colours/illustrations have more effect on the consumer. tenth and last set of the survey are of three well-known brands, they have a white background in common. Label one is of the brand Barefoot. It is yellow, from California, has the grape pinot grigio and a sticker for winning a contest. Label two is of the brand Hardy s. This brand produces their wine in Australia. y used a black and white background with a gold font. For illustrations they used stamps. grapes are Chardonnay and Semillon. third is Casillero del Diablo of the brand Concha y Toro. grape they used is Sauvignon Blanc from Chile. y also used a black and white background, but used red for their font. This set was designed to see if the respondents would choose familiarity over type of grape. last part of the survey asked the respondents to validate the importance of the individual aspects by selecting a wine on a one to five point scale, on which one was very unimportant and five was very important. last question of the survey was optional. question was about their opinion on why certain elements on wine labels were more important than others. survey was checked by the Hogeschool supervisor Anjali Barbosa and after she gave her permission the survey was pretested by three people to see if they would answer accordingly. survey was then set out online through Facebook and . results of the survey were analysed using SPSS. Participants required number of respondents is 125. target group is men and women older than 18 that buy wines in supermarkets, but have never followed a course about wine. 18

19 Procedure By setting out the online survey, a request was sent to the target group asking them to share the survey on their Facebook or to the link to people they knew. This was to ensure that the aimed number of respondents was reached and that there was age variety within the respondents. data collection was organized through Microsoft Office Excel and transferred to SPSS and analysed there. advantage of a survey is that it can easily collect preferences and it is easy to analyse the results as long as there are a lot of closed questions. disadvantage of the method is that it does not give as much insight in the thought process of the buyer. Also an online survey has to be explained thoroughly for people to be able to answer the question correctly, as there is no one there to explain further if the respondents don t understand the questions(baarda, 2010). results of the survey show what label in each set is most likely to be picked by the respondent and what aspect of the label stands out most to the respondents. Each set was analysed separately and for each label the most important aspects of that label were reviewed. se results were tested on significance with the chi quadrat. An overview of the results shows the popular labels and aspects of the labels. Out these results a profile is compiled to give an overview of the perfect label for the Dutch consumers. 3.3 Qualitative exploratory research research into qualitative answers and reactions of Dutch consumers was done by doing short interviews. objective of this research was to find out consumers opinions of the importance of the different aspects on wine labels. During the interviews questions were asked about the profile of what a label needs to look like, opinion on the buying process, what information or design they prefer and any other insights they might have on wine labelling. This research will answer the following sub question: 4. What aspects of a wine label do Dutch consumers look at? interview questions were composed after the results of the quantitative research were analysed. following questions were asked during the interviews: What kind of wine do you usually by in the supermarket? (ask about: font, background colour, brand name) This question was asked to let the participant think about the label and type of wines they usually buy in the supermarkets. y were given the time to think of a profile of the wines they buy. objective of this question was to find out what aspects of a wine label triggers the participant. What do you notice when you are standing in the wine aisle in the supermarket? (ask about: labels, aisle labels, deals, grape, regions, feeling) This question was asked to make the participant visualize the wine aisle. participant had to describe the aspects they look at and the thoughts they have when they are in the wine aisle to pick out a wine. objective for this question was to find out what the participant consciously looks at, thinks and feels when they are in a wine aisle. How long do you spend on picking out a wine? (ask about: before going to the supermarket, during shopping, for yourself, for someone else) participant was asked this question to keep visualizing standing in the wine aisle and think about the process they go through when they buy wine for different occasions. objective of this question was to find out if the participant would act and think differently about picking wines for different occasions What does the label of a good wine look like? This question was asked to close of the interview and to compare this answer to their first answer. 19

20 objective of this question was to find out if the participant would consider new aspects in comparison to their first answer or if they would stick to the same type of wines they used to buy. Instruments instrument used to do the qualitative research were in-depth interviews. se were short interviews of approximately 15 to 30 minutes. amount of time the interviews were kept short due to the specific questions and to gauche the first reaction to the profile of the labels given. Participants participants of the interview were people that buy wines in the supermarket. re was no restriction on the pre known knowledge of wines, because the questions were formed after the results of the survey. re were 10 people interviewed from various ages. One male and nine females were interviewed. reason for the many women in the interview is that all men that were asked to participate did not do the groceries. refore due to time limit mostly women were interviewed. As not all categories were evenly represented in the survey a similar population has been interviewed. participants were the following: 1. Rick van Esch, Tialda Fongers, Jakeline Kooijman, Gea van Esch, Sonja Schröder, Minou de Ruiter, Daphne Boumans, Denise Spruijt, Atie de Ruiter, Mariska Kromwijk, 48 Procedure interviews were carried out via Skype and face to face conversations. interviews were designed to take up to 15 minutes depending on the respondent. interviews were recorded by using the Dictaphone function on the Apple Iphone 5. After the interviews were taken the audio was transcribed verbatim. following codes were used in the labelling: Important aspects of labels Unimportant aspects of labels Other influences of the buying process. advantage of in-depth interviews is that the participants can give more insight into their thought process during the selection of a wine. y can explain their choices more thoroughly and visualize the experience better. In-depth interviews gives the opportunity to learn about the thought process directly from the consumer. A disadvantage of interviews is that it might be viewed as unscientific and biased. opinion of the respondent can t be controlled and might be influenced by the thought process of the interviewer. Certain assumptions might be made by the interviewer due to subjectivity (Auerbach & Silverstein, 2003). 3.4 Field research To complement the research a content analysis was carried out to gauge to what extent supermarkets stock wines with labels that the participants of the survey and interviews prefer. This research was designed after a similar research done in Austria by Köning and Lick (2014). objective of the research 20

21 is to get a profile of the current wine labels in the supermarkets and if they fit the needs of the Dutch consumer. results will answer the following sub question: 5. Which aspects are presented on wine labels currently sold in supermarkets? Instruments Photos were taken of the wine shelves in three different supermarkets. A camera and the website of the supermarkets were used to reference the wines. Participants three supermarkets that were analysed were: Albert Heijn, Jumbo and Emté. Albert Heijn and Jumbo are two of the biggest supermarkets in the Netherlands. Emté was added to compare the assortment to that of Albert Heijn and Jumbo. third choice of supermarket was selected, because the Plus and the Spar did not allow pictures to be taken in their aisles. All supermarkets were photographed between the 24 th of January 2015 and the 27 th of January Procedure Pictures were taken of the wine aisles and the shelves. Once the pictures were uploaded on the computer they were zoomed in to score the different elements of each wine label. website of the supermarkets and google were used as a reference for when the pictures were not clear enough. This resulted in four lists of elements from the wines at each supermarkets and one complete list of all the elements from all three stores. lists were analysed and for each supermarket a profile has been made of the assortment. categories for the analysis are: - Total amount of bottle s (overall and per supermarket). - Type of wine (red, rosé or white) - Colour of the background - Second dominant colour on the label - Type of illustration Serif font Sans serif Other font - Type of font (serif, sans serif or other) font - Design of the font (italic, underlined, bold/capitalized or standard) - Type of information on the label (wine company, brand name, grape, quality, region, description) advantage of this type of research is that it gives extra value to the research into the influential elements of wine labels. results of this research can either confirm or disclaim that the supermarkets fill their shelves with products the consumer wants. disadvantage of the study is that assortments change and not all the shelves are filled up all the time. So the timing of the photo s is highly influential on the assortment perceived at that time and can be inconsistent with the current assortment. Field research is a highly selective method of research as conditions of a certain situation might vary day to day (Baarda, 2010). 21

22 Chapter 4: Results 4.1 Survey results All tables and graphs that are made with the results of the online questionnaire have been put in the appendix in the chapter called SPSS, which starts at page 45. All sets have subcategories and all tables used have been referenced in the written text. survey had a total of 172 respondents, but only 136 of those were within the aimed target audience. gender of the respondents were unevenly divided as 88 of the respondents were women and 48 were men (see: table 1; appendix: spss, figure 2, page 49). Almost half (45,6%) of the respondents were in the age category, there was only one respondent older than 70 and only four were in the year age category (appendix: spss, figure 1, page 49). That makes that the survey is not representative for the whole population, so conclusion will be made only for the responses of the participants of this survey. Age vs. gender respondents of the survey Total year year year year year 70+ year Man Count % gender 39,6% 33,3% 10,4% 8,3% 8,3% 0,0% 100,0% % age 30,6% 53,3% 20,8% 26,7% 100,0% 0,0% 35,3% % total 14,0% 11,8% 3,7% 2,9% 2,9% 0,0% 35,3% Woman Count % gender 48,9% 15,9% 21,6% 12,5% 0,0% 1,1% 100,0% % age 69,4% 46,7% 79,2% 73,3% 0,0% 100,0% 64,7% % total 31,6% 10,3% 14,0% 8,1% 0,0% 0,7% 64,7% Total Count % gender 45,6% 22,1% 17,6% 11,0% 2,9% 0,7% 100,0% % age 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % total 45,6% 22,1% 17,6% 11,0% 2,9% 0,7% 100,0% Table 1: Gender versus age respondents Set one: In set one the difference in labels was in colours used on the label and on the background, the shapes of the labels and label two and three had an extra quality classification. results show that overall label one was the most popular label with 56,6% of the answers. Label two was chosen by 29,4% of the respondents and label three 14,0% (appendix spss, figure 3, page 50). re was no difference in preference between the men and women (appendix spss, table 2, page 50). Also in age the same preference was seen (appendix spss, table 3, page 50). overall important element of the labels was the colour of the background (35,3%) (appendix spss, table 4; 5; 6, page 51-53). However, per label this varies. For label one 51,9 % of the respondents gave the colour of the background as reason for choosing that label, for label two the illustration as reason (36,8%) and for label three the shape was the most important reason (57,5%) (appendix spss, table 5, page 51-52). overall of the women and men said that the colour of the background was the most important element. For label two there was a difference in preference as more men chose the colour of the background as most important element than women (appendix spss, table 6, page 52-53). re was also no difference in preference regarding to age (appendix spss, table 4, page 51). question about the other important elements showed that the style of the font was chosen most often with 28,6% (see: figure 4). Both men and women chose this element as important in the overall 22

23 count of the other important elements. Label one and three had the highest count for this element by the male respondents and the female respondents chose this element as most important by label one and two (appendix spss, table 7, page 54-55). In the age categories a slight preference for the colour of the background can be seen in the year old respondents (appendix spss, table 8, page 55). Other important elements set 1 None illustration Shape of the label Brand name Style of the font Colour of the font Colour of the background 6,6% 7,7% 8,7% 11,7% 17,3% 19,4% 28,6% 0,00% 5,00% 10,00% 15,00% 20,00% 25,00% 30,00% 35,00% Other important elements Figure 4: Other important elements set 1 results of this set show that the respondents had a preference for the most sober label with a white coloured background. extra classification indicated on label two and three seem to have no effect and none of the respondents mentioned this as a reason for choosing the label. Set two: In the second set of labels the wines were all made from the same grape and they all had a big illustration on the label. difference was the type of illustration, the region the wines came from, the font used and the amount of information presented on the label. results show that the most popular label in this set was label two with 43,4% of the responses (appendix spss, figure 5, page 56). However, the women seemed more attracted to label one as 40,9% of the women chose this label over 38,6% of the women who chose label two. men did choose label two most often with 52,1% of all the male responses choosing label two (see: table 9). As for age, the people between 18 and 29 years old chose with 45,2% of their age category for label one while the respondents older than 29 chose for label two. Only the people between 50 and 59 years old chose label one over label two and the people between years chose label three (appendix spss, table 10, page 56). Gender Set 2: Which one of these labels would you choose? Total Label 1 Label 2 Label 3 Man Count % Gender 29,2% 52,1% 18,8% 100,0% % Label 28,0% 42,4% 33,3% 35,3% % Total 10,3% 18,4% 6,6% 35,3% Woman Count % Gender 40,9% 38,6% 20,5% 100,0% % Label 72,0% 57,6% 66,7% 64,7% % Total 26,5% 25,0% 13,2% 64,7% Total Count % Gender 36,8% 43,4% 19,9% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 36,8% 43,4% 19,9% 100,0% Table 9: Gender vs. labels set 2 most important element chosen was the illustration with 54,4% of all responses. This element was chosen as most important element for all labels, showing no difference in preference in age categories and gender categories (appendix spss, table 11; 12; 13, page 57-59). For all labels respondents chose the illustration as the most important element (appendix spss, table 13, page 58-59). 23

24 results about the other important elements show that the respondent preferred two elements: the style of the font and the colours used on the label both scored 20,0% of the responses (appendix spss, figure 6, page 59). responses show that women preferred the style of the font more than the colours used in the overall responses. In the responses per label a difference can be seen as more women who chose label one responded that the colours used were more important than the style of the font. female responses for label two show the opposite result: the style of the font was chosen more as important element than the colours used on the label. women who chose label three had the most responses for no other elements with 35,0% and the second most responses for place of origin with 30,0% of the female responses for this label. male responses are not as decisive as the women as they scored similar on various elements. As for the overall responses the colours used on the label scored the most 22,4% of all male responses, but the style of the font and other important elements only had 19,0% of all responses (appendix spss, table 14, page 60-61). Also in the age categories there is no clear preference seen. people between 18,-29 years old preferred the style of the font with 25,6%. In the older categories the colours used on the label is chosen more often as most important other element (appendix spss, table 15 page 61). se results show that the illustration of a landscape is chosen more often than other type of images. respondents who were attracted to label two show that they prefer that illustration with combination of the style of the font. respondents who chose label one also preferred the illustration, but for other important elements they chose the colours used on the label as more valuable. information on the label was clearly not important enough to be chosen as an important element. font of label two was a serif font for the name and had sans serif and italic serif fonts that gave other information on the label. This was preferred above the sans serif font of label three and the designed font of label one. Set three: By the third set of labels all were the same type of wine from the same region, but the designs of the three were different in colours, illustration, font and the amount of information on the label. most popular label by the respondents was label one with 53,7% of all the responses (appendix spss, figure 7, page 62). re was no difference in preference seen in gender and in age categories (appendix spss, table 16 and 17, page 62). respondents were just as decisive in element as they were in label as the most important element is the colour of the background that was chosen with 47,1% of all responses (appendix spss, table 18; 19; 20, page 63-65). For all labels this was chosen as the most important element, the only difference is seen by the male respondents that chose label three as their favourite. For this label they chose the style of the font, the brand name and the illustration as more important, but as there were only six male respondents that chose this label, these results are not representative enough (appendix spss, table 20, page 64-65). re was no significant other preference in the age categories seen (appendix spss, table 18, page 63). other important elements show that the style of the font was chosen most often with 24,0% of all responses, the second most popular other element are the colours used on the label with 20,1% of all responses (see: figure 8). male responses show that there were a few more responses for the element the colours used on the label than there were for the answer none with 23,7%. style of the font also had almost the same amount of responses with 22,0% of all male answers. female respondents did prefer the style of the font over all the other elements as 25,0% of the women chose this option. However, the women that chose label one also preferred the colours used on the background almost as much as the style of the font. overall count shows that the colours used on 24

25 the label is mostly chosen for label one (appendix spss, table 21, page 66-67). In the age categories more difference is seen. style of the font is most popular with people between 18 and 39 years old, but in the youngest category there was only one response less for the colours used on the label. people over 39 years old seemed to all go for different elements than the style of the font (appendix spss, table 22, page 67). None illustration colours used on the label brand name style of the font colour of the font colour of the background Figure 8: Other important elements set 3 Other important elements 5,6% 7,8% se results show that the respondents preferred the label with the white background and the least used colours over the modern and colourful labels. Label one did have the most information on the label that is presented in a serif font. other important elements style of the font and the colours used on the labels were both chosen for label one as well, so the conclusion for this set is that the respondents were more attracted to a classical clear coloured label. Set four: fourth set had three blue coloured labels, that had the same grape and extra wine information on the label. difference was in the illustrations, font, region and one of the labels has a well-known brand name. results show that label three was slightly more popular with 38,2% than label two that had 34,6% of all responses. Label one scored 32,2% of all responses (appendix spss, figure 9, page 68). male respondents have a preference for label three with 52,1% of the male responses, surprisingly their second most popular label is label one with 27,1% of the male responses. Label two had 20,8% of the male responses. female respondents did prefer label two with 42,0% of all female responses. Label three scored second place with 30,7% and label one had 27,3% of all female responses (see: table 24). age categories show that the respondents between years old and the year categories preferred label three. age categories show that the difference in preference is not that clear for all age categories, as the amount of responses for all labels are very close together (appendix spss, table 23, page 68). 15,6% 14,0% most important element is a tie between the colour of the background and the brand name; both scored 24,3% of all responses. A close third is the style of the font that had 18,4% of all responses (appendix spss, table 25; 26; 27, page 69-71). age categories show that they all went for a different element as most important. youngest category 12,8% 20,1% 24,0% 0,00% 5,00% 10,00% 15,00% 20,00% 25,00% 30,00% Other important elements Gender Set 4: Which one of these labels would you choose? Total Label 1 Label 2 Label 3 Man Count % Gender 27,1% 20,8% 52,1% 100,0% % Label 35,1% 21,3% 48,1% 35,3% % Total 9,6% 7,4% 18,4% 35,3% Woman Count % Gender 27,3% 42,0% 30,7% 100,0% % Label 64,9% 78,7% 51,9% 64,7% % Total 17,6% 27,2% 19,9% 64,7% Total Count % Gender 27,2% 34,6% 38,2% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 27,2% 34,6% 38,2% 100,0% Table 24: Sex vs. labels set 4 25

26 went with the colour of the background (29,0%), the year category preferred the style of the font (26,7%), but had the brand name as a close second with only one response less (23,3%) year category preferred the brand name with 37,5% of their responses. older age categories were not significant enough in responses (appendix spss, table 25, page 69). same indecisive pattern is seen in the male responses. males that chose label one responded that the illustration (53,8%) was the most important element for their decision. males that chose label two preferred the brand name (50,0%) and the males that went for label three preferred the style of the font (28,0%). female responses were more decisive as most went for the colour of the background, with the exception for the females that chose label two. brand name was the more important element for this label according to the female respondents. In the overall count can a clear preference in element seen per label. respondents that chose label one prefer the illustration over the others, while the respondents that went with label two chose the brand name as most important element and the respondents for label three preferred the colour of the background over the other elements (appendix spss, table 27, page 70-71). other important element is the style of the font with 20,2% (appendix spss, figure 10, page 71). most popular other element for the male responses was the colours used on the label with 21,8%. female respondents preferred the style of the font, with the exception of the respondents that chose label two (appendix spss, table 28, page 72-73). preference for the age categories is very varied. youngest category scored the highest on the style of the font with 23,8% of this category (appendix spss, table 29, page 73). se results show that there was a big difference in preference per label and that the results are not decisive enough to point out a winner in labels, elements and other important elements. This might be due to the amount of similarities in design between the labels. Important to note is that the respondents that went with label two, which had the well-known brand name, were triggered by the brand name. colour of the background was more important for label three, which had a light blue coloured background and this was the only label with only one colour on the label. respondents that went with label one preferred this label for the illustration and this was the only label with a dominant image. Set five: fifth set was created out of labels that have the same grape on the label. difference is in the design and the region the labels are from. most popular label is label two with 43,4% of all responses. Label three came in second with 33,8% of all responses (appendix spss, figure 11, page 74). Both male and female respondents chose label two as the most popular label, but the female respondents had a close second in label three that had only three responses less than label two (appendix spss, table 30, page 74). As for the age categories, the respondents between years old had a clear preference for label two, the respondents between years old both had a tie in responses for label one and three (appendix spss, table 31, page 74). most popular element of all respondents is the colour of the background with 22,1%, the second important element is the shape of the label with 18,4% and the third important is the style of the font with 14,7%. y all had a difference of five responses (see: table 33; appendix spss, table 32 & 34, page 75-77). first label scored best on the colours used on the label with 29,0%, label two with 39,0% scored best on the shape of the label and label three had most responses for the illustration with 34,8% (see: table 33). age categories show that there is not a distinct preference for one element. Only the youngest category had a clear preference for one element: the shape of the label with 27,4%. All the other age categories had the same amount of responses on multiple elements (appendix spss, table 32, page 75). same pattern can be seen in the responses of the male and female respondents. re is 26

27 no clear picture on which element is decisively the most popular element. male responses have a tie with the colours used on the label (20,8%) and the place of origin (20,8%), while the female responses show that the colour of the background (25,0%) is most popular with the shape of the label (19,3) a close second (appendix spss, table 34, page 76-77). Labels Set 5: What attracted you the most in the chosen label? Total colour style colours Place of the colour of of the brand shape of used on the of background the font font name the label label illustration origin Other Label 1 Count % Label 16,1% 0,0% 12,9% 3,2% 6,5% 29,0% 9,7% 16,1% 6,5% 100,0% % Element 16,7% 0,0% 20,0% 25,0% 8,0% 47,4% 15,8% 31,3% 66,7% 22,8% % Total 3,7% 0,0% 2,9% 0,7% 1,5% 6,6% 2,2% 3,7% 1,5% 22,8% Label 2 Count % Label 28,8% 0,0% 10,2% 1,7% 39,0% 13,6% 0,0% 6,8% 0,0% 100,0% % Element 56,7% 0,0% 30,0% 25,0% 92,0% 42,1% 0,0% 25,0% 0,0% 43,4% % Total 12,5% 0,0% 4,4% 0,7% 16,9% 5,9% 0,0% 2,9% 0,0% 43,4% Label 3 Count % Label 17,4% 0,0% 21,7% 4,3% 0,0% 4,3% 34,8% 15,2% 2,2% 100,0% % Element 26,7% 0,0% 50,0% 50,0% 0,0% 10,5% 84,2% 43,8% 33,3% 33,8% % Total 5,9% 0,0% 7,4% 1,5% 0,0% 1,5% 11,8% 5,1% 0,7% 33,8% Total Count % Label 22,1% 0,0% 14,7% 2,9% 18,4% 14,0% 14,0% 11,8% 2,2% 100,0% % Element 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 22,1% 0,0% 14,7% 2,9% 18,4% 14,0% 14,0% 11,8% 2,2% 100,0% Table 33: Labels vs. elements set 5 question about other important elements show that 21,0% of the responses was none. second best response was the style of the font with 19,9% of all responses (appendix spss, figure 12, page 77). difference in choice can also be seen in the responses of the male and female participants. 40,0% of the males responded that no other element was important in their choice for the label. female respondents all gave the style of the font (22,1%) as most important element for the labels of their choice, but the totals for their answers show that other elements scored almost as much (appendix spss, table 35, page 78-79). age categories show that mostly the younger respondents chose the style of the font, while all other categories went with none (appendix spss, table 36, page 79). se results show that a dark coloured label can also appeal to the respondents. Label two was the only one with a dark dominant colour and was the only one with a different than usual shaped label. It has a sans serif font, while the others had a serif font or a designed font. Label three had more information on the label, while label two only showed the name, grape and place of origin. This shows that the respondents went with the most simple and symmetrical design. Set six: sixth set had three labels with yellow as the most prominent colour, all have the same grape and all have a differently shaped label. difference in the labels is in font, second colours and information on the label. One label also had an extra sticker to show it won a price, another label has extra classifications on the label. This set had a clear winner with 49,3 % of the respondents choosing label three (appendix spss, figure 13, page 80). Both male and female respondent clearly chose label three as their favourite label (appendix spps, table 37, page 80). Also the age categories show the same pattern in favour of label three (appendix spss, table 38, page 80). important elements show that the shape of the label scored best on all labels with 33,8%, the second best element is the colours used on the label with 28,7% (appendix spss, table 39; 40; 41, page 81-83). This element was chosen on all labels almost as much as the first label with only as much as three 27

28 responses less (see: table 40). male respondents clearly preferred the shape of the label over the other elements with 37,5% of the male responses. female responses show a near tie between the shape of the label that scores 31,8% and the colours used on the label that scores 33,0% of female responses (appendix spss, table 41, page 82-83). Labels colour of the font style of the font Set 6: What attracted you the most in the chosen label? colours Place brand shape of used on the of name the label label illustration origin Other Total Label 1 Count % Label 10,5% 10,5% 2,6% 31,6% 23,7% 2,6% 13,2% 5,3% 100,0% % Element 66,7% 23,5% 16,7% 26,1% 23,1% 25,0% 38,5% 40,0% 27,9% % Total 2,9% 2,9% 0,7% 8,8% 6,6% 0,7% 3,7% 1,5% 27,9% Label 2 Count % Label 3,2% 9,7% 12,9% 32,3% 29,0% 0,0% 9,7% 3,2% 100,0% % Element 16,7% 17,6% 66,7% 21,7% 23,1% 0,0% 23,1% 20,0% 22,8% % Total 0,7% 2,2% 2,9% 7,4% 6,6% 0,0% 2,2% 0,7% 22,8% Label 3 Count % Label 1,5% 14,9% 1,5% 35,8% 31,3% 4,5% 7,5% 3,0% 100,0% % Element 16,7% 58,8% 16,7% 52,2% 53,8% 75,0% 38,5% 40,0% 49,3% % Total 0,7% 7,4% 0,7% 17,6% 15,4% 2,2% 3,7% 1,5% 49,3% Total Count % Label 4,4% 12,5% 4,4% 33,8% 28,7% 2,9% 9,6% 3,7% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 4,4% 12,5% 4,4% 33,8% 28,7% 2,9% 9,6% 3,7% 100,0% Table 40: Labels vs. elements set 6 category none of the other elements was most popular with 30,1% of all responses. elements that did influence the respondents were the style of the font with 20,2% and the colours used on the label with 18,4% (appendix spss, figure 14, page 83). This is explained in the responses of the male and female participants as 48,1% of the males answered none. female respondents are more influenced by the elements as their choices show that 24,3% was influenced by the style of the font and 18,9% was influenced by the colours used on the label. However, 21,6% answered in line with the male opinion that none of the other elements were of influence (appendix spss, table 42, page 84-85). se results show that the label with the most classifications, colours and serif styled font was the winner of this set. shape of the label was combined out of three islands on which information was represented. It was the only label that also had a very different colour besides yellow on the label. other labels used white or gold, while the third label also had a black rectangle shape around the brand name. sticker on label two apparently had no extra value for the respondents. Set seven: seventh set had three labels of merlot wines, the difference of the wines is in the designs of the label. y all three had a different colour and different style in providing information on the label. One of the labels was called Eco to indicate that it contains biological produced grapes. winning label of the set is label two with 54,4% of all responses, label three that is called Eco had 26,5% of all responses and label one had 19,1% (appendix spss, figure 15, page 86). majority of the male and female participants both answered that label two was their favourite. However, label one did score 37,5% of the female votes, which were only nine responses less than label two that scored 47,7% of all female responses (appendix spss, table 45, page 86). All age categories chose label two as the most popular label (appendix spss, table 44, page 86). most popular element is the colour of the background that got 32,4% of all responses (appendix spss, table 46; 47; 48, page 87-89). However, each label had a different element that was most 28

29 influential. respondents that chose label one scored 27,8% on the brand name, 25,0% on the style of the font and 22,2% on the colour of the background. respondents that went with label two did chose the colour of the background as the most influential element with 45,9% responses. label three respondents chose the place of origin as the most important element in their decision with 26,9% of the responses, also the style of the font was important with 23,1% of the label three responses (see: table 47). age categories show a more decisive pattern with the majority going for the colour of the background (appendix spss, table 46, page 87). choices made my male and female respondents show a different pattern, while the majority of the male and female respondents chose the colour of the background, there is a difference per label. male respondents that chose label one favoured the element brand name, the female respondents favoured the style of the font with one response more over the brand name. Label two did get the majority in responses for the colour of the background for both genders. Label three varied again, with the male respondents choosing the place of origin and the female respondents chose the style of the font (appendix spss, table 48, page 88-89). Labels Set 7: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Other Label 1 Count % Label 22,2% 0,0% 25,0% 27,8% 8,3% 5,6% 8,3% 0,0% 2,8% 100,0% % Element 18,2% 0,0% 40,9% 55,6% 100,0% 11,1% 37,5% 0,0% 12,5% 26,5% % Total 5,9% 0,0% 6,6% 7,4% 2,2% 1,5% 2,2% 0,0% 0,7% 26,5% Label 2 Count % Label 45,9% 6,8% 9,5% 6,8% 0,0% 16,2% 4,1% 2,7% 8,1% 100,0% % Element 77,3% 83,3% 31,8% 27,8% 0,0% 66,7% 37,5% 22,2% 75,0% 54,4% % Total 25,0% 3,7% 5,1% 3,7% 0,0% 8,8% 2,2% 1,5% 4,4% 54,4% Label 3 Count % Label 7,7% 3,8% 23,1% 11,5% 0,0% 15,4% 7,7% 26,9% 3,8% 100,0% % Element 4,5% 16,7% 27,3% 16,7% 0,0% 22,2% 25,0% 77,8% 12,5% 19,1% % Total 1,5% 0,7% 4,4% 2,2% 0,0% 2,9% 1,5% 5,1% 0,7% 19,1% Total Count % Label 32,4% 4,4% 16,2% 13,2% 2,2% 13,2% 5,9% 6,6% 5,9% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 32,4% 4,4% 16,2% 13,2% 2,2% 13,2% 5,9% 6,6% 5,9% 100,0% Table 47: Labels vs. elements set 7 other important elements show that 24,4% of all respondents chose the style of the font as the most important other element that influenced their decision for the label (appendix spss, figure 16, page 89). However, the majority of the male respondents (21,4%) responded that none of the other elements influenced their decision, although 18,6% did answer the style of the font. female responses have a more decisive pattern. Only for label three the elements tie with the style of the font, the colours used on the label and no other elements (appendix spss, table 49, page 90-91). same pattern is seen in the age categories, the style of the font is the clear favourite other element (appendix spss, table 50, page 91). se results show that the respondents favoured the black and gold label over the biological label and the modern light green coloured label. black coloured background was the most important element for the majority of the respondent and especially the ones that chose for this label, also the style of the font helped their decision. same was concluded for the other winning black label in set five. y both had gold letters on them and the information of the wine was clearly centred on the label, so that all the information was clear in one look on the label. biological wine did not trigger the respondents attention and neither did the stamps on the logo. conclusion is that for this set the respondents rather went for design than producing method. 29

30 Set eight: eight set had three comical labels with names and illustration that had a touch of humour. difference is in the design, grapes and place of origin. clear winner for this set was label three with 56,6% of all responses. Label one scored second place with 33,8% and label two had 9,6% of all responses (appendix spss, figure 18, page 92). In the male and female responses the majority of the participants went with label three, 66,7% of the male respondents and 51,1% for the female responses. Label one did score 39,8% of all female responses (appendix spss, table 52, page 92). age categories also show the same preference (appendix spss, table 51, page 92). most important element that was of influence for the respondents was the illustration with 35,3% of all responses (appendix spss, table 53; 54; 55, page 93-95). However, for label three the majority of the respondents chose the element the brand name as most influential with 28,6% of the responses. element the illustration did score the second most responses for this label with 24,7%. For the other labels the illustration was the most popular element (see: table 54). age categories show the same preference with the brand name scoring second in the youngest age category and scoring a tie with the style of the font in the year category (appendix spss, table 53, page 93). re is a difference in preference for the genders, the male respondents chose the illustration as the most important element for all labels, while the females that chose label three prefer the brand name over the illustration (appendix spss, table 55, page 94-95). Labels Set 8: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Grape varietal Other Label 1 Count % Label 4,3% 2,2% 13,0% 4,3% 2,2% 6,5% 52,2% 0,0% 10,9% 4,3% 100,0% % Element 28,6% 100,0% 40,0% 8,0% 14,3% 50,0% 50,0% 0,0% 35,7% 33,3% 33,8% % Total 1,5% 0,7% 4,4% 1,5% 0,7% 2,2% 17,6% 0,0% 3,7% 1,5% 33,8% Label 2 Count % Label 0,0% 0,0% 7,7% 7,7% 0,0% 0,0% 38,5% 30,8% 15,4% 0,0% 100,0% % Element 0,0% 0,0% 6,7% 4,0% 0,0% 0,0% 10,4% 57,1% 14,3% 0,0% 9,6% % Total 0,0% 0,0% 0,7% 0,7% 0,0% 0,0% 3,7% 2,9% 1,5% 0,0% 9,6% Label 3 Count % Label 6,5% 0,0% 10,4% 28,6% 7,8% 3,9% 24,7% 3,9% 9,1% 5,2% 100,0% % Element 71,4% 0,0% 53,3% 88,0% 85,7% 50,0% 39,6% 42,9% 50,0% 66,7% 56,6% % Total 3,7% 0,0% 5,9% 16,2% 4,4% 2,2% 14,0% 2,2% 5,1% 2,9% 56,6% Total Count % Label 5,1% 0,7% 11,0% 18,4% 5,1% 4,4% 35,3% 5,1% 10,3% 4,4% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 5,1% 0,7% 11,0% 18,4% 5,1% 4,4% 35,3% 5,1% 10,3% 4,4% 100,0% Table 54: Labels vs. elements set 8 other important elements show that the illustration is again the most important element with 19,0% of all responses, this can indicate that the respondents that did not choose the illustration as most important element did think it was influential too. second important other element is the style of the font that scored 16,4% of all responses (appendix spss, figure 18, page 95). As the most important element was the illustration, the conclusion of the other important elements is that the style of the font also influenced the decision of the respondents (appendix spss, table 56, page 96-97). se results show that the illustration on the labels had the most effect on the participants of the survey, as it had the most responses for the most important element and the other elements. brand name also seemed to trigger the consumer. winning label was the only label that had the illustration not prominently on the label and showed the most clear information on the label. style of the font 30

31 was serif styled with an italic accent in the brand name. name Fat bastard is supposed to indicate the richness of the taste, where label ones name only indicated the grapes used and the label two indicated the place of origin and the illustration used on the label. Set nine: labels in the ninth set all had the same type of grape and they all had an illustration on the label. difference is in the design and the place of origin. most popular label is label one that got 38,2% of all responses, label two is a close second with 36,0%. In the overall count label two had three responses less, so the result is not conclusive (appendix spss, figure 19, page 98). close count in labels is seen in the preference of the male and female respondents. count for Gender Set 9: Which one of these labels would you choose? Total Label 1 Label 2 Label 3 Man Count % Gender 43,8% 33,3% 22,9% 100,0% % Label 40,4% 32,7% 31,4% 35,3% % Total 15,4% 11,8% 8,1% 35,3% Woman Count % Gender 35,2% 37,5% 27,3% 100,0% % Label 59,6% 67,3% 68,6% 64,7% % Total 22,8% 24,3% 17,6% 64,7% Total Count % Gender 38,2% 36,0% 25,7% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 38,2% 36,0% 25,7% 100,0% Table 58: Sex vs. labels set 9 all labels is close together, but the male respondents prefer label one with 43,8% of the male respondents. female respondents preferred label two with 37,5%, while label one had two responses less and scored 35,2% of the female responses (see: table 58). In the age categories the opinions are divided as well, the youngest category is the only one that had a majority in responses for label two, while the older categories preferred label one. However, for all the age categories it is true that the amount of responses for each label is really close together (appendix spss, table 59, page 98). results of the elements used have a more decisive pattern as the illustration has 40,4% of all responses. For label two there were also a lot of responses for the style of the font (appendix spss, table 61, page ). In the age categories the illustration is most popular for all ages (appendix spss, table 60, page 99). male and female respondents also chose the illustration as the most popular, with the only exception for the male respondents that chose label two. se respondents chose the style of the font as more important (appendix spss, table 62, page ). As for the other important elements, the style of the font was the most popular with 19,6% of all responses. illustration came in second place with 17,7% of all responses. This could indicate that the participants that did not choose the illustration as important element, did choose it to be also influential in their decision (appendix spss, figure 20, page 101). male respondents are divided in their answer for other important element. Three answers score 18,1% of the male responses: style of the font, the illustration and none of the elements. women who participated vary their opinion per label. women who chose label one prefer the style of the font. women that chose label two prefer the colours used on the label with one response over the style of the font and responses of the women that chose label three were divided over all the elements (appendix spss, table 63, page ). In the age categories the same dividing pattern is seen with the most respondents going for the style of the font, the illustration and the colours used on the label (appendix spss, table 64, page 102). results show that the preference in labels were very close together for the participants of the survey. winning label is again a white coloured one with basic information and illustration in the centre of the label. label does not have any other colour besides black and white and gives of a calm and clear vibe. second label is also clear coloured with a light yellow background and also the information and illustration in the centre of the label. difference is in the fonts, label one has a clear bold serif font, 31

32 where label two has an italic serif font with lots of curls. losing label is the red comical label with the penguin as illustration and name. This could indicate that the respondents preferred simple light coloured labels over labels with a darker shaded colour. Set ten: tenth and final set was made up out of labels of well-known brands. results show a tie between label two and label three. Label two is from the brand Hardy s and label three bears the name Casillero del Diablo and is from the big wine company: Concha y Toro (appendix spss, figure 21, page 104). As these results are a tie it is expected to see a divide in answers between the genders. male respondents had a majority, with two responses more than label two, in label three with 41,7% of all male responses. female respondents had a majority, with two responses more than label three, in label two with 40,9% of all female responses (see: table 65). In the age categories the same indecisive pattern is seen, in all categories the amount of response for especially label three and two is really close together (appendix spss, table 66, page 104). Gender Set 10: Which one of these labels would you choose? Total Label 1 Label 2 Label 3 Man Count % Gender 20,8% 37,5% 41,7% 100,0% % Label 35,7% 33,3% 37,0% 35,3% % Total 7,4% 13,2% 14,7% 35,3% Woman Count % Gender 20,5% 40,9% 38,6% 100,0% % Label 64,3% 66,7% 63,0% 64,7% % Total 13,2% 26,5% 25,0% 64,7% Total Count % Gender 20,6% 39,7% 39,7% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 20,6% 39,7% 39,7% 100,0% Table 65: Sex vs. labels set 10 As for the important elements there is not a very clear winner either. brand name scores 19,9% of all responses and is therefore the most popular, but label one shows it had the illustration as a clear favourite. Label two did have the brand name as most chosen element, but the colour of the background was chosen just as often. Also the illustration had only one response less than the other two for this label, so the most important element for this label is indecisive. Label three has a tie with the most responses for both the brand name and the style of the font (appendix spss, table 68, page ). same indecisive pattern is seen in the age categories and the divide of the genders. Multiple elements are important for these label with the illustration specifically for label one. For label two the colour of the background, the brand name and the illustration is important and for label three the style of the font and the brand name are the important triggers (appendix spss, table 67; 69, page ). As for the other important elements did 24,5% of the respondents answer that no other element was of influence to them. second scoring answer is the style of the font with 16,3% of all responses and 12,9% of the responses was for the colours used on the label (appendix spss, figure 22, page 107). male respondents are clear in their preference as 37,3% of all males responded that none of the other elements was of influence. female respondents are more divided. majority did answer none with 18,2% of all responses, but the colours used on the label and the style of the font each only scored one response less (17,3%) than the none answer (appendix spss, table 70, page ). In the age categories it is seen that mostly the younger respondents answered different elements, while the older respondents mostly answered none (appendix spss, table 71, page 109). se results show that the brand name was a clear trigger for the participants of the survey. This element was chosen for both label two and three. Surprisingly the respondents that went with label one were more triggered by the illustration than the brand name even though they were all from a wellknown brand. winning labels show that a simple black and white design of the label won again over other coloured labels. Label two was also chosen by respondents for the illustration, which shows that a less prominent illustration can be a trigger as well. 32

33 losing labels: picture above shows all of the labels that were not one of the most popular labels in the survey. first thing that strikes is that they are all very colourful. This is in clear contrast with the winning labels. y were all in one colour and most had a light coloured background. background also seems to be the favoured element in the survey. other important element is the style of the as this element scored consistently high in all sets. Most of the winning labels have a simple serif font, without a lot of curls or special designed elements. On the losing labels different designed fonts are seen more often. Another important detail that was shown for both the losing as the winning labels was that brand name recognition made respondents choose names they recognized over ones they did not recognize. last question last question of the survey was about the importance of the individual elements according to the respondents. results of this question show that the element illustration had the biggest response of the important elements. colour of the background and the style of the font scored the second and third biggest count on importance. se are in line with the results of the individual sets as these elements were often chosen by the respondents. count of these elements on importance is over half the amount of respondents. Other elements that also scored more than half on important or very important are: colours used on the label and the place of origin. This last element has not been very popular in the individual sets, but does score on individual importance for the participants of the survey. lowest scoring element is the colour of the font, after this element the shape of the label and the grape varietal score low. shape of the label has been mentioned as an important element on set six, but on itself it seems to have not much value to the respondents (appendix spss, table 72, page 110). Conclusion significance could not be calculated for the winning labels, as they were inconclusive. This is mostly due to the limited number of respondents and the varied amount of elements asked after. most important aspects were applicable to all of the labels in the different sets. Another cause for the low significance in results is due to quality perception and the difference in taste of the respondents. conclusion that can be drawn from these results is that labels need to have a clear colour, a readable font and a prominent and relevant image on the label. As these elements were chosen most often by the respondents. results of this survey indicate that the colour of the background and the style of the font are two very important design elements for helping the respondents of the survey pick out a wine. colour of the background was selected five times as the most important elements, with the illustration as a close 33

34 second with four times of all labels. As for the other important elements the style of the font was chosen nine times as most important other element. winning labels of the survey show that the participants favoured a light or white coloured background over bright coloured backgrounds. Black backgrounds also did well with the respondents and both black labels had a gold coloured font as contrast. labels indicate that the respondents do prefer the information printed on the label as long as the label does not get too crowded. exception was with the label of set four which also had information of the wine printed on it, but was the least busiest label of the three. brand name seemed of influence as well as it was the trigger for well-known brand names (set: 4, 8 & 10). Recognition of these names made respondents choose a label of a brand they knew and respond with the brand name as most important element for their decision. As for other information on the label, the place of origin and grape varietal did not seem very important in the individual sets, but they were included in the last question about the individual importance of the labels. Especially place of origin was mentioned as important by more than half of the respondents and this shows that information is important as long as the design speaks to the respondent as well. This result was surprising as this was not one of the often chosen elements, so this might be picked by the respondents to seem more interested in the information on the labels. se results are in line with the theoretical framework. Recognition was an important aspect for the research done by Schamel and Anderson (2003). ir conclusion was that consumers will choose wines that they recognize by region, grape or name over other wines. In this research recognition was mostly for the brand names rather than the grapes and regions as these last two elements were not often picked as important. same was concluded in the research done by Troncoso and Aguirre (2006) that researched the region, year and grape information on the label for Chilean wines. results do not confirm the conclusion made by de Mello and Pires (2009). y stated that consumers prefer rectangular shaped labels when they have a colour hue like brown, yellow, black and green. survey results show that the respondents mostly seem to prefer a light coloured background with the exception of a few black ones. Sherman and Tuten (2011) study that concluded that other factors are more important than brand name and design is also not in line with the results of the survey. Most respondents picked the wine purely based on the design or brand name. survey did show that there were differences in preference between the male and female respondents, so this does not confirm the study done by Christina Lombardo (2012). Her research concluded that both men and women prefer wine labels that are colourful and unique. 4.2 Interview results ten interviews that were held to gain more insight into the thought process of the buyer and the buying process in the supermarket were labelled, and summarized in the codebook on page 111 and 112, according these codes: Important aspects of labels Unimportant aspects of labels Other influences of the buying process Important aspects of labels Almost all the participants said they like a clear label on which the grape, place-of-origin and the winery information is clearly shown. Most like a light coloured background or a bit more cream. One participant (Sonja Schröder, 29 April 2015) preferred dark coloured background due to her good experience with wines that had a black background. 34

35 For the font they weren t as agreeable. re is a clear difference in taste, only a couple of the participants liked curly fonts (Tialda Fongers, 25 April 2015; Denise Spruijt, 1 May 2015), but they also stated that the information on the label needed to be easy to read. refore a serif font would be most preferable. Brand names were not a deciding factor for the respondents as they would first look at the information. Names do trigger the consumers when they have drank the wine before. y were likely to pick a recognizable wine over a new wine. When shopping for other people, funny names were more likely to be picked. For example: South African wines often use Dutch words that could connect to a certain event for the receiver (Daphne Boumans, 30 April 2015). As for illustrations on the label, most agreed that the illustration should be relevant to the wine otherwise it would only distract the consumer. illustration have to connect the wine to a type of food with which it pairs or connect with the name of the wine (Jakeline Kooijman, 25 April 2015; Minou de Ruiter, 29 April 2015). Unimportant aspects of labels results of the interviews show that the interviewees said illustrations are not very important to them. Prominent illustrations are said to be distracting and almost all preferred stylish shown text to pictures on the labels. This difference might be explained that when people think back on what they bought, they do not remember the illustration. Text is said to show more class for a wine. A classy look of a label helps the consumer convince themselves they have bought a good wine. Wines with irrelevant illustrations or information were experienced as bad wines. As for the font on the label, lots preferred a classy font, but without exaggerated curls. font needed to be easy to read, but show class at the same time. Also modern styled wine label seems to show more class as they are easier to read (Rick van Esch, 22 April 2015; Gea van Esch, 26 April 2015; Sonja Schröder, 29 April 2015; Minou de Ruiter; 29 April 2015; Daphne Boumans, 30 April 2015; Denise Spruijt, 1 May 2015; Atie de Ruiter, 3 May 2015; Mariska Kromwijk, 7 May 2015). Other influences of the buying process Besides the elements investigated in the survey and asked after during the interviews, there were other aspects that influenced the buying process of the Dutch consumer. During the interviews the participants could elaborate more on other influences in their decision making. Almost all the participants said they mostly buy wine for themselves in the supermarkets. For gifts they go to the liquor stores to get advice from a professional (Rick van Esch, 22 April 2015; Tialda Fongers 25 April 2015; Gea van Esch, 26 April 2015; Sonja Schröder, 29 April 2015; Minou de Ruiter, 29 April 2015; Denise Spruijt, 1 May 2015, Atie de Ruiter, 3 May 2015; Mariska Kromwijk, 7 May 2015) main reason they buy wine for themselves is, because they want something that fits with what they are eating (Rick van Esch, 22 April 2015; Tialda Fongers, 25 April 2015; Jakeline Kooijman, 25 April 2015; Minou de Ruiter, 29 April 2015; Atie de Ruiter, 3 May 2015). Also price was one of the first factors the participants named in their selection process. average price they spend on a wine in the supermarket is between three and six euros. Before entering the wine aisle they look at the current wine deals and see if any of the wines triggers their attention. y either choose a wine on discount, because they already know the wine or it looks interesting enough to experiment. If no deal agrees with them, they go into the wine aisle (Rick van Esch, 22 April 2015; Tialda Fongers, 25 April 2015; Jakeline Kooijman, 25 April 2015; Sonja Schröder, 29 April 2015; Daphne Boumans, 30 April 2015; Denise Spruijt, 1 May 2015; Atie de Ruiter, 3 May 2015; Mariska Kromwijk, 7 May 2015). 35

36 In the wine aisle they mostly look at wines on the shelves in the middle. A couple of the participants stated that these wines have the best prices as the lower shelves are for cheap wines and the upper shelves are too expensive (Rick van Esch, 22 April 2015; Sonja Schröder, 29 April 2015; Minou de Ruiter; 29 April 2015; Daphne Boumans, 30 April 2015; Denise Spruijt, 1 May 2015; Mariska Kromwijk, 7 May 2015). After checking the shelf arrangements for the order in white, rosé and red wines, they check the shelf labels for taste perception information. Some participants preferred it when the aisles were in the order of country and taste (Rick van Esch, 22 April 2015; Tialda Fongers, 25 April 2015), but most only looked at the tastes (Gea van Esch, 26 April 2015; Sonja Schröder, 29 April 2015; Minou de Ruiter, 29 April 2015; Denise Spruijt, 1 May 2015, Atie de Ruiter, 3 May 2015; Mariska Kromwijk, 7 May 2015). Extra texts on the shelves that promote a certain wine helps the consumer with trying out new wines (Tialda Fongers, 25 April 2015). After these steps are taken the label becomes the deciding factor for the consumers in the buying process. Conclusion se results are in line with the results of the survey, with the exception on the element illustrations. survey responses showed that they did value the illustrations on labels, but the participants of the interviews do not prefer illustration, except when they are relevant to the wine or if it is a small logo that does not dominate the label. preference in colour of the background is the same as in the survey. Most participants of the interviews preferred light coloured labels over darker ones, with the exception of two participants (Rick van Esch, 22 April; Sonja Schröder, 29 April 2015). style of the font was mentioned often during the interviews and the participants gave away that they like an elegant styled font, but that it needs to be readable. This explains the lack of winning labels with curly fonts by the survey. Other aspects that are important for the participants of the interviews are recognition of the brands. y will buy a wine they have previously drunk before trying out a new wine. If they don t recognize a brand name, they will look for familiar regions and grape varietal. recognition of brand names was also seen in the sets of the survey, so this is in line with the interviews. survey did not show that recognition of place of origin and grape varietal was important during the different sets. Besides the influence of the labels the participants also mentioned other factors that influence their decision. first thing they look at before even going to the supermarket are the deals that are mentioned in the brochures delivered to their homes or the they get (Rick van Esch, 22 April 2015; Tialda Fongers, 25 April 2015; Jakeline Kooijman, 25 April 2015; Sonja Schröder, 29 April 2015; Daphne Boumans, 30 April 2015; Denise Spruijt, 1 May 2015; Atie de Ruiter, 3 May 2015). After the deals they look at the occasion they are buying wines for. This is also in line with the research of Sherman and Tuten (2011) that concluded that design and information give an indication of quality to the consumer, but it depends on the occasion where the consumers buys wine for what good enough quality is. This is also of influence on the price the participants are willing to pay. Several of the interviewed mentioned they had a fixed price region in mind when they select a wine. After these information are settled in the mind of the participants they will start looking at labels. Design is then the first thing that attracts them, but they will only buy the wine if they are convinced of the quality. For this quality they will look at the information on the label. information they look for are (Rick van Esch, 22 April 2015; Tialda Fongers, 25 April 2015; Jakeline Kooijman, 25 April 2015; Minou de Ruiter, 29 April 2015; Atie de Ruiter, 3 May 2015; Mariska Kromwijk, 7 May 2015): Place of origin Grape varietal Vintage year Wine and food pairings 36

37 se are in line with the survey Tang and Cohen (2014) conducted in Hong Kong. ir research concluded that design helps the consumer pick a wine, but the information is the element that convinces the consumer to buy it. participants of the interviews described a similar process when they are picking out a wine. To summarize the interviews, the participants valued light coloured labels, with an easy to read font. font must show elegance and give the indication of quality. information that needs to be present on the label are: Brand name Place of origin Grape varietal Vintage year Other factors that influence the participants are wine deals. In the store they look at the shelves for taste perceptions and they like to see more information on the shelves about certain wines. When they are buying to fit the wine with the food they are cooking they like to see food pairing tips as well. se can be presented on the label, the shelf or on boards above the wine aisle. For gifts they are less likely to buy these in the supermarket and rather go to a wine or liquor store for advice. 4.3 Content analysis complete overview of tables for the content analysis can be found in the appendixes chapter: Content analysis on page 111. following findings are clustered according three different elements of wine labels that were included in the statistical analysis of the content in the three supermarkets. se are colour, illustrations and text. overall content that was analysed were 486 wine labels, of these there were 177 white wines, 236 red wines and 73 rosé wines (appendix content analysis, table 74, page 111). Colours of wine label most frequently used background colour is white (76%) followed by a crème/beige colour (10%) and thirdly by a black background (4%) (appendix content analysis, table 75 page 111). Only half of the labels had a second background colour (51%) the most dominantly used colour was black (25%), red (18%) and green (10%) (appendix content analysis, table 76, page ). Visual design About 81% of the analysed labels had a visual design element on the label. statistical analysis shows that 74% of the visuals were illustrations, 17% had only a logo and 9% had an abstract illustration. Due to the variety of the illustrations they were put in six different categories to describe them, all percentages are calculated on the amount of illustrations leaving out the logo s and abstract pictures: - Landscapes (estates, vineyard, mountains) 32% - Plants (grapes, flowers, trees) 18% - Items (shield, map, sun) 18% - Animals 17% - Letter 9% - People 6% se percentages show that the most dominated type of images are landscapes. On the overall count of 393 images on labels the landscapes dominate with 24% (appendix content analysis, table 77 & 78, page ). 37

38 Text last part of the content analysis categorized the text on the label. texts were analysed on three different aspects: Type of font, design of the font and the information the text provides. texts were first categorized in three types of fonts: Serif, sans serif and other fonts. serif fonts were used most often, on 57,9% of the labels, sans serif fonts were used on 38% of the labels and other fonts were used on 4,1% of the labels (appendix content analysis, table 83, page 117). re were also differences in how the font was designed, these were divided in four design categories: italic, underlines, bold and standard. Most of the labels, 77%, were written in a bold design. 12,5% of the labels were written in italic and 10,5% used a standard design. No underlined texts were present on any of the labels (appendix content analysis, table 79, 80, 81, 82 & 83 page ). information on the texts were put in 6 different categories: 1. Wine company s name; 2. Brand name; 3. Grape/type; 4. Quality; 5. Region; 6. Wine description. All of the labels had a brand name, 93% also had a grape or type of the wine on the label, the region was on 80% of the labels, 53% of the labels presented the quality of the wine, 28% had a description of the wine and 4% featured the name of the wine company (appendix content analysis, table 79, page 115). Differences and similarities per supermarket biggest difference between the three supermarkets was that the Albert Heijn had the biggest wine aisle of all three and was responsible for 47,5% of all labels. Jumbo had 27,8% of the labels and the Emté 24,7%. This same divide is seen in all categories where Albert Heijn has almost half of the elements found. In the Jumbo and Albert Heijn the most represented colour of wine is red wine, Emté has a slightly bigger assortment in white wines. Jumbo has almost as much white wines as they have rosé wines, while Albert Heijn and Emté have more white wines than rosé wines on their shelves. This gives the indication that rosé wines are not sold as much as white wines and white wines are not sold as much as red wines (see: table 74). Supermarkets: Total wines counted Total Albert Heijn Jumbo Emté Count % Count % Count % Count % White 97 54,8% 29 16,4% 51 28,8% ,4% Red ,6% 78 33,1% 48 20,3% ,6% Rosé 24 32,9% 28 38,4% 21 28,8% 73 15,0% Total ,5% ,8% ,7% ,0% Table 74: Total wines counted Colour of the wine label All supermarkets had wines with a white dominant background, but the Emté and Albert Heijn also had crème coloured backgrounds. For Albert Heijn this colour was not as much represented on the total count of wines with 8,2%, but for the Emté the number of crème coloured labels was more significant with 17,5% (appendix content analysis, table 75, page 111). As for the second dominant colour on the label the overall score showed that black was most popular, but by the Albert Heijn the colour red scored a little better than black. Also by the wines of the Jumbo 38

39 red was found often on the labels. Only the Emté did not have a lot of wine labels with red on them. colour pink and green was found more often in the Emté besides the colour black (appendix content analysis, table 76, page ). Visual design results in visual design variety were for all supermarkets very similar. biggest difference is seen for the visual design of grapes. Emté scored much higher on this as their own labelled wine had the image of grapes on them (appendix content analysis, table 77 & 78, page ). Text As for the style of the texts, all the supermarkets scored the least on the other styled fonts. Serif fonts were most popular for all three of the supermarkets. For all supermarkets more than 50,0% of the information on the labels had a serif font. biggest amount in comparison to the total count of information had the Emté. serif font was found in 65,1% of all information presented on the labels. Jumbo s serif information was 52,4% and that of Albert Heijn was 57,3% (appendix content analysis, table 79, 80, 81, 82 & 83 page ). Conclusion se results show that the most frequented labels have a white background with serif styled fonts for the information on the label. All of the labels feature a brand name, after that the grape or type of wine and the place of origin is mostly found on the label. Only 53% of the labels have a type of quality on the label and this can vary between an official country qualification to a personal given qualification. second most dominant colour on the label is most likely black, but the colour of the wine may also be presented on the label with a green or red colour. As for visual design, most labels had a picture or illustration. most featured type of picture is a landscape or a logo. biggest difference between the supermarkets was that the Albert Heijn has a bigger wine aisle and assortment in wines than the Jumbo and the Emté. Other difference were minimal as the results were very close together. conclusion for this is that the type of labels selected are the same or the wine producers all have a similar preferred style for their labels. se results are in line with the study that has been done in 2014 in Austria (König & Lick, 2014). Only they only researched the red wines in the supermarkets and included more supermarkets in their content analysis. ir conclusion was that most labels had a white background, a serif styled font and a picture of a landscape on it. biggest difference with the results above is that the landscape pictures are not a clear overall favourite. This can be due to the ample variety of wines and wine regions in the Dutch supermarkets, where Köning and Lick (2014) remarked that most wines were from Austria. 39

40 5. Conclusions 5.1 Conclusions Question one: What aspects are important in brand design? This question is answered by using the results out of the desk research that are presented in the chapter oretical Framework. Labels are important for consumers, without labels it would be impossible for the consumer to see the difference in products or for the brands to show what products are theirs. Packaging is a communication method for brands to connect with the consumer. With packaging they can provide information to the consumers and promote their brand. aspects of brand design on packaging, or for wine bottles, on labels that are most important are: illustrations, colours and typography (Boer, 2007; Wheeler, 2013). look of the label is not the only important aspect of packaging. Information can be given on the label and it is essential to provide as much information about the product as possible. Information can take away any uncertainties the consumer might have for a product. For information both the front label and the back label are important, but consumers value the look of the front label more than the back label. y will only read the back label if the front label is attractive to them (Boer, 2007; Thomas & Pickering, 2003). Another important aspect in brand design is knowing how well-known your brand is. If you have an unknown brand it is important to set yourself apart from other brands and show active shelf value. If your brand is known it is important that the consumer will recognize your product, without effort, on the shelves (Boer, 2007; Kotler & Armstrong, 2012; Wheeler, 2013). Question two: What are the findings from current research on wine labels? answer to this questions is answered by using the studies presented in the chapter oretical framework. most important conclusion derived from a review of the current research is that there is not one element that completely triggers a consumer buys a wine. re are a couple of elements needed on a label to convince the consumer. This is mostly a combination of the visual design and the information given on the label. se combined need to give the consumer a perception of good quality. This perceived perception may vary with the occasion they buy wine for (Schamel & Anderson, 2003; Sherman & Tuten, 2011; Tang & Cohen, 2014). Current research shows that the visual elements on wine labels are very important to trigger the consumer to a certain wine. visual elements need to fit with the quality perception of the consumers. visual elements that trigger the most consumers have to do with the colours, the type of font used, the imagery on the label and the shape of the label. colours encompass the colour of the background, the other colours used in the design of the label and the colour of the font. font is important as it can set the feel of the label. A curly font is perceived differently than an Arial type of font. imagery on the label are the pictures or illustrations on the label, but can also be abstract drawings or images and (brand)logo s. shape of the label can also be of influence, but colour is a big influence for the perception of a label with a different shape than the basic rectangular pattern (Boudreaux & Palmer, 2007; De Mello & Pires, 2009; Köning & Lick, 2014; Lombardo, 2012; Tang & Cohen, 2014). 40

41 Information is the second trigger for a consumer. wine label needs to have certain information to trigger associations within the consumer. Information of importance to the front label are: brand name, grape varietal and place of origin. If the consumer has had a positive experience with either one or all of the information given on the label, it will be more likely that the consumer will buy that wine. reputation of the grape, region and brand individually might also help the consumer in selecting your wine, if there is no previous experience. Consumers most likely buy wines they have bought before, but will try new wines faster if they have heard positive stories about the region, grape or brand from other people or from other sources (Boer, 2007; Bruwer et al, 2013; Schamel & Anderson, 2003; Sherman & Tuten, 2011; Tang & Cohen, 2014; Troncoso & Aguirre, 2006). Question three: What are Dutch regulations on wine labels? rules and regulations are all mentioned in the chapter oretical framework. re are many dangers involved in drinking alcohol and packing regulations could become a serious threat to the design of wine labels. effect of alcohol can have a negative influence and in Dutch law only people over the age of eighteen can buy alcoholic substances. It has become a rule for brands to inform and warn their buyers the effect their product can have. This means that certain information needs to be given to the consumers by printing it on the labels (Huyghe, 2014; Moodie, 2013; STIVA, 2013). Most rules about alcoholic consumption is about advertisement for their products but this the most important information that needs to be presented on all wine labels (Boer, 2007; Productschap wijn, 2013): 1. Name of the product 2. Name every substance that can cause allergies or intolerances that are used by making the product 3. amount of each ingredient used 4. amount of substance inside the bottle 5. minimum shelf life or the ultimate consumption date 6. Special storage conditions/user conditions 7. Name and the address of the importer 8. Country of origin or place of origin 9. effective alcohol percentage se rules do not affect the current outlook of the labels much, as all information is already on it and mostly on the back label. So for the front label the wine producers can be as creative as they want to be. Question four: What aspects of a wine label do Dutch consumers look at? aspects that are most important can be split up into two categories: visual design and information. Both need to trigger the consumer in order for them to be convinced that the wine they are buying will be one of good quality. Quality perception is different for every person, but the aspects that have a clear preference should always be taken into account. For visual design the colour of the background was chosen as most influential by the Dutch consumers surveyed. A lightly coloured background is preferred over other colours, a dark coloured background is agreeable as long as it fits with the type of wine. Text style is the second important thing on the label. style must give off a classy feel to the label, but not be over the top or old fashioned. Illustrations seem to be less important for the consumer. survey showed that it does have an influence as a couple of the winning labels were chosen for their pictures, but the participants of the interviews said 41

42 that the image needs to be relevant to the wines they are buying. For example: the image can fit with the name of the wine or with the type of food the wine fits well with. For information recognition is important in the selecting process of the participants of the research. Well-known brands have precedence over unknown brands. Not only the brand name can trigger recognition, also the grape and region can give the consumer reason to buy a wine. Previous experience with either of these aspects can be the deciding factor for a consumer to buy a wine. main reason for the participants of the interviews to buy a wine in the supermarket is for themselves or something that fits with what they are cooking. For gifts they are likely to spend more and rather go to a liquor store to get advice from a professional. Other elements that effected the participants of the interviews is deals and the signs on the shelves. Before looking at the label they evaluate deals and in the wine aisle they look at the taste indications on the shelves. After finding the correct shelf with the taste they are looking for they will scan the labels. Extra texts on the shelves with taste perception have a positive effect on the selection process of the participants of the interviews. re was also a difference analysed in the survey in the preference between women and men. elements have more influence on women than on men. Women gave more responses on other elements that influence their decision than the men had. Also the opinions varied more often by the women than it did by the men. Women more often chose different elements of design as popular element, that shows that the participants of the survey were more attracted to design than to information. Question five: Which aspects are presented on wine labels currently sold in supermarkets? content analysis was carried out by looking at five different elements: Background colour Second background colour Visual design Visual text Information on the label conclusion of the background colour is that white is the most frequently used colour for the background of all labels researched. A second background colour was less popular, but black was most often used. As for visual design, 80% of all the labels had an visual element. Pictures and illustrations were most frequently used and of these most were considered landscapes, followed by logo s. As far as text goes, the style that was most frequently used was a serif styled font printed in a bold manner. information this fonts presents is on all labels the brand name. After brand name the grape varietal or type of wine and place of origin were printed mostly on the labels. In comparison with the survey and interviews, these labels only partly respond to the preferences of the participants of the survey and the interviews. white coloured background is in line as is the style of the font and the information on the label. However, the survey respondents did value illustrations on some labels, they did not on all. interview participants explained that they only like an illustration when it is relevant or small enough to not take the attention away from the information on the label. refore, the wine brands could improve their labels to make illustrations less prominent and print the basic information clearly centred on the label. basic information should contain: Brand name 42

43 Grape varietal Place of origin Vintage year Main question: What aspects of wine labels, sold in supermarkets, are important for the Dutch wine consumer in buying a wine? aspects that can influence a Dutch wine consumers can be divided into two categories. Visual design is important in triggering the consumer to look closer at the information that is printed on the label. For visual design the participants of the research prefer a light coloured or white background. This gives a good basic vibe to the setting of the label. A white background indicates that the rest on the label needs to be clear to see with one look of the eye. Brightly coloured labels were not popular during the research, with the exception of a couple of black labels, that were less crowded than the other options given. White gives the best setting to a serif styled font. font must be boldly presented on the label, so that it is easy to read. Images are presented on a lot of the labels that are found in supermarkets. However, these are not always relevant to the wines and can trigger a negative response by the consumer. consumers don t appreciate prominent images and if they are on the label they need to be clearly relevant to the wine. y will mostly prefer relevant images to the name of the wine, the place of origin or to the grape varietal, otherwise a small logo is appreciated as well. se are the elements meant to get the consumers attention. Labels need more than an attractive design, it also needs to provide information to enhance the consumers quality perception. information on the label can give the consumer positive associations and increase the chance of being bought. Information that is most important for recognition are the brand name, grape varietal and the region of origin. Recognition with a brand name is the strongest association a consumer can have. If there are no known brands then positive experiences with either the grape or the region of origin can be the deciding factor for the consumer to buy the wine. To conclude these are the elements that are important to the respondents of the research: Colour of the background (white) Style of the font (serif, bold) Imagery (only when relevant and not too prominent) Brand name Grape varietal Region of origin 5.2 Recommendations To conclude the answers of the main questions the following do s and do not s can be given regarding wine labels in the supermarket: Do s: - Clear coloured background: Consumers prefer light coloured backgrounds, so that label will give a calm and elegant vibe. - Serif styled font: A serif styled font looks richer and gives a sense of quality to the label. It also makes it easy for consumers to read what is written on the label. - Relevant image: An image should not distract the consumer from the contents of the wine. An image may be presented on the label as long as it complements the name of the wine, is the logo 43

44 of the brand or gives information about the food that pairs well with it. imagery should not dominate the label. - Give basic information: Brand name, grape and region: This information can trigger positive associations within the consumer. consumer will be more inclined to buy a wine that is recognized, rather than one that is completely unknown to them. It will be very valuable to the wine and the consumer to give these basic information. - Taste perceptions on the shelves: Supermarkets are already doing this, but they can do better. taste perceptions as is are fine, but they might help the consumer with their associations and their search by giving examples of grapes with their taste perceptions. So if a consumer searches for a fruity and full bodied red wine, they could give examples of grapes that might have that quality. - Centre the information on the label: respondents preferred labels that had the information in the centre of the label, so they could see right away if the wine did or did not attract their attention. - Rectangular shaped labels: participants of the survey valued rectangular shaped labels over any other shaped label. Do not s: - Use of different colours: use of different colour is permitted as long as it is limited to two or three different hues. More colour will come across as too overwhelming and will not attract consumers. - Curly fonts: Curly fonts can be perceived as very high quality wine, but the Dutch consumer likes to know what is written and experiences curly fonts as hard to read. It is not likely that they will take a closer look at labels with curly fonts. - Prominent displayed images: Labels with big images on them are perceived as low quality as image takes precedence over information. respondents like to know what they are drinking and a label with too big an image will be perceived as irrelevant and messy. - Irrelevant information: information on the label must add to the taste perception of the wine. Unnecessary words, besides brand name, grape and region, is distracting to the consumer and will not be the convincing factor for buying a certain wine. Further research For further research I would advise to look more closely at the information part of the labels and what associations the brand name, grapes and regions can call upon. se can be thoroughly investigated for the Dutch market and give an overview of the most popular grapes or the grapes with the best associations. Also this research could be done on a much larger scale, so it can represent the Dutch population. Ideally the surveys and interviews could be carried out at big supermarkets, or they could sent out the survey via . variety in gender and age will be much greater on a bigger scale. research could include much more chains of supermarkets and give a representation of the difference in region. 5.3 Limitations limitations within the study where mostly due to time and research location. re were time limitations and scope limitations. With a longer run of the survey, much more respondents could have been reached. 44

45 With a larger sample of respondent it might have been possible for the significance to be calculated. For the survey results the limitation was the amount of respondents and the amount of elements asked after in each label set. limited amount of respondents and the large amount of elements caused the chiquadrat test in SPSS to fail. After putting elements together these tests still failed and could not show any significance in the answers given. By further limiting the elements too much information would have been lost. So on a larger sample of respondents, the chi-quadrat would not have failed. location of the researcher was also experienced as a disadvantage. Being in the same place as the research is about makes it easier to physically do something to make the research run more smoothly. For example the interviews were limited by the use of Skype. A face to face interview gives a lot more cues to the interviewer to address certain questions and answers further. Skype makes it more difficult to read body language and it is harder to process the results of the audio tape. re were also limits for the content analysis, as the pictures were taken in one week and not all the shelves were filled with the wines they had in the assortment. Assortments also change regularly. refore the content analysis would be only representative for the time the pictures were taken. Strong aspects of the research Beside the limitations there were also some strong points of the research. More people than the minimum amount of respondents were reached. Ten interviews were held even though the time limit was imminent. A content analysis was carried out for at least three supermarkets and over 400 labels were analysed. Lastly a clear preference in label design was concluded out of the participants of the research: y like a light coloured background, with an elegant serif styled font. y appreciate illustrations as long as they are relevant for the wine, or do not dominate the label. Small logos are the better option for an illustration. participants do not pick a label solely based on one element. female respondents of the survey seem to prefer multiple design based elements, while the men mostly chose one or two elements of the label they like. Also the decision is not only based on design, information is another important aspect. Recognition of the brand name was important for the participants of the survey, while recognition of the place of origin and grape varietal was also of influence to the participants of the interviews. A wine is picked in the supermarket based on an attractive design and information that is recognized as good quality. 45

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48 Appendix SPSS First questions SET SET SET SET SET SET SET SET SET SET Last question Interviews Interview questions Labels Code book Content analysis Total wines Colour of the background Second background colour Visual design Visual text

49 SPSS First questions Age vs. gender respondents of the survey Total year year year year year 70+ Gender Man 88; 64,7% Vrouw Figure 2: Gender respondents 48; 35,3% Man Count % geslacht 39,6% 33,3% 10,4% 8,3% 8,3% 0,0% 100,0% % leeftijd 30,6% 53,3% 20,8% 26,7% 100,0% 0,0% 35,3% % total 14,0% 11,8% 3,7% 2,9% 2,9% 0,0% 35,3% Woman Count % geslacht 48,9% 15,9% 21,6% 12,5% 0,0% 1,1% 100,0% % leeftijd 69,4% 46,7% 79,2% 73,3% 0,0% 100,0% 64,7% % total 31,6% 10,3% 14,0% 8,1% 0,0% 0,7% 64,7% Total Count % geslacht 45,6% 22,1% 17,6% 11,0% 2,9% 0,7% 100,0% % leeftijd 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % total 45,6% 22,1% 17,6% 11,0% 2,9% 0,7% 100,0% Table 1: Gender vs age respondents Age 4; 2,9% 1; 0,7% 15; 11,0% 24; 17,6% 62; 45,6% 30; 22,1% year year year year year 70+ Figure 1: Age respondents 49

50 RUNNING HEAD: THESIS JESSICA KOOIJMAN, SET 1 Gender Set 1: Which one of these labels would you choose? Total Label 1 Label 2 Label 3 Man Count % Gender 56,3% 18,8% 25,0% 100% % Label 35,1% 47,4% 30,0% 35,3% % Total 19,9% 6,6% 8,8% 35,3% Woman Count % Gender 56,8% 11,4% 31,8% 100,0% % Label 64,9% 52,6% 70,0% 64,7% % Total 36,8% 7,4% 20,6% 64,7% Total Count % Gender 56,6% 14,0% 29,4% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 56,6% 14,0% 29,4% 100,0% Table 2: Gender vs. labels set 1 Favourite label 29,4% 14,0% 56,6% Age Set 1: Which one of these labels would you choose? Total Label 1 Label 2 Label year Count % Age 46,8% 24,2% 29,0% 100,0% % Label 37,7% 78,9% 45,0% 45,6% % Total 21,3% 11,0% 13,2% 45,6% year Count % Age 66,7% 6,7% 26,7% 100,0% % Label 26,0% 10,5% 20,0% 22,1% % Total 14,7% 1,5% 5,9% 22,1% year Count % Age 70,8% 4,2% 25,0% 100,0% % Label 22,1% 5,3% 15,0% 17,6% % Total 12,5% 0,7% 4,4% 17,6% year Count % Age 53,3% 6,7% 40,0% 100,0% % Label 10,4% 5,3% 15,0% 11,0% % Total 5,9% 0,7% 4,4% 11,0% year Count % Age 50,0% 0,0% 50,0% 100,0% % Label 2,6% 0,0% 2,6% 2,9% % Total 1,5% 0,0% 1,5% 2,9% 70+ year Count % Age 100,0% 0,0% 0,0% 100,0% % Label 1,3% 0,0% 0,0% 0,7% % Total 0,7% 0,0% 0,0% 0,7% Total Count % Age 56,6% 14,0% 29,4% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 56,6% 14,0% 29,4% 100,0% Table 3: Age vs. labels set 1 Label 1 Label 2 Label 3 Figure 3: Favourite label set 1

51 Age Set 1: What attracted you the most in the chosen label? Total colour of colour style brand shape of Other the background of the font of the font name the label illustration year Count % Age 32,3% 1,6% 16,1% 3,3% 24,2% 16,1% 6,5% 100,0% % Label 41,7% 50,0% 58,8% 40,0% 51,7% 50,0% 26,7% 45,6% % Total 14,7% 0,7% 7,4% 1,5% 11,0% 7,4% 2,9% 45,6% year Count % Age 40,0% 3,3% 10,0% 3,3% 23,3% 16,7% 3,3% 100,0% % Label 25,0% 50,0% 17,6% 20,0% 24,1% 25,0% 6,7% 22,1% % Total 8,8% 0,7% 2,2% 0,7% 5,1% 3,7% 0,7% 22,1% year Count % Age 37,5% 0,0% 8,3% 6,7% 16,7% 8,3% 25,0% 100,0% % Label 18,8% 0,0% 11,8% 20,0% 13,8% 10,0% 40,0% 17,6% % Total 6,6% 0,0% 1,5% 0,7% 2,9% 1,5% 4,4% 17,6% year Count % Age 33,3% 0,0% 13,3% 6,7% 13,3% 20,0% 13,3% 100,0% % Label 10,4% 0,0% 11,8% 20,0% 11,8% 15,0% 13,3% 11,0% % Total 3,7% 0,0% 1,5% 0,7% 1,5% 2,2% 1,5% 11,0% year Count % Age 50,0% 0,0% 0,0% 0,0% 25,0% 0,0% 25,0% 100,0% % Label 4,2% 0,0% 0,0% 0,0% 3,4% 0,0% 6,7% 2,9% % Total 1,5% 0,0% 0,0% 0,0% 0,7% 0,0% 0,7% 2,9% 70+ year Count % Age 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% 100,0% % Label 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 6,7% 0,7% % Total 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% 0,7% Total Count % Age 35,3% 1,5% 12,5% 3,7% 21,3% 14,7% 11,0% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 35,3% 1,5% 12,5% 3,7% 21,3% 14,7% 11,0% 100,0% Table 4: Age vs. elements set 1 Labels Set 1: What attracted you the most in the chosen label? Total colour of colour style of brand shape Other the background of the font the font name of the label illustration Label 1 Count % Label 51,9% 2,6% 15,6% 1,3% 6,5% 9,1% 13,0% 100,0% % Element 83,3% 100,0% 70,6% 20,0% 17,2% 35,0% 66,7% 56,6% % Total 29,4% 1,5% 8,8% 0,7% 3,7% 5,1% 7,4% 56,6% Label 2 Count % Label 31,6% 0,0% 15,8% 5,3% 5,3% 36,8% 5,3% 100,0% % Element 12,5% 0,0% 17,6% 20,0% 3,4% 35,0% 6,7% 14,0% % Total 4,4% 0,0% 2,2% 0,7% 0,7% 5,1% 0,7% 14,0% Label 3 Count % Label 5,0% 0,0% 5,0% 7,5% 57,5% 15,0% 10,0% 100,0% 51

52 % Element 4,2% 0,0% 11,8% 60,0% 79,3% 30,0% 26,7% 29,4% % Total 1,5% 0,0% 1,5% 2,2% 16,9% 4,4% 2,9% 29,4% Total Count % Label 35,3% 1,5% 12,5% 3,7% 21,3% 14,7% 11,0% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 35,3% 1,5% 12,5% 3,7% 21,3% 14,7% 11,0% 100,0% Table 5: Labels vs. elements set 1 Gender Labels Set 1: What attracted you the most in the chosen label? Total colour of colour style of brand shape Other the background of the font the font name of the label illustration Man Label 1 Count % Label 59,3% 0,0% 7,4% 0,0% 3,7% 11,1% 18,5% 100,0% % Element 80,0% 0,0% 40,0% 0,0% 11,1% 42,9% 83,3% 56,3% % Gender 33,3% 0,0% 4,2% 0,0% 2,1% 6,3% 10,4% 56,3% Label 2 Count % Label 33,3% 0,0% 22,2% 11,1% 11,1% 22,2% 0,0% 100,0% % Element 15,0% 0,0% 40,0% 100,0% 11,1% 28,6% 0,0% 18,8% % Gender 6,3% 0,0% 4,2% 2,1% 2,1% 4,2% 0,0% 18,8% Label 3 Count % Label 8,3% 0,0% 8,3% 0,0% 58,3% 16,7% 8,3% 100,0% % Element 5,0% 0,0% 20,0% 0,0% 77,8% 28,6% 16,7% 25,0% % Gender 2,1% 0,0% 2,1% 0,0% 14,6% 4,2% 2,1% 25,0% Total Count % Label 41,7% 0,0% 10,4% 2,1% 18,8% 14,6% 12,5% 100,0% % Element 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 41,7% 0,0% 10,4% 2,1% 18,8% 14,6% 12,5% 100,0% Woman Label 1 Count % Label 48,0% 4,0% 20,0% 2,0% 8,0% 8,0% 10,0% 100,0% % Element 85,7% 100,0% 83,3% 25,0% 20,0% 30,8% 55,6% 56,8% % Gender 27,3% 2,3% 11,4% 1,1% 4,5% 4,5% 5,7% 56,8% Label 2 Count % Label 30,0% 0,0% 10,0% 0,0% 0,0% 50,0% 10,0% 100,0% % Element 10,7% 0,0% 8,3% 0,0% 0,0% 38,5% 11,1% 11,4% % Gender 3,4% 0,0% 1,1% 0,0% 0,0% 5,7% 1,1% 11,4% Label 3 Count % Label 3,6% 0,0% 3,6% 10,7% 57,1% 14,3% 10,7% 100,0% % Element 3,6% 0,0% 8,3% 75,0% 80,0% 30,8% 33,3% 31,8% % Gender 1,1% 0,0% 1,1% 3,4% 18,2% 4,5% 3,4% 31,8% Total Count % Label 31,8% 2,3% 13,6% 4,5% 22,7% 14,8% 10,2% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 31,8% 2,3% 13,6% 4,5% 22,7% 14,8% 10,2% 100,0% Total Label 1 Count % Label 51,9% 2,6% 15,6% 1,3% 6,5% 9,1% 13,0% 100,0% 52

53 % Element 83,3% 100,0% 70,6% 20,0% 17,2% 35,0% 66,7% 56,6% % Gender 29,4% 1,5% 8,8% 0,7% 3,7% 5,1% 7,4% 56,6% Label 2 Count % Label 31,6% 0,0% 15,8% 5,3% 5,3% 36,8% 5,3% 100,0% % Element 12,5% 0,0% 17,6% 20,0% 3,4% 35,0% 6,7% 14,0% % Gender 4,4% 0,0% 2,2% 0,7% 0,7% 5,1% 0,7% 14,0% Label 3 Count % Label 5,0% 0,0% 5,0% 7,5% 57,5% 15,0% 10,0% 100,0% % Element 4,2% 0,0% 11,8% 60,0% 79,3% 30,0% 26,7% 29,4% % Gender 1,5% 0,0% 1,5% 2,2% 16,9% 4,4% 2,9% 29,4% Total Count % Label 35,3% 1,5% 12,5% 3,7% 21,3% 14,7% 11,0% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 35,3% 1,5% 12,5% 3,7% 21,3% 14,7% 11,0% 100,0% Table 6: Gender and labels vs. elements set 1 Other important elements set 1 None 8,7% illustration 19,4% Shape of the label 11,7% Brand name 6,6% Style of the font 28,6% Colour of the font 7,7% Colour of the background 17,3% 0,00% 5,00% 10,00% 15,00% 20,00% 25,00% 30,00% 35,00% Other important elements Figure 4: Other important elements set 1 53

54 Gender Labels Set 1: What are other important elements for you? Total colour of the colour of the style of the brand shape of None background font font name the label illustration Man Label 1 Count % Labels 7,7% 5,1% 30,8% 5,1% 25,6% 10,3% 15,4% 100,0% % Gender 42,9% 100,0% 60,0% 100,0% 76,9% 40,0% 60,0% 60,9% % Total 16,7% 33,3% 34,3% 25,0% 66,7% 21,1% 60,0% 35,1% Label 2 Count % Labels 0,0% 0,0% 18,2% 0,0% 27,3% 27,3% 27,3% 100,0% % Gender 0,0% 0,0% 10,0% 0,0% 23,1% 30,0% 30,0% 17,2% % Total 0,0% 0,0% 28,6% 0,0% 75,0% 42,9% 75,0% 39,3% Label 3 Count % Labels 28,6% 0,0% 42,9% 0,0% 0,0% 21,4% 7,1% 100,0% % Gender 57,1% 0,0% 30,0% 0,0% 0,0% 30,0% 10,0% 21,9% % Total 30,8% 0,0% 42,9% 0,0% 0,0% 25,0% 33,3% 24,6% Total Count % Labels 10,9% 3,1% 31,3% 3,1% 20,3% 15,6% 15,6% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 20,6% 13,3% 35,7% 15,4% 56,5% 26,3% 58,8% 32,7% Woman Label 1 Count % Labels 20,8% 5,6% 31,9% 8,3% 6,9% 20,8% 5,6% 100,0% % Gender 55,6% 30,8% 63,9% 54,5% 50,0% 53,6% 57,1% 54,5% % Total 83,3% 66,7% 65,7% 75,0% 33,4% 79,0% 40,0% 64,9% Label 2 Count % Labels 17,7% 5,9% 29,4% 11,8% 5,9% 23,5% 5,9% 100,0% % Gender 11,1% 7,7% 13,9% 18,2% 10,0% 14,3% 14,3% 12,9% % Total 100,0% 100,0% 71,4% 100,0% 25,0% 57,1% 25,0% 60,7% Label 3 Count % Labels 20,9% 18,6% 18,6% 7,0% 9,3% 20,9% 4,7% 100,0% % Gender 33,3% 61,5% 22,2% 27,3% 40,0% 32,1% 28,6% 32,6% % Total 69,2% 100,0% 57,1% 100,0% 100,0% 75,0% 66,7% 75,4% Total Count % Labels 20,5% 9,8% 27,3% 8,3% 7,6% 21,2% 5,3% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 79,4% 86,7% 64,3% 84,6% 43,5% 73,7% 41,2% 67,3% Total Label 1 Count % Labels 16,2% 5,4% 31,% 7,2% 13,5% 17,1% 9,0% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 52,9% 40,0% 62,5% 61,5% 65,2% 50,0% 58,8% 56,6% Label 2 Count % Labels 10,7% 3,6% 25,0% 7,1% 14,3% 25,0% 14,3% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 8,8% 6,7% 12,5% 15,4% 17,4% 18,4% 23,5% 14,3% Label 3 Count % Labels 22,8% 14,0% 24,6% 5,3% 7,0 21,1% 5,3% 100,0% 54

55 % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 38,2% 53,3% 25,0% 23,1% 17,4% 31,6% 17,6% 29,1% Total Count % Labels 17,3% 7,7% 28,6% 6,6% 11,7% 19,4% 8,7% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% Table 7: Gender and labels vs. other important elements set 1 Age Set 1: What attracted you the most in the chosen label? Total colour of the colour of style of brand name shape of illustration None background the font the font the label year Count % Age 14,3% 13,3% 27,6% 5,1% 13,3% 22,5% 4,1% 100,0% % Label 41,2% 86,7% 48,2% 38,5% 56,5% 57,9% 23,5% 41,2% % Total 7,1% 6,6% 13,8% 2,6% 6,6% 11,3% 2,1% 50,0% year Count % Age 19,1% 2,4% 31,0% 7,1% 7,1% 21,4% 11,9% 100,0% % Label 23,5% 6,7% 23,2% 23,1% 13,0% 23,7% 29,4% 23,5% % Total 4,1% 0,5% 6,6% 1,5% 1,5% 4,6% 2,6% 21,4% year Count % Age 32,1% 3,6% 28,6% 7,1% 7,1% 1,5% 1,5% 100,0% % Label 26,5% 6,7% 14,3% 15,4% 8,7% 7,9% 17,6% 26,5% % Total 4,6% 0,5% 4,1% 1,0% 1,0% 1,5% 1,5% 14,3% year Count % Age 5,0% 0,0% 30,0% 15,0% 20,0% 10,0% 20,0% 100,0% % Label 2,9% 0,0% 10,7% 23,1% 17,4% 5,3% 23,5% 2,9% % Total 0,5% 0,0% 3,1% 1,5% 2,1% 1,0% 2,1% 10,2% year Count % Age 14,3% 0,0% 28,6% 0,0% 14,3% 28,6% 14,3% 100,0% % Label 2,9% 0,0% 3,6% 0,0% 4,3% 5,3% 5,9% 2,9% % Total 0,5% 0,0% 1,0% 0,0% 0,5% 1,0% 0,5% 3,6% 70+ year Count % Age 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 2,9% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 2,9% % Total 0,5% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,5% Total Count % Age 17,4% 7,7% 28,6% 6,6% 11,8% 19,4% 8,7% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% Table 8: Age vs other important elements set 1 55

56 SET 2 Gender Set 2: Which one of these labels would you choose? Total Label 1 Label 2 Label 3 Man Count % Gender 29,2% 52,1% 18,8% 100,0% % Label 28,0% 42,4% 33,3% 35,3% % Total 10,3% 18,4% 6,6% 35,3% Woman Count % Gender 40,9% 38,6% 20,5% 100,0% % Label 72,0% 57,6% 66,7% 64,7% % Total 26,5% 25,0% 13,2% 64,7% Total Count % Gender 36,8% 43,4% 19,9% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 36,8% 43,4% 19,9% 100,0% Table 9: Gender vs. labels set 2 Favourite label 19,9% 43,4% 36,8% Label 1 Label 2 Label 3 Age Set 2: Which one of these labels would you choose? Total Label 1 Label 2 Label year Count % Age 45,2% 37,1% 17,7% 100,0% % Label 56,0% 39,0% 40,7% 45,6% % Total 20,6% 16,9% 8,1% 45,6% year Count % Age 30,0% 46,7% 23,3% 100,0% % Label 18,0% 23,7% 25,9% 22,1% % Total 6,6% 10,3% 5,1% 22,1% year Count % Age 16,7% 66,7% 16,7% 100,0% % Label 8,0% 27,1% 14,8% 17,6% % Total 2,9% 11,8% 2,9% 17,6% year Count % Age 46,7% 33,3% 20,0% 100,0% % Label 14,0% 8,5% 11,1% 11,0% % Total 5,1% 3,7% 2,2% 11,0% year Count % Age 25,0% 25,0% 50,0% 100,0% % Label 2,0% 1,7% 7,4% 2,9% % Total 0,7% 0,7% 1,5% 2,9% 70+ year Count % Age 100,0% 0,0% 0,0% 100,0% % Label 2,0% 0,0% 0,0% 0,7% % Total 0,7% 0,0% 0,0% 0,7% Total Count % Age 36,8% 43,4% 19,9% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 36,8% 43,4% 19,9% 100,0% Table 10: Age vs. labels set 2 Figure 5: Favourite label set 2 56

57 Age Set 2: What attracted you the most in the chosen label? Total colour of style of the brand colours used on the place of Other the font font name label illustration origin year Count % Age 0,0% 8,1% 4,8% 19,4% 59,7% 6,5% 1,6% 100,0% % Label 0,0% 55,6% 50,0% 52,2% 50,0% 28,6% 12,5% 45,6% % Total 0,0% 3,7% 2,2% 8,8% 27,2% 2,9% 0,7% 45,6% year Count % Age 3,3% 3,3% 3,3% 20,0% 56,7% 10,0% 3,3% 100,0% % Label 50,0% 11,1% 16,7% 26,1% 23,0% 21,4% 12,5% 22,1% % Total 0,7% 0,7% 0,7% 4,4% 12,5% 2,2% 0,7% 22,1% year Count % Age 0,0% 12,5% 4,2% 12,5% 41,7% 16,7% 12,5% 100,0% % Label 0,0% 33,3% 16,7% 13,0% 13,5% 28,6% 37,5% 17,6% % Total 0,0% 2,2% 0,7% 2,2% 7,4% 2,9% 2,2% 17,6% year Count % Age 0,0% 0,0% 6,7% 13,3% 46,7% 20,0% 13,3% 100,0% % Label 0,0% 0,0% 16,7% 8,7% 9,5% 21,4% 25,0% 11,0% % Total 0,0% 0,0% 0,7% 1,5% 5,1% 2,2% 1,5% 11,0% year Count % Age 0,0% 0,0% 0,0% 0,0% 75,0% 0,0% 25,0% 100,0% % Label 0,0% 0,0% 0,0% 0,0% 4,1% 0,0% 12,5% 2,9% % Total 0,0% 0,0% 0,0% 0,0% 2,2% 0,0% 0,7% 2,9% 70+ year Count % Age 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 50,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% % Total 0,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% Total Count % Age 1,5% 6,6% 4,4% 16,9% 54,4% 10,3% 5,9% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 1,5% 6,6% 4,4% 16,9% 54,4% 10,3% 5,9% 100,0% Table 11: Age vs. elements set 2 Labels Set 2: What attracted you the most in the chosen label? Total colour of style of the brand colours used on the illustration place of Other the font font name label origin Label 1 Count % Label 2,0% 4,0% 6,0% 16,0% 60,0% 4,0% 8,0% 100,0% % Element 50,0% 22,2% 50,0% 34,8% 40,5% 14,3% 50,0% 36,8% % Total 0,7% 1,5% 2,2% 5,9% 22,1% 1,5% 2,9% 36,8% Label 2 Count % Label 1,7% 10,2% 5,1% 20,3% 45,8% 10,2% 6,8% 100,0% % Element 50,0% 66,7% 50,0% 52,2% 36,5% 42,9% 50,0% 43,4% % Total 0,7% 4,4% 2,2% 8,8% 19,9% 4,4% 2,9% 43,4% Label 3 Count % Label 0,0% 3,7% 0,0% 11,1% 63,0% 22,2% 0,0% 100,0% 57

58 % Element 0,0% 11,1% 0,0% 13,0% 23,0% 42,9% 0,0% 19,9% % Total 0,0% 0,7% 0,0% 2,2% 12,5% 4,4% 0,0% 19,9% Total Count % Label 1,5% 6,6% 4,4% 16,9% 54,4% 10,3% 5,9% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 1,5% 6,6% 4,4% 16,9% 54,4% 10,3% 5,9% 100,0% Table 12: Labels vs. elements set 2 Gender Labels Set 2: What attracted you the most in the chosen label? Total colour of style of the brand colours used on the illustration place of Other the font font name label origin Man Label 1 Count % Label 0,0% 7,1% 7,1% 35,7% 42,9% 7,1% 0,0% 100,0% % Element 0,0% 50,0% 50,0% 50,0% 27,3% 12,5% 0,0% 29,2% % Gender 0,0% 2,1% 2,1% 10,4% 12,5% 2,1% 0,0% 29,2% Label 2 Count % Label 4,0% 4,0% 4,0% 12,0% 40,0% 24,0% 12,0% 100,0% % Element 100,0% 50,0% 50,0% 30,0% 45,5% 75,0% 100,0% 52,1% % Gender 2,1% 2,1% 2,1% 6,3% 20,8% 12,5% 6,3% 52,1% Label 3 Count % Label 0,0% 0,0% 0,0% 22,2% 66,7% 11,1% 0,0% 100,0% % Element 0,0% 0,0% 0,0% 20,0% 27,3% 12,5% 0,0% 18,8% % Gender 0,0% 0,0% 0,0% 4,2% 12,5% 2,1% 0,0% 18,8% Total Count % Label 2,1% 4,2% 4,2% 20,8% 45,8% 16,7% 6,3% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 2,1% 4,2% 4,2% 20,8% 45,8% 16,7% 6,3% 100,0% Woman Label 1 Count % Label 2,8% 2,8% 5,6% 8,3% 66,7% 2,8% 11,1% 100,0% % Element 100,0% 14,3% 50,0% 23,1% 46,2% 16,7% 80,0% 40,9% % Gender 1,1% 1,1% 2,3% 3,4% 27,3% 1,1% 4,5% 40,9% Label 2 Count % Label 0,0% 14,7% 5,9% 26,5% 50,0% 0,0% 2,9% 100,0% % Element 0,0% 71,4% 50,0% 69,2% 32,7% 0,0% 20,0% 38,6% % Gender 0,0% 5,7% 2,3% 10,2% 19,3% 0,0% 1,1% 38,6% Label 3 Count % Label 0,0% 5,6% 0,0% 5,6% 61,1% 27,8% 0,0% 100,0% % Element 0,0% 14,3% 0,0% 7,7% 21,2% 83,3% 0,0% 20,5% % Gender 0,0% 1,1% 0,0% 1,1% 12,5% 5,7% 0,0% 20,5% Total Count % Label 1,1% 8,0% 4,5% 14,8% 59,1% 6,8% 5,7% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 1,1% 8,0% 4,5% 14,8% 59,1% 6,8% 5,7% 100,0% Total Label 1 Count % Label 2,0% 4,0% 6,0% 16,0% 60,0% 4,0% 8,0% 100,0% 58

59 % Element 50,0% 22,2% 50,0% 34,8% 40,5% 14,3% 50,0% 36,8% % Gender 0,7% 1,5% 2,2% 5,9% 22,1% 1,5% 2,9% 36,8% Label 2 Count % Label 1,7% 10,2% 5,1% 20,3% 45,8% 10,2% 6,8% 100,0% % Element 50,0% 66,7% 50,0% 52,2% 36,5% 42,9% 50,0% 43,4% % Gender 0,7% 4,4% 2,2% 8,8% 19,9% 4,4% 2,9% 43,4% Label 3 Count % Label 0,0% 3,7% 0,0% 11,1% 63,0% 22,2% 0,0% 100,0% % Element 0,0% 11,1% 0,0% 13,0% 23,0% 42,9% 0,0% 19,9% % Gender 0,0% 0,7% 0,0% 2,2% 12,5% 4,4% 0,0% 19,9% Total Count % Label 1,5% 6,6% 4,4% 16,9% 54,4% 10,3% 5,9% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 1,5% 6,6% 4,4% 16,9% 54,4% 10,3% 5,9% 100,0% Table 13: Gender and labels vs. elements set 2 Set 2: Other important elements Nee 15,6% place of origin 14,4% illustration 15,0% Colours used on the label 20,0% Brand name 7,2% Style of the font 20,0% Colour of the font 7,8% 0,00% 5,00% 10,00% 15,00% 20,00% 25,00% Other important elements Figure 6: Other important elements set 2 59

60 Gender Labels Set 2: What are other important elements for you? Total colour of the style of the brand colours used on illustration place of None font font name the label origin Man Label 1 Count % Labels 0,0% 27,8% 0,0% 27,8% 11,1% 5,6% 27,8% 100,0% % Gender 0,0% 45,5% 0,0% 38,5% 20,0% 16,7% 45,5% 31,0% % Total 0,0% 2,8% 0,0% 2,8% 1,1% 0,6% 2,8% 10,0% Label 2 Count % Labels 12,9% 19,4% 6,5% 22,6% 16,1% 12,9% 9,7% 100,0% % Gender 80,0% 54,5% 100,0% 53,8% 50,0% 66,7% 27,3% 53,5% % Total 2,2% 3,3% 1,1% 3,9% 2,8% 2,2% 1,7% 17,2% Label 3 Count % Labels 11,1% 0,0% 0,0% 11,1% 33,3% 11,1% 33,3% 100,0% % Gender 20,0% 0,0% 0,0% 7,7% 30,0% 16,7% 27,3% 15,5% % Total 0,6% 0,0% 0,0% 0,6% 1,7% 0,6% 1,7% 5,0% Total Count % Labels 8,6% 19,0% 3,5% 22,4% 17,2% 10,3% 19,0% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 2,8% 6,1% 1,1% 7,2% 5,6% 3,3% 6,1% 32,2% Woman Label 1 Count % Labels 9,3% 22,2% 9,3% 24,1% 11,1% 11,1% 13,0% 100,0% % Gender 55,6% 48,0% 45,5% 56,5% 35,3% 30,0% 41,2% 44,3% % Total 2,8% 6,7% 2,8% 7,2% 3,3% 3,3% 3,9% 30,0% Label 2 Count % Labels 8,3% 25,0% 10,4% 16,7% 16,7% 16,7% 6,3% 100,0% % Gender 44,4% 48,0% 45,5% 34,8% 47,1% 40,0% 17,6% 39,3% % Total 2,2% 6,7% 2,8% 4,4% 4,4% 4,4% 1,7% 26,7% Label 3 Count % Labels 0,0% 5,0% 5,0% 10,0% 15,0% 30,0% 35,0% 100,0% % Gender 0,0% 4,0% 9,1% 8,7% 17,6% 30,0% 41,2% 16,4% % Total 0,0% 0,6% 0,6% 1,1% 1,7% 3,3% 3,9% 11,1 Total Count % Labels 7,4% 20,5% 9,0% 18,9% 13,9% 16,4% 13,9% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 5,0% 13,9% 6,1% 12,8% 9,4% 11,1% 9,4% 67,8% Total Label 1 Count % Labels 6,9% 23,6% 6,9% 25,0% 11,1% 9,7% 16,7% 100,0% % Gender 35,7% 47,2% 38,5% 50,0% 29,6% 26,9% 42,9% 100,0% % Total 2,8% 9,4% 2,8% 10,0% 4,4% 3,9% 6,7% 40,0% Label 2 Count % Labels 10,1% 22,8% 8,9% 19,0% 16,5% 15,2% 7,6% 100,0% % Gender 57,1% 50,0% 53,8% 41,7% 48,1% 46,2% 21,4% 100,0% % Total 4,4% 10,0% 3,9% 8,3% 7,2% 6,7% 3,3% 43,9% Label 3 Count % Labels 3,4% 3,4% 3,4% 10,4% 20,7% 24,1% 34,5% 100,0% 60

61 % Gender 7,1% 2,8% 7,7% 8,3% 22,2% 26,9% 35,7% 100,0% % Total 0,6% 0,6% 0,6% 1,7% 3,3% 3,9% 5,6% 16,1% Total Count % Labels 7,8% 20,0% 7,2% 20,0% 15,0% 14,4% 15,6% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% Table 14: Gender and labels vs. other important element set 2 Age Set 2: What attracted you the most in the chosen label? Total colour of style of the brand colours used on the illustration place of None the font font name label origin year Count % Age 7,0% 25,6% 5,8% 16,3% 17,4% 14,0% 14,0% 100,0% % Label 42,9% 61,1% 38,5% 38,9% 55,6% 46,2% 42,9% 47,8% % Total 3,3% 12,2% 2,8% 7,8% 8,3% 6,7% 6,7% 47,8% year Count % Age 8,1% 19,0% 8,1% 19,0% 13,5% 13,5% 19,0% 100,0% % Label 21,4% 19,4% 23,1% 19,4% 18,5% 19,2% 25,0% 20,6% % Total 1,7% 3,9% 1,7% 3,9% 2,8% 2,8% 3,9% 20,6% year Count % Age 6,7% 10,0% 3,3% 33,3% 16,7% 13,3% 16,7% 100,0% % Label 14,3% 8,3% 7,7% 27,8% 18,5% 15,4% 17,9% 16,7% % Total 1,1% 1,7% 0,6% 5,6% 2,8% 2,2% 2,8% 16,7% year Count % Age 9,9% 18,2% 18,2% 13,6% 4,6% 22,7% 13,6% 100,0% % Label 14,3% 11,1% 30,8% 8,3% 3,7% 19,2% 10,7% 12,2% % Total 1,1% 2,2% 2,2% 1,7% 0,6% 2,8% 1,7% 12,2% year Count % Age 25,0% 0,0% 0,0% 50,0% 25,0% 0,0% 0,0% 100,0% % Label 7,1% 0,0% 0,0% 5,6% 3,7% 0,0% 0,0% 2,2% % Total 0,6% 0,0% 0,0% 1,1% 0,6% 0,0% 0,0% 2,2% 70+ year Count % Age 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% 100,0% % Label 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 3,6% 0,6% % Total 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,6% 0,6% Total Count % Age 7,8% 20,0% 7,2% 20,0% 15,0% 14,4% 15,6% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 7,8% 20,0% 7,2% 20,0% 15,0% 14,4% 15,6% 100,0% Table 15: Age vs. other important elements set 2 61

62 SET 3 Gender Set 3: Which one of these labels would you choose? Total Label 1 Label 2 Label 3 Man Count % Gender 64,6% 22,9% 12,5% 100,0% % Label 42,5% 34,4% 19,4% 35,3% % Total 22,8% 8,1% 4,4% 35,3% Woman Count % Gender 47,7% 23,9% 28,4% 100,0% % Label 57,5% 65,6% 80,6% 64,7% % Total 30,9% 15,4% 18,4% 64,7% Total Count % Gender 53,7% 23,5% 22,8% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 53,7% 23,5% 22,8% 100,0% Table 16: Gender vs. labels set 3 Favourite label 22,8% 23,5% 53,7% Age Set 3: Which one of these labels would you choose? Total Label 1 Label 2 Label year Count % Age 50,0% 22,6% 27,4% 100,0% % Label 42,5% 43,8% 54,8% 45,6% % Total 22,8% 10,3% 12,5% 45,6% year Count % Age 50,0% 30,0% 20,0% 100,0% % Label 20,5% 28,1% 19,4% 22,1% % Total 11,0% 6,6% 4,4% 22,1% year Count % Age 54,2% 20,8% 25,0% 100,0% % Label 17,8% 15,6% 19,4% 17,6% % Total 9,6% 3,7% 4,4% 17,6% year Count % Age 73,3% 13,3% 13,3% 100,0% % Label 15,1% 6,3% 6,5% 11,0% % Total 8,1% 1,5% 1,5% 11,0% year Count % Age 50,0% 50,0% 0,0% 100,0% % Label 2,7% 6,3% 0,0% 2,9% % Total 1,5% 1,5% 0,0% 2,9% 70+ year Count % Age 100,0% 0,0% 0,0% 100,0% % Label 1,4% 0,0% 0,0% 0,7% % Total 0,7% 0,0% 0,0% 0,7% Total Count % Age 53,7% 23,5% 22,8% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 53,7% 23,5% 22,8% 100,0% Table 17: Age vs labels set 3 Label 1 Label 2 Label 3 Figure 7: Favourite label set 3 62

63 Age Set 3: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name colours used on the label illustration Other year Count % Age 53,2% 3,2% 6,5% 1,6% 16,1% 14,5% 4,8% 100,0% % Label 51,6% 100,0% 50,0% 14,3% 37,0% 47,4% 33,3% 45,6% % Total 24,3% 1,5% 2,9% 0,7% 7,4% 6,6% 2,2% 45,6% year Count % Age 46,7% 0,0% 0,0% 10,0% 23,3% 16,7% 3,3% 100,0% % Label 21,9% 0,0% 0,0% 42,9% 25,9% 26,3% 11,1% 22,1% % Total 10,3% 0,0% 0,0% 2,2% 5,1% 3,7% 0,7% 22,1% year Count % Age 37,5% 0,0% 16,7% 8,3% 20,8% 4,2% 12,5% 100,0% % Label 14,1% 0,0% 50,0% 28,6% 18,5% 5,3% 33,3% 17,6% % Total 6,6% 0,0% 2,9% 1,5% 3,7% 0,7% 2,2% 17,6% year Count % Age 33,3% 0,0% 0,0% 6,7% 26,7% 26,7% 6,7% 100,0% % Label 7,8% 0,0% 0,0% 14,3% 14,8% 21,1% 11,1% 11,0% % Total 3,7% 0,0% 0,0% 0,7% 2,9% 2,9% 0,7% 11,0% year Count % Age 50,0% 0,0% 0,0% 0,0% 25,0% 0,0% 25,0% 100,0% % Label 3,1% 0,0% 0,0% 0,0% 3,7% 0,0% 11,1% 2,9% % Total 1,5% 0,0% 0,0% 0,0% 0,7% 0,0% 0,7% 2,9% 70+ year Count % Age 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 1,6% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% % Total 0,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% Total Count % Age 47,1% 1,5% 5,9% 5,1% 19,9% 14,0% 6,6% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 47,1% 1,5% 5,9% 5,1% 19,9% 14,0% 6,6% 100,0% Table 18: Age vs elements set 3 Labels Set 3: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name colours used on the label illustration Other Label 1 Count % Label 45,2% 1,4% 5,5% 2,7% 20,5% 16,4% 8,2% 100,0% % Element 51,6% 50,0% 50,0% 28,6% 55,6% 63,2% 66,7% 53,7% % Total 24,3% 0,7% 2,9% 1,5% 11,0% 8,8% 4,4% 53,7% Label 2 Count % Label 53,1% 3,1% 6,3% 9,4% 6,3% 12,5% 9,4% 100,0% % Element 26,6% 50,0% 25,0% 42,9% 7,4% 21,1% 33,3% 23,5% % Total 12,5% 0,7% 1,5% 2,2% 1,5% 2,9% 2,2% 23,5% Label 3 Count % Label 45,2% 0,0% 6,5% 6,5% 32,3% 9,7% 0,0% 100,0% 63

64 % Element 21,9% 0,0% 25,0% 28,6% 37,0% 15,8% 0,0% 22,8% % Total 10,3% 0,0% 1,5% 1,5% 7,4% 2,2% 0,0% 22,8% Total Count % Label 47,1% 1,5% 5,9% 5,1% 19,9% 14,0% 6,6% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 47,1% 1,5% 5,9% 5,1% 19,9% 14,0% 6,6% 100,0% Table 19: Labels vs. elements set 3 Gender Labels Set 3: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name colours used on the label illustration Other Man Label 1 Count % Label 51,6% 3,2% 6,5% 3,2% 16,1% 12,9% 6,5% 100,0% % Element 69,6% 100,0% 50,0% 33,3% 62,5% 57,1% 100,0% 64,6% % Gender 33,3% 2,1% 4,2% 2,1% 10,4% 8,3% 4,2% 64,6% Label 2 Count % Label 63,6% 0,0% 0,0% 18,2% 9,1% 9,1% 0,0% 100,0% % Element 30,4% 0,0% 0,0% 66,7% 12,5% 14,3% 0,0% 22,9% % Gender 14,6% 0,0% 0,0% 4,2% 2,1% 2,1% 0,0% 22,9% Label 3 Count % Label 0,0% 0,0% 33,3% 0,0% 33,3% 33,3% 0,0% 100,0% % Element 0,0% 0,0% 50,0% 0,0% 25,0% 28,6% 0,0% 12,5% % Gender 0,0% 0,0% 4,2% 0,0% 4,2% 4,2% 0,0% 12,5% Total Count % Label 47,9% 2,1% 8,3% 6,3% 16,7% 14,6% 4,2% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 47,9% 2,1% 8,3% 6,3% 16,7% 14,6% 4,2% 100,0% Woman Label 1 Count % Label 40,5% 0,0% 4,8% 2,4% 23,8% 19,0% 9,5% 100,0% % Element 41,5% 0,0% 50,0% 25,0% 52,6% 66,7% 57,1% 47,7% % Gender 19,3% 0,0% 2,3% 1,1% 11,4% 9,1% 4,5% 47,7% Label 2 Count % Label 47,6% 4,8% 9,5% 4,8% 4,8% 14,3% 14,3% 100,0% % Element 24,4% 100,0% 50,0% 25,0% 5,3% 25,0% 42,9% 23,9% % Gender 11,4% 1,1% 2,3% 1,1% 1,1% 3,4% 3,4% 23,9% Label 3 Count % Label 56,0% 0,0% 0,0% 8,0% 32,0% 4,0% 0,0% 100,0% % Element 34,1% 0,0% 0,0% 50,0% 42,1% 8,3% 0,0% 28,4% % Gender 15,9% 0,0% 0,0% 2,3% 9,1% 1,1% 0,0% 28,4% Total Count % Label 46,6% 1,1% 4,5% 4,5% 21,6% 13,6% 8,0% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 46,6% 1,1% 4,5% 4,5% 21,6% 13,6% 8,0% 100,0% Total Label 1 Count % Label 45,2% 1,4% 5,5% 2,7% 20,5% 16,4% 8,2% 100,0% 64

65 % Element 51,6% 50,0% 50,0% 28,6% 55,6% 63,2% 66,7% 53,7% % Gender 24,3% 0,7% 2,9% 1,5% 11,0% 8,8% 4,4% 53,7% Label 2 Count % Label 53,1% 3,1% 6,3% 9,4% 6,3% 12,5% 9,4% 100,0% % Element 26,6% 50,0% 25,0% 42,9% 7,4% 21,1% 33,3% 23,5% % Gender 12,5% 0,7% 1,5% 2,2% 1,5% 2,9% 2,2% 23,5% Label 3 Count % Label 45,2% 0,0% 6,5% 6,5% 32,3% 9,7% 0,0% 100,0% % Element 21,9% 0,0% 25,0% 28,6% 37,0% 15,8% 0,0% 22,8% % Gender 10,3% 0,0% 1,5% 1,5% 7,4% 2,2% 0,0% 22,8% Total Count % Label 47,1% 1,5% 5,9% 5,1% 19,9% 14,0% 6,6% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 47,1% 1,5% 5,9% 5,1% 19,9% 14,0% 6,6% 100,0% Table 20: Gender and labels vs. elements set 3 Other important elements None illustration 14,0% 15,6% colours used on the label 20,1% brand name 7,8% style of the font 24,0% colour of the font 5,6% colour of the background 12,8% Figure 8: Other important elements set 3 0,00% 5,00% 10,00% 15,00% 20,00% 25,00% 30,00% Other important elements 65

66 Gender Labels Set 3: What are other important elements for you? Total colour of the background colour of the font style of the font brand name colours used on the label illustration None Man Label 1 Count % Labels 2,7% 5,4% 24,3% 2,7% 27,0% 13,5% 24,3% 100,0% % Gender 33,3% 100,0% 69,2% 50,0% 71,4% 45,5% 64,3% 62,7% % Total 0,6% 1,1% 5,0% 0,6% 5,6% 2,8% 5,0% 20,7% Label 2 Count % Labels 6,7% 0,0% 13,3% 6,7% 13,3% 33,3% 26,7% 100,0% % Gender 33,3% 0,0% 15,4% 50,0% 14,3% 45,5% 28,6% 25,4% % Total 0,6% 0,0% 1,1% 0,6% 1,1% 2,8% 2,2% 8,4% Label 3 Count % Labels 14,3% 0,0% 28,6% 0,0% 28,6% 14,3% 14,3% 100,0% % Gender 33,3% 0,0% 15,4% 0,0% 14,3% 9,1% 7,1% 11,9% % Total 0,6% 0,0% 1,1% 0,0% 1,1% 0,6% 0,6% 3,9% Total Count % Labels 5,1% 3,4% 22,0% 3,4% 23,7% 18,6% 23,7% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 1,7% 1,1% 7,3% 1,1% 7,8% 6,2% 7,8% 33,0% Woman Label 1 Count % Labels 19,0% 8,6% 20,7% 10,3% 17,2% 12,1% 12,1% 100,0% % Gender 55,0% 62,5% 40,0% 50,0% 45,5% 50,0% 50,0% 48,3% % Total 6,2% 2,8% 6,7% 3,4% 5,6% 3,9% 3,9% 32,4% Label 2 Count % Labels 21,4% 7,1% 28,6% 3,6% 14,3% 17,9% 7,1% 100,0% % Gender 30,0% 25,0% 26,7% 8,3% 18,2% 35,7% 14,3% 23,3% % Total 3,4% 1,1% 4,5% 0,6% 2,2% 2,8% 1,1% 15,6% Label 3 Count % Labels 8,8% 2,9% 29,4% 14,7% 23,5% 5,9% 14,7% 100,0% % Gender 15,0% 12,5% 33,3% 41,7% 36,4% 14,3% 35,7% 28,3% % Total 1,7% 0,6% 5,6% 2,8% 4,5% 1,1% 2,8% 19,0% Total Count % Labels 16,6% 6,7% 25,0% 10,0% 18,3% 11,6% 11,6% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 11,2% 4,5% 16,8% 6,7% 12,3% 7,8% 7,8% 67,0% Total Label 1 Count % Labels 12,6% 7,4% 22,1% 7,4% 21,1% 12,6% 16,8% 100,0% % Gender 52,2% 70,0% 48,8% 50,0% 55,6% 48,0% 57,1% 53,1% % Total 6,7% 3,9% 11,7% 3,9% 11,2% 6,7% 8,9% 53,1% Label 2 Count % Labels 16,3% 4,7% 23,3% 4,7% 14,0% 23,3% 14,0% 100,0% % Gender 30,4% 20,0% 23,3% 14,3% 16,7% 40,0% 21,4% 24,0% % Total 3,9% 1,1% 5,6% 1,1% 3,4% 5,6% 3,4% 24,0% Label 3 Count

67 % Labels 9,8% 2,4% 29,3% 12,2% 24,4% 7,3% 14,6% 100,0% % Gender 17,4% 10,0% 27,9% 35,7% 27,8% 12,0% 21,4% 22,9% % Total 2,2% 0,6% 6,7% 2,8% 5,6% 1,7% 3,4% 22,9% Total Count % Labels 12,9% 5,6% 24,0% 7,8% 20,1% 14,0% 15,6% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 12,9% 5,6% 24,0% 7,8% 20,1% 14,0% 15,6% 100,0% Table 21: Gender and labels vs. other important elements set 3 Age Set 3: What other elements are important for you? Total colour of the background colour of the font style of the font brand name colours used on the label illustration None year Count % Age 14,1% 5,9% 24,7% 7,1% 23,5% 11,8% 12,9% 100,0% % Label 52,2% 50,0% 48,8% 42,9% 55,6% 40,0% 39,3% 47,5% % Total 6,7% 2,8% 11,7% 3,4% 11,2% 5,6% 6,2% 47,5% year Count % Age 13,5% 2,7% 29,7% 10,8% 13,5% 13,5% 16,2% 100,0% % Label 21,7% 10,0% 25,6% 28,6% 13,9% 20,0% 21,4% 20,7% % Total 2,8% 0,6% 6,2% 2,2% 2,8% 2,8% 3,4% 20,7% year Count % Age 16,7% 6,7% 20,0% 0,0% 26,7% 16,7% 13,3% 100,0% % Label 21,7% 20,0% 14,0% 0,0% 22,2% 20,0% 14,3% 16,8% % Total 2,8% 1,1% 3,4% 0,0% 4,5% 2,8% 2,2% 16,8% year Count % Age 4,8% 9,5% 19,0% 19,0% 9,5% 19,0% 19,0% 100,0% % Label 4,3% 20,0% 9,3% 28,6% 5,6% 16,0% 14,3% 11,7% % Total 0,6% 1,1% 2,2% 2,2% 1,1% 2,2% 2,2% 11,7% year Count % Age 0,0% 0,0% 20,0% 0,0% 20,0% 20,0% 40,0% 100,0% % Label 0,0% 0,0% 2,3% 0,0% 2,8% 4,0% 7,1% 2,8% % Total 0,0% 0,0% 0,6% 0,0% 0,6% 0,6% 1,1% 2,8% 70+ year Count % Age 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% 100,0% % Label 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 3,6% 0,6% % Total 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,6% 0,6% Total Count % Age 12,9% 5,6% 24,0% 7,8% 20,1% 14,0% 15,6% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 12,9% 5,6% 24,0% 7,8% 20,1% 14,0% 15,6% 100,0% Table 22: Age vs. other important elements set 3 67

68 SET 4 Gender Set 4: Which one of these labels would you choose? Total Label 1 Label 2 Label 3 Man Count % Gender 27,1% 20,8% 52,1% 100,0% % Label 35,1% 21,3% 48,1% 35,3% % Total 9,6% 7,4% 18,4% 35,3% Woman Count % Gender 27,3% 42,0% 30,7% 100,0% % Label 64,9% 78,7% 51,9% 64,7% % Total 17,6% 27,2% 19,9% 64,7% Total Count % Gender 27,2% 34,6% 38,2% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 27,2% 34,6% 38,2% 100,0% Table 23: Gender vs. labels set 4 Favourite label 38,2% 34,6% 27,2% Label 1 Label 2 Label 3 Age Set 4: Which one of these labels would you choose? Total Label 1 Label 2 Label year Count % Age 21,0% 35,5% 43,5% 100,0% % Label 35,1% 46,8% 51,9% 45,6% % Total 9,6% 16,2% 19,9% 45,6% year Count % Age 33,3% 30,0% 36,7% 100,0% % Label 27,0% 19,1% 21,2% 22,1% % Total 7,4% 6,6% 8,1% 22,1% year Count % Age 25,0% 50,0% 25,0% 100,0% % Label 16,2% 25,5% 11,5% 17,6% % Total 4,4% 8,8% 4,4% 17,6% year Count % Age 40,0% 26,7% 33,3% 100,0% % Label 16,2% 8,5% 9,6% 11,0% % Total 4,4% 2,9% 3,7% 11,0% year Count % Age 25,0% 0,0% 75,0% 100,0% % Label 2,7% 0,0% 5,8% 2,9% % Total 0,7% 0,0% 2,2% 2,9% 70+ year Count % Age 100,0% 0,0% 0,0% 100,0% % Label 2,7% 0,0% 0,0% 0,7% % Total 0,7% 0,0% 0,0% 0,7% Total Count % Age 27,2% 34,6% 38,2% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 27,2% 34,6% 38,2% 100,0% Table 24: Age vs labels set 4 Figure 9: Favourite label set 4 68

69 Table 25: Age vs. elements set 4 THESIS JESSICA KOOIJMAN, Age Set 4: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Other year Count % Age 29,0% 0,0% 17,7% 19,4% 6,5% 9,7% 12,9% 4,8% 100,0% % Label 54,5% 0,0% 44,0% 36,4% 44,4% 50,0% 44,4% 60,0% 45,6% % Total 13,2% 0,0% 8,1% 8,8% 2,9% 4,4% 5,9% 2,2% 45,6% year Count % Age 16,7% 3,3% 26,7% 23,3% 10,0% 10,0% 10,0% 0,0% 100,0% % Label 15,2% 100,0% 32,0% 21,2% 33,3% 25,0% 16,7% 0,0% 22,1% % Total 3,7% 0,7% 5,9% 5,1% 2,2% 2,2% 2,2% 0,0% 22,1% year Count % Age 20,8% 0,0% 12,5% 37,5% 4,2% 8,3% 8,3% 8,3% 100,0% % Label 15,2% 0,0% 12,0% 27,3% 11,1% 16,7% 11,1% 40,0% 17,6% % Total 3,7% 0,0% 2,2% 6,6% 0,7% 1,5% 1,5% 1,5% 17,6% year Count % Age 26,7% 0,0% 13,3% 26,7% 6,7% 6,7% 20,0% 0,0% 100,0% % Label 12,1% 0,0% 8,0% 12,1% 11,1% 8,3% 16,7% 0,0% 11,0% % Total 2,9% 0,0% 1,5% 2,9% 0,7% 0,7% 2,2% 0,0% 11,0% year Count % Age 0,0% 0,0% 25,0% 25,0% 0,0% 0,0% 50,0% 0,0% 100,0% % Label 0,0% 0,0% 4,0% 3,0% 0,0% 0,0% 11,1% 0,0% 2,9% % Total 0,0% 0,0% 0,7% 0,7% 0,0% 0,0% 1,5% 0,0% 2,9% 70+ year Count % Age 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 3,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% % Total 0,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% Total Count % Age 24,3% 0,7% 18,4% 24,3% 6,6% 8,8% 13,2% 3,7% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 24,3% 0,7% 18,4% 24,3% 6,6% 8,8% 13,2% 3,7% 100,0% Labels Set 4: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Other Label 1 Count % Label 21,6% 0,0% 21,6% 5,4% 5,4% 5,4% 35,1% 5,4% 100,0% % Element 24,2% 0,0% 32,0% 6,1% 22,2% 16,7% 72,2% 40,0% 27,2% % Total 5,9% 0,0% 5,9% 1,5% 1,5% 1,5% 9,6% 1,5% 27,2% Label 2 Count % Label 12,8% 0,0% 6,4% 57,4% 12,8% 8,5% 0,0% 2,1% 100,0% % Element 18,2% 0,0% 12,0% 81,8% 66,7% 33,3% 0,0% 20,0% 34,6% % Total 4,4% 0,0% 2,2% 19,9% 4,4% 2,9% 0,0% 0,7% 34,6% Label 3 Count % Label 36,5% 1,9% 26,9% 7,7% 1,9% 11,5% 9,6% 3,8% 100,0% 69

70 % Element 57,6% 100,0% 56,0% 12,1% 11,1% 50,0% 27,8% 40,0% 38,2% % Total 14,0% 0,7% 10,3% 2,9% 0,7% 4,4% 3,7% 1,5% 38,2% Total Count % Label 24,3% 0,7% 18,4% 24,3% 6,6% 8,8% 13,2% 3,7% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 24,3% 0,7% 18,4% 24,3% 6,6% 8,8% 13,2% 3,7% 100,0% Table 26: Labels vs. elements set 4 Gender Labels Set 4: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Other Man Label 1 Count % Label 7,7% 0,0% 23,1% 0,0% 7,7% 7,7% 53,8% 0,0% 100,0% % Element 20,0% 0,0% 30,0% 0,0% 25,0% 12,5% 77,8% 0,0% 27,1% % Gender 2,1% 0,0% 6,3% 0,0% 2,1% 2,1% 14,6% 0,0% 27,1% Label 2 Count % Label 0,0% 0,0% 0,0% 50,0% 30,0% 10,0% 0,0% 10,0% 100,0% % Element 0,0% 0,0% 0,0% 55,6% 75,0% 12,5% 0,0% 50,0% 20,8% % Gender 0,0% 0,0% 0,0% 10,4% 6,3% 2,1% 0,0% 2,1% 20,8% Label 3 Count % Label 16,0% 4,0% 28,0% 16,0% 0,0% 24,0% 8,0% 4,0% 100,0% % Element 80,0% 100,0% 70,0% 44,4% 0,0% 75,0% 22,2% 50,0% 52,1% % Gender 8,3% 2,1% 14,6% 8,3% 0,0% 12,5% 4,2% 2,1% 52,1% Total Count % Label 10,4% 2,1% 20,8% 18,8% 8,3% 16,7% 18,8% 4,2% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 10,4% 2,1% 20,8% 18,8% 8,3% 16,7% 18,8% 4,2% 100,0% Woman Label 1 Count % Label 29,2% 0,0% 20,8% 8,3% 4,2% 4,2% 25,0% 8,3% 100,0% % Element 25,0% 0,0% 33,3% 8,3% 20,0% 25,0% 66,7% 66,7% 27,3% % Gender 8,0% 0,0% 5,7% 2,3% 1,1% 1,1% 6,8% 2,3% 27,3% Label 2 Count % Label 16,2% 0,0% 8,1% 59,5% 8,1% 8,1% 0,0% 0,0% 100,0% % Element 21,4% 0,0% 20,0% 91,7% 60,0% 75,0% 0,0% 0,0% 42,0% % Gender 6,8% 0,0% 3,4% 25,0% 3,4% 3,4% 0,0% 0,0% 42,0% Label 3 Count % Label 55,6% 0,0% 25,9% 0,0% 3,7% 0,0% 11,1% 3,7% 100,0% % Element 53,6% 0,0% 46,7% 0,0% 20,0% 0,0% 33,3% 33,3% 30,7% % Gender 17,0% 0,0% 8,0% 0,0% 1,1% 0,0% 3,4% 1,1% 30,7% Total Count % Label 31,8% 0,0% 17,0% 27,3% 5,7% 4,5% 10,2% 3,4% 100,0% % Element 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 31,8% 0,0% 17,0% 27,3% 5,7% 4,5% 10,2% 3,4% 100,0% Total Label 1 Count

71 % Label 21,6% 0,0% 21,6% 5,4% 5,4% 5,4% 35,1% 5,4% 100,0% % Element 24,2% 0,0% 32,0% 6,1% 22,2% 16,7% 72,2% 40,0% 27,2% % Gender 5,9% 0,0% 5,9% 1,5% 1,5% 1,5% 9,6% 1,5% 27,2% Label 2 Count % Label 12,8% 0,0% 6,4% 57,4% 12,8% 8,5% 0,0% 2,1% 100,0% % Element 18,2% 0,0% 12,0% 81,8% 66,7% 33,3% 0,0% 20,0% 34,6% % Gender 4,4% 0,0% 2,2% 19,9% 4,4% 2,9% 0,0% 0,7% 34,6% Label 3 Count % Label 36,5% 1,9% 26,9% 7,7% 1,9% 11,5% 9,6% 3,8% 100,0% % Element 57,6% 100,0% 56,0% 12,1% 11,1% 50,0% 27,8% 40,0% 38,2% % Gender 14,0% 0,7% 10,3% 2,9% 0,7% 4,4% 3,7% 1,5% 38,2% Total Count % Label 24,3% 0,7% 18,4% 24,3% 6,6% 8,8% 13,2% 3,7% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 24,3% 0,7% 18,4% 24,3% 6,6% 8,8% 13,2% 3,7% 100,0% Table 27: Gender & labels vs. elements set 4 Other important elements None 19,7% illustration 7,5% colours used on the label 17,3% shape of the label 6,9% brand name 9,8% style of the font 20,2% colour of the font 5,2% colour of the background 13,3% 0,00% 5,00% 10,00% 15,00% 20,00% 25,00% Other important elements Figure 10: Other important elements set 4 71

72 Gender Labels Set 4: What are other important elements for you? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration None Man Label 1 Count % Labels 26,7% 0,0% 20,0% 6,7% 0,0% 13,3% 13,3% 20,0% 100,0% % Gender 57,1% 0,0% 42,9% 20,0% 0,0% 16,7% 40,0% 18,8% 27,3% % Total 2,3% 0,0% 1,7% 0,6% 0,0% 1,2% 1,2% 1,7% 8,7% Label 2 Count % Labels 10,0% 0,0% 0,0% 10,0% 20,0% 30,0% 0,0% 30,0% 100,0% % Gender 14,3% 0,0% 0,0% 20,0% 100,0% 25,0% 0,0% 18,8% 18,2% % Total 0,6% 0,0% 0,0% 0,6% 1,2% 1,7% 0,0% 1,7% 5,9% Label 3 Count % Labels 6,7% 3,3% 13,3% 10,0% 0,0% 23,3% 10,0% 33,3% 100,0% % Gender 28,6% 100,0% 57,1% 60,0% 0,0% 58,3% 60,0% 62,5% 54,6% % Total 1,2% 0,6% 2,3% 1,7% 0,0% 4,1% 1,7% 5,8% 17,3% Total Count % Labels 12,7% 1,8% 12,7% 9,1% 3,6% 21,8% 9,1% 29,1% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 4,1% 0,6% 4,1% 2,9% 1,2% 6,9% 2,9% 9,3% 31,8% Woman Label 1 Count % Labels 6,7% 3,3% 33,3% 13,3% 6,7% 13,3% 10,0% 13,3% 100,0% % Gender 12,5% 12,5% 35,7% 33,3% 20,0% 22,2% 37,5% 22,2% 25,4% % Total 1,2% 0,6% 5,8% 2,3% 1,2% 2,3% 1,7% 2,3% 17,3% Label 2 Count % Labels 16,4% 10,9% 12,7% 12,7% 12,7% 12,7% 1,8% 20,0% 100,0% % Gender 56,3% 75,0% 25,0% 58,3% 70,0% 38,9% 12,5% 61,1% 46,6% % Total 5,2% 3,5% 4,1% 4,1% 4,1% 4,1% 0,6% 6,4% 31,8% Label 3 Count % Labels 15,2% 3,0% 33,3% 3,0% 3,0% 21,2% 12,1% 9,1% 100,0% % Gender 31,3% 12,5% 39,3% 8,3% 10,0% 38,9% 50,0% 16,7% 28,0% % Total 2,9% 0,6% 6,4% 0,6% 0,6% 4,1% 2,3% 1,7% 19,1% Total Count % Labels 13,6% 6,8% 23,7% 10,2% 8,5% 15,3% 6,8% 15,3% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 9,3% 4,6% 16,2% 6,9% 5,8% 10,4% 4,6% 10,4% 68,2% Total Label 1 Count % Labels 13,3% 2,2% 28,9% 11,1% 4,4% 13,3% 11,1% 15,6% 100,0% % Gender 26,1% 11,1% 37,1% 29,4% 16,7% 20,0% 38,5% 20,6% 26,0% % Total 3,5% 0,6% 7,5% 2,9% 1,2% 3,5% 2,9% 4,1% 26,0% Label 2 Count % Labels 15,4% 9,2% 10,8% 12,3% 13,8% 15,4% 1,5% 21,5% 100,0% % Gender 43,5% 66,7% 20,0% 47,1% 75,0% 33,3% 7,7% 41,2% 37,6% % Total 5,8% 3,5% 4,1% 4,6% 5,2% 5,8% 0,6% 8,1% 37,6% Label 3 Count % Labels 11,1% 3,2% 23,8% 6,4% 1,6% 22,2% 11,1% 20,6% 100,0% 72

73 % Gender 30,4% 22,2% 42,9% 23,5% 8,3% 46,7% 53,8% 38,2% 36,4% % Total 4,1% 1,2% 23,8% 2,3% 0,6% 8,1% 4,1% 7,5% 36,4% Total Count % Labels 13,3% 5,2% 20,2% 9,8% 6,9% 17,3% 7,5% 19,7% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 13,3% 5,2% 20,2% 9,8% 6,9% 17,3% 7,5% 19,7% 100,0% Table 28: Gender and labels vs. other important elements set 4 Age Set 4: What other elements are important for you? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration None year Count % Age 10,7% 8,3% 23,8% 4,8% 7,1% 16,7% 9,5% 19,0% 100,0% % Label 39,1% 77,8% 57,1% 23,5% 50,0% 46,7% 61,5% 47,1% 48,6% % Total 5,2% 4,1% 11,6% 2,3% 3,5% 8,1% 4,6% 9,3% 48,6% year Count % Age 20,6% 2,9% 17,7% 17,7% 5,9% 8,8% 5,9% 20,6% 100,0% % Label 30,4% 11,1% 17,1% 35,3% 16,7% 10,0% 15,4% 20,6% 19,7% % Total 4,1% 0,6% 3,5% 3,5% 1,2% 1,7% 0,6% 3,5% 19,7% year Count % Age 13,8% 0,0% 13,8% 6,9% 10,3% 31,0% 3,5% 20,7% 100,0% % Label 17,4% 0,0% 11,4% 11,8% 25,0% 30,0% 7,7% 17,6% 16,8% % Total 2,3% 0,0% 2,3% 1,2% 1,7% 5,2% 0,6% 3,5% 16,8% year Count % Age 15,0% 5,0% 25,0% 15,0% 5,0% 10,0% 5,0% 20,0% 100,0% % Label 13,0% 11,1% 14,3% 17,6% 8,3% 6,7% 7,7% 11,8% 11,6% % Total 1,7% 0,6% 2,9% 1,7% 0,6% 1,2% 0,6% 2,3% 11,6% year Count % Age 0,0% 0,0% 0,0% 50,0% 0,0% 25,0% 25,0% 25,0% 100,0% % Label 0,0% 0,0% 0,0% 11,8% 0,0% 3,3% 7,7% 2,9% 2,9% % Total 0,0% 0,0% 0,0% 1,2% 0,0% 0,6% 0,6% 0,6% 2,9% 70+ year Count % Age 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% 0,0% 0,0% 100,0% % Label 0,0% 0,0% 0,0% 0,0% 0,0% 3,3% 0,0% 0,0% 0,6% % Total 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% 0,0% 0,0% 0,6% Total Count % Age 13,3% 5,2% 20,2% 9,8% 6,9% 17,3% 7,5% 19,7% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 13,3% 5,2% 20,2% 9,8% 6,9% 17,3% 7,5% 19,7% 100,0% Table 29: Age vs. other important elements set 4 73

74 SET 5 Gender Set 5: Which one of these labels would you choose? Total Label 1 Label 2 Label 3 Man Count % Gender 16,7% 52,1% 31,3% 100,0% % Label 25,8% 42,4% 32,6% 35,3% % Total 5,9% 18,4% 11,0% 35,3% Woman Count % Gender 26,1% 38,6% 35,2% 100,0% % Label 74,2% 57,6% 67,4% 64,7% % Total 16,9% 25,0% 22,8% 64,7% Total Count % Gender 22,8% 43,4% 33,8% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 22,8% 43,4% 33,8% 100,0% Table 30: Gender vs. labels set 5 Favourite label 33,8% 22,8% 43,4% Age Set 5: Which one of these labels would you choose? Total Label 1 Label 2 Label year Count % Age 14,5% 56,5% 29,0% 100,0% % Label 29,0% 59,3% 39,1% 45,6% % Total 6,6% 25,7% 13,2% 45,6% year Count % Age 16,7% 43,3% 40,0% 100,0% % Label 16,1% 22,0% 26,1% 22,1% % Total 3,7% 9,6% 8,8% 22,1% year Count % Age 37,5% 25,0% 37,5% 100,0% % Label 29,0% 10,2% 19,6% 17,6% % Total 6,6% 4,4% 6,6% 17,6% year Count % Age 40,0% 20,0% 40,0% 100,0% % Label 19,4% 5,1% 13,0% 11,0% % Total 4,4% 2,2% 4,4% 11,0% year Count % Age 25,0% 50,0% 25,0% 100,0% % Label 3,2% 3,4% 2,2% 2,9% % Total 0,7% 1,5% 0,7% 2,9% 70+ year Count % Age 100,0% 0,0% 0,0% 100,0% % Label 3,2% 0,0% 0,0% 0,7% % Total 0,7% 0,0% 0,0% 0,7% Total Count % Age 22,8% 43,4% 33,8% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 22,8% 43,4% 33,8% 100,0% Table 31: Age vs. labels set 5 Label 1 Label 2 Label 3 Figure 11: Favourite label set 5 74

75 Age Set 5: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Other year Count % Age 21,0% 0,0% 9,7% 3,2% 27,4% 16,1% 14,5% 8,1% 0,0% 100,0% % Label 43,3% 0,0% 30,0% 50,0% 68,0% 52,6% 47,4% 31,3% 0,0% 45,6% % Total 9,6% 0,0% 4,4% 1,5% 12,5% 7,4% 6,6% 3,7% 0,0% 45,6% year Count % Age 20,0% 0,0% 13,3% 0,0% 20,0% 10,0% 20,0% 16,7% 0,0% 100,0% % Label 20,0% 0,0% 20,0% 0,0% 24,0% 15,8% 31,6% 31,3% 0,0% 22,1% % Total 4,4% 0,0% 2,9% 0,0% 4,4% 2,2% 4,4% 3,7% 0,0% 22,1% year Count % Age 25,0% 0,0% 25,0% 0,0% 8,3% 16,7% 4,2% 12,5% 8,3% 100,0% % Label 20,0% 0,0% 30,0% 0,0% 8,0% 21,1% 5,3% 18,8% 66,7% 17,6% % Total 4,4% 0,0% 4,4% 0,0% 1,5% 2,9% 0,7% 2,2% 1,5% 17,6% year Count % Age 20,0% 0,0% 20,0% 13,3% 0,0% 6,7% 20,0% 13,3% 6,7% 100,0% % Label 10,0% 0,0% 15,0% 50,0% 0,0% 5,3% 15,8% 12,5% 33,3% 11,0% % Total 2,2% 0,0% 2,2% 1,5% 0,0% 0,7% 2,2% 1,5% 0,7% 11,0% year Count % Age 25,0% 0,0% 25,0% 0,0% 0,0% 25,0% 0,0% 25,0% 0,0% 100,0% % Label 3,3% 0,0% 5,0% 0,0% 0,0% 5,3% 0,0% 6,3% 0,0% 2,9% % Total 0,7% 0,0% 0,7% 0,0% 0,0% 0,7% 0,0% 0,7% 0,0% 2,9% 70+ year Count % Age 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 3,3% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% % Total 0,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% Total Count % Age 22,1% 0,0% 14,7% 2,9% 18,4% 14,0% 14,0% 11,8% 2,2% 100,0% % Label 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 22,1% 0,0% 14,7% 2,9% 18,4% 14,0% 14,0% 11,8% 2,2% 100,0% Table 32: Age vs. elements set 5 Labels Set 5: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Other Label 1 Count % Label 16,1% 0,0% 12,9% 3,2% 6,5% 29,0% 9,7% 16,1% 6,5% 100,0% % Element 16,7% 0,0% 20,0% 25,0% 8,0% 47,4% 15,8% 31,3% 66,7% 22,8% % Total 3,7% 0,0% 2,9% 0,7% 1,5% 6,6% 2,2% 3,7% 1,5% 22,8% Label 2 Count % Label 28,8% 0,0% 10,2% 1,7% 39,0% 13,6% 0,0% 6,8% 0,0% 100,0% % Element 56,7% 0,0% 30,0% 25,0% 92,0% 42,1% 0,0% 25,0% 0,0% 43,4% % Total 12,5% 0,0% 4,4% 0,7% 16,9% 5,9% 0,0% 2,9% 0,0% 43,4% Label 3 Count % Label 17,4% 0,0% 21,7% 4,3% 0,0% 4,3% 34,8% 15,2% 2,2% 100,0% % Element 26,7% 0,0% 50,0% 50,0% 0,0% 10,5% 84,2% 43,8% 33,3% 33,8% 75

76 % Total 5,9% 0,0% 7,4% 1,5% 0,0% 1,5% 11,8% 5,1% 0,7% 33,8% Total Count % Label 22,1% 0,0% 14,7% 2,9% 18,4% 14,0% 14,0% 11,8% 2,2% 100,0% % Element 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 22,1% 0,0% 14,7% 2,9% 18,4% 14,0% 14,0% 11,8% 2,2% 100,0% Table 33: Labels vs. elements set 5 Gender Labels Set 5: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Other Man Label 1 Count % Label 0,0% 0,0% 0,0% 12,5% 0,0% 50,0% 12,5% 25,0% 0,0% 100,0% % Element 0,0% 0,0% 0,0% 100,0% 0,0% 40,0% 25,0% 20,0% 0,0% 16,7% % Gender 0,0% 0,0% 0,0% 2,1% 0,0% 8,3% 2,1% 4,2% 0,0% 16,7% Label 2 Count % Label 28,0% 0,0% 8,0% 0,0% 32,0% 24,0% 0,0% 8,0% 0,0% 100,0% % Element 87,5% 0,0% 33,3% 0,0% 100,0% 60,0% 0,0% 20,0% 0,0% 52,1% % Gender 14,6% 0,0% 4,2% 0,0% 16,7% 12,5% 0,0% 4,2% 0,0% 52,1% Label 3 Count % Label 6,7% 0,0% 26,7% 0,0% 0,0% 0,0% 20,0% 40,0% 6,7% 100,0% % Element 12,5% 0,0% 66,7% 0,0% 0,0% 0,0% 75,0% 60,0% 100,0% 31,3% % Gender 2,1% 0,0% 8,3% 0,0% 0,0% 0,0% 6,3% 12,5% 2,1% 31,3% Total Count % Label 16,7% 0,0% 12,5% 2,1% 16,7% 20,8% 8,3% 20,8% 2,1% 100,0% % Element 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 16,7% 0,0% 12,5% 2,1% 16,7% 20,8% 8,3% 20,8% 2,1% 100,0% Woman Label 1 Count % Label 21,7% 0,0% 17,4% 0,0% 8,7% 21,7% 8,7% 13,0% 8,7% 100,0% % Element 22,7% 0,0% 28,6% 0,0% 11,8% 55,6% 13,3% 50,0% 100,0% 26,1% % Gender 5,7% 0,0% 4,5% 0,0% 2,3% 5,7% 2,3% 3,4% 2,3% 26,1% Label 2 Count % Label 29,4% 0,0% 11,8% 2,9% 44,1% 5,9% 0,0% 5,9% 0,0% 100,0% % Element 45,5% 0,0% 28,6% 33,3% 88,2% 22,2% 0,0% 33,3% 0,0% 38,6% % Gender 11,4% 0,0% 4,5% 1,1% 17,0% 2,3% 0,0% 2,3% 0,0% 38,6% Label 3 Count % Label 22,6% 0,0% 19,4% 6,5% 0,0% 6,5% 41,9% 3,2% 0,0% 100,0% % Element 31,8% 0,0% 42,9% 66,7% 0,0% 22,2% 86,7% 16,7% 0,0% 35,2% % Gender 8,0% 0,0% 6,8% 2,3% 0,0% 2,3% 14,8% 1,1% 0,0% 35,2% Total Count % Label 25,0% 0,0% 15,9% 3,4% 19,3% 10,2% 17,0% 6,8% 2,3% 100,0% % Element 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 25,0% 0,0% 15,9% 3,4% 19,3% 10,2% 17,0% 6,8% 2,3% 100,0% Total Label 1 Count % Label 16,1% 0,0% 12,9% 3,2% 6,5% 29,0% 9,7% 16,1% 6,5% 100,0% 76

77 % Element 16,7% 0,0% 20,0% 25,0% 8,0% 47,4% 15,8% 31,3% 66,7% 22,8% % Gender 3,7% 0,0% 2,9% 0,7% 1,5% 6,6% 2,2% 3,7% 1,5% 22,8% Label 2 Count % Label 28,8% 0,0% 10,2% 1,7% 39,0% 13,6% 0,0% 6,8% 0,0% 100,0% % Element 56,7% 0,0% 30,0% 25,0% 92,0% 42,1% 0,0% 25,0% 0,0% 43,4% % Gender 12,5% 0,0% 4,4% 0,7% 16,9% 5,9% 0,0% 2,9% 0,0% 43,4% Label 3 Count % Label 17,4% 0,0% 21,7% 4,3% 0,0% 4,3% 34,8% 15,2% 2,2% 100,0% % Element 26,7% 0,0% 50,0% 50,0% 0,0% 10,5% 84,2% 43,8% 33,3% 33,8% % Gender 5,9% 0,0% 7,4% 1,5% 0,0% 1,5% 11,8% 5,1% 0,7% 33,8% Total Count % Label 22,1% 0,0% 14,7% 2,9% 18,4% 14,0% 14,0% 11,8% 2,2% 100,0% % Element 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 22,1% 0,0% 14,7% 2,9% 18,4% 14,0% 14,0% 11,8% 2,2% 100,0% Table 34: Gender and labels vs. elements set 5 Other important elements None 21,0% Place of origin 7,5% illustration 9,7% colours used on the label 11,8% shape of the label 8,1% brand name 1,6% syle of the font 19,9% colour of the font 9,1% colour of the background 11,3% 0,00% 5,00% 10,00% 15,00% 20,00% 25,00% Other important elements Figure 12: Other important elements set 5 77

78 Gender Labels Set 5: What are other important elements for you? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin None Man Label 1 Count % Labels 0,0% 12,5% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 87,5% 100,0% % Gender 0,0% 33,3% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 31,8% 14,6% % Total 0,0% 0,5% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 3,8% 4,3% Label 2 Count % Labels 12,5% 6,3% 21,9% 0,0% 15,6% 9,4% 9,4% 3,1% 21,9% 100,0% % Gender 100,0% 66,7% 87,5% 0,0% 100,0% 75,0% 50,0% 33,3% 31,8% 58,2% % Total 2,2% 1,1% 3,8% 0,0% 2,7% 1,6% 1,6% 0,5% 3,8% 17,2% Label 3 Count % Labels 0,0% 0,0% 6,7% 0,0% 0,0% 6,7% 20,0% 13,3% 53,3% 100,0% % Gender 0,0% 0,0% 12,5% 0,0% 0,0% 25,0% 50,0% 66,7% 36,4% 27,3% % Total 0,0% 0,0% 0,5% 0,0% 0,0% 0,5% 1,6% 1,1% 4,3% 8,1% Total Count % Labels 7,3% 5,5% 14,6% 0,0% 9,1% 7,3% 10,9% 5,5% 40,0% 100,0% % Gender 100,0% 100,0% 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% 29,6% % Total 2,2% 1,6% 4,3% 0,0% 2,7% 2,2% 3,2% 1,6% 11,8% 29,6% Woman Label 1 Count % Labels 15,6% 9,4% 15,6% 3,1% 6,3% 12,5% 6,3% 15,6% 15,6% 100,0% % Gender 29,4% 21,4% 17,2% 33,3% 20,0% 22,2% 16,7% 45,5% 29,4% 24,4% % Total 2,7% 1,6% 2,7% 0,5% 1,1% 2,2% 1,1% 2,7% 2,7% 17,2% Label 2 Count % Labels 14,5% 12,7% 27,3% 3,6% 10,9% 1,4% 1,8% 3,6% 9,1% 100,0% % Gender 47,1% 50,0% 51,7% 66,7% 60,0% 50,0% 8,3% 18,2% 29,4% 42,0% % Total 4,3% 3,8% 8,1% 1,1% 3,2% 4,8% 0,5% 1,1% 2,7% 29,6% Label 3 Count % Labels 9,1% 9,1% 20,5% 0,0% 4,6% 11,4% 20,5% 9,1% 15,9% 100,0% % Gender 23,5% 28,6% 31,0% 0,0% 20,0% 27,8% 75,0% 36,4% 41,2% 33,6% % Total 2,2% 2,2% 4,8% 0,0% 1,1% 2,7% 4,8% 2,2% 3,8% 23,7% Total Count % Labels 13,0% 10,7% 22,1% 2,3% 7,6% 13,7% 9,2% 8,4% 13,0% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 70,4% % Total 9,1% 7,5% 15,6% 1,6% 5,4% 9,7% 6,5% 5,9% 9,1% 70,4% Total Label 1 Count % Labels 12,5% 10,0% 12,5% 2,5% 5,0% 10,0% 5,0% 12,5% 30,0% 100,0% % Gender 23,8% 23,5% 13,5% 33,3% 13,3% 18,2% 11,1% 35,7% 30,8% 21,5% % Total 2,7% 2,2% 2,7% 0,5% 1,1% 2,2% 1,1% 2,7% 6,5% 21,5% Label 2 Count % Labels 13,8% 10,4% 25,3% 2,3% 12,6% 13,8% 4,6% 3,4% 13,8% 100,0% % Gender 57,1% 52,9% 59,5% 66,7% 73,3% 54,5% 22,2% 21,4% 30,8% 46,8% % Total 6,5% 4,8% 11,8% 1,1% 5,9% 6,5% 2,2% 1,6% 6,5% 46,8% Label 3 Count

79 % Labels 6,8% 6,8% 17,0% 0,0% 3,4% 10,2% 20,3% 10,2% 25,4% 100,0% % Gender 19,0% 23,5% 27,0% 0,0% 13,3% 27,3% 66,7% 42,9% 38,5% 31,7% % Total 2,2% 2,2% 5,4% 0,0% 1,1% 3,2% 6,5% 3,2% 8,1% 31,7% Total Count % Labels 11,3% 9,1% 19,9% 1,6% 8,1% 11,8% 9,7% 7,5% 21,0% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 11,3% 9,1% 19,9% 1,6% 8,1% 11,8% 9,7% 7,5% 21,0% 100,0% Table 35: Gender and labels vs. other important elements set 5 Age Set 5: What other elements are important for you? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin None year Count % Age 12,5% 8,3% 20,8% 2,1% 11,5% 11,5% 7,3% 8,3% 17,7% 100,0% % Label 57,1% 47,1% 54,1% 66,7% 73,3% 50,0% 38,9% 57,1% 43,6% 51,6% % Total 6,5% 4,3% 10,8% 1,1% 5,9% 5,9% 3,8% 4,3% 9,1% 51,6% year Count % Age 11,1% 8,3% 25,0% 0,0% 0,0% 8,3% 5,6% 8,3% 33,3% 100,0% % Label 19,0% 17,6% 24,3% 0,0% 0,0% 13,6% 11,1% 21,4% 30,8% 19,4% % Total 2,2% 1,6% 4,8% 0,0% 0,0% 1,6% 1,1% 1,6% 6,5% 19,4% year Count % Age 13,8% 10,4% 17,2% 0,0% 10,4% 17,2% 10,4% 0,0% 20,7% 100,0% % Label 19,0% 17,6% 13,5% 0,0% 20,0% 22,7% 16,7% 0,0% 15,4% 15,6% % Total 2,2% 1,6% 2,7% 0,0% 1,6% 2,7% 1,6% 0,0% 3,2% 15,6% year Count % Age 5,0% 15,0% 15,0% 5,0% 0,0% 10,0% 25,0% 15,0% 10,0% 100,0% % Label 4,8% 17,6% 8,1% 33,3% 0,0% 9,1% 27,8% 21,4% 5,1% 10,8% % Total 0,5% 1,6% 1,6% 0,5% 0,0% 1,1% 2,7% 1,6% 1,1% 10,8% year Count % Age 0,0% 0,0% 0,0% 0,0% 25,0% 0,0% 25,0% 0,0% 50,0% 100,0% % Label 0,0% 0,0% 0,0% 0,0% 6,7% 0,0% 5,6% 0,0% 5,1% 2,2% % Total 0,0% 0,0% 0,0% 0,0% 0,5% 0,0% 0,5% 0,0% 1,1% 2,2% 70+ year Count % Age 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% 0,0% 0,0% 0,0% 100,0% % Label 0,0% 0,0% 0,0% 0,0% 0,0% 4,5% 0,0% 0,0% 0,0% 0,5% % Total 0,0% 0,0% 0,0% 0,0% 0,0% 0,5% 0,0% 0,0% 0,0% 0,5% Total Count % Age 11,3% 9,1% 19,9% 1,6% 8,1% 11,8% 9,7% 7,5% 21,0% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 11,3% 9,1% 19,9% 1,6% 8,1% 11,8% 9,7% 7,5% 21,0% 100,0% Table 36: age vs. other important elements set 5 79

80 SET 6 Gender Set 6: Which one of these labels would you choose? Total Label 1 Label 2 Label 3 Man Count % Gender 20,8% 10,4% 68,8% 100,0% % Label 26,3% 16,1% 49,3% 35,3% % Total 7,4% 3,7% 24,3% 35,3% Woman Count % Gender 31,8% 29,5% 38,6% 100,0% % Label 73,7% 83,9% 50,7% 64,7% % Total 20,6% 19,1% 25,0% 64,7% Total Count % Gender 27,9% 22,8% 49,3% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 27,9% 22,8% 49,3% 100,0% Table 37: Gender vs. labels set 6 49,3% Favourite label 27,9% Age Set 6: Which one of these labels would you choose? Total Label 1 Label 2 Label year Count % Age 32,3% 16,1% 51,6% 100,0% % Label 52,6% 32,3% 47,8% 45,6% % Total 14,7% 7,4% 23,5% 45,6% year Count % Age 30,0% 20,0% 50,0% 100,0% % Label 23,7% 19,4% 22,4% 22,1% % Total 6,6% 4,4% 11,0% 22,1% year Count % Age 20,8% 33,3% 45,8% 100,0% % Label 13,2% 25,8% 16,4% 17,6% % Total 3,7% 5,9% 8,1% 17,6% year Count % Age 20,0% 40,0% 40,0% 100,0% % Label 7,9% 19,4% 9,0% 11,0% % Total 2,2% 4,4% 4,4% 11,0% year Count % Age 25,0% 0,0% 75,0% 100,0% % Label 2,6% 0,0% 4,5% 2,9% % Total 0,7% 0,0% 2,2% 2,9% 70+ year Count % Age 0,0% 100,0% 0,0% 100,0% % Label 0,0% 3,2% 0,0% 0,7% % Total 0,0% 0,7% 0,0% 0,7% Total Count % Age 27,9% 22,8% 49,3% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 27,9% 22,8% 49,3% 100,0% Table 38: Age vs. labels set 6 22,8% Label 1 Label 2 Label 3 Figure 13: Favourite label set 6 80

81 Table 39: Age vs. elements set 6 THESIS JESSICA KOOIJMAN, Age Set 6: What attracted you the most in the chosen label? colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Other Total year Count % Age 3,2% 11,3% 4,8% 38,7% 29,0% 3,2% 8,1% 1,6% 100,0% % Label 33,3% 41,2% 50,0% 52,2% 46,2% 50,0% 38,5% 20,0% 45,6% % Total 1,5% 5,1% 2,2% 17,6% 13,2% 1,5% 3,7% 0,7% 45,6% year Count % Age 0,0% 16,7% 0,0% 36,7% 26,7% 3,3% 13,3% 3,3% 100,0% % Label 0,0% 29,4% 0,0% 23,9% 20,5% 25,0% 30,8% 20,0% 22,1% % Total 0,0% 3,7% 0,0% 8,1% 5,9% 0,7% 2,9% 0,7% 22,1% year Count % Age 8,3% 8,3% 8,3% 25,0% 29,2% 0,0% 8,3% 12,5% 100,0% % Label 33,3% 11,8% 33,3% 13,0% 17,9% 0,0% 15,4% 60,0% 17,6% % Total 1,5% 1,5% 1,5% 4,4% 5,1% 0,0% 1,5% 2,2% 17,6% year Count % Age 13,3% 6,7% 6,7% 13,3% 40,0% 6,7% 13,3% 0,0% 100,0% % Label 33,3% 5,9% 16,7% 4,3% 15,4% 25,0% 15,4% 0,0% 11,0% % Total 1,5% 0,7% 0,7% 1,5% 4,4% 0,7% 1,5% 0,0% 11,0% year Count % Age 0,0% 25,0% 0,0% 75,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 0,0% 5,9% 0,0% 6,5% 0,0% 0,0% 0,0% 0,0% 2,9% % Total 0,0% 0,7% 0,0% 2,2% 0,0% 0,0% 0,0% 0,0% 2,9% 70+ year Count % Age 0,0% 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 0,0% 5,9% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% % Total 0,0% 0,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% Total Count % Age 4,4% 12,5% 4,4% 33,8% 28,7% 2,9% 9,6% 3,7% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 4,4% 12,5% 4,4% 33,8% 28,7% 2,9% 9,6% 3,7% 100,0% Labels Set 6: What attracted you the most in the chosen label? colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Other Total Label 1 Count % Label 10,5% 10,5% 2,6% 31,6% 23,7% 2,6% 13,2% 5,3% 100,0% % Element 66,7% 23,5% 16,7% 26,1% 23,1% 25,0% 38,5% 40,0% 27,9% % Total 2,9% 2,9% 0,7% 8,8% 6,6% 0,7% 3,7% 1,5% 27,9% Label 2 Count % Label 3,2% 9,7% 12,9% 32,3% 29,0% 0,0% 9,7% 3,2% 100,0% % Element 16,7% 17,6% 66,7% 21,7% 23,1% 0,0% 23,1% 20,0% 22,8% % Total 0,7% 2,2% 2,9% 7,4% 6,6% 0,0% 2,2% 0,7% 22,8% Label 3 Count % Label 1,5% 14,9% 1,5% 35,8% 31,3% 4,5% 7,5% 3,0% 100,0% 81

82 % Element 16,7% 58,8% 16,7% 52,2% 53,8% 75,0% 38,5% 40,0% 49,3% % Total 0,7% 7,4% 0,7% 17,6% 15,4% 2,2% 3,7% 1,5% 49,3% Total Count % Label 4,4% 12,5% 4,4% 33,8% 28,7% 2,9% 9,6% 3,7% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 4,4% 12,5% 4,4% 33,8% 28,7% 2,9% 9,6% 3,7% 100,0% Table 40: Labels vs. elements set 6 Gender Labels Set 6: What attracted you the most in the chosen label? Total colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Other Man Label 1 Count % Label 0,0% 10,0% 0,0% 40,0% 20,0% 0,0% 20,0% 10,0% 100,0% % Element 0,0% 12,5% 0,0% 22,2% 20,0% 0,0% 28,6% 33,3% 20,8% % Gender 0,0% 2,1% 0,0% 8,3% 4,2% 0,0% 4,2% 2,1% 20,8% Label 2 Count % Label 0,0% 20,0% 20,0% 20,0% 0,0% 0,0% 40,0% 0,0% 100,0% % Element 0,0% 12,5% 100,0% 5,6% 0,0% 0,0% 28,6% 0,0% 10,4% % Gender 0,0% 2,1% 2,1% 2,1% 0,0% 0,0% 4,2% 0,0% 10,4% Label 3 Count % Label 0,0% 18,2% 0,0% 39,4% 24,2% 3,0% 9,1% 6,1% 100,0% % Element 0,0% 75,0% 0,0% 72,2% 80,0% 100,0% 42,9% 66,7% 68,8% % Gender 0,0% 12,5% 0,0% 27,1% 16,7% 2,1% 6,3% 4,2% 68,8% Total Count % Label 0,0% 16,7% 2,1% 37,5% 20,8% 2,1% 14,6% 6,3% 100,0% % Element 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 0,0% 16,7% 2,1% 37,5% 20,8% 2,1% 14,6% 6,3% 100,0% Woman Label 1 Count % Label 14,3% 10,7% 3,6% 28,6% 25,0% 3,6% 10,7% 3,6% 100,0% % Element 66,7% 33,3% 20,0% 28,6% 24,1% 33,3% 50,0% 50,0% 31,8% % Gender 4,5% 3,4% 1,1% 9,1% 8,0% 1,1% 3,4% 1,1% 31,8% Label 2 Count % Label 3,8% 7,7% 11,5% 34,6% 34,6% 0,0% 3,8% 3,8% 100,0% % Element 16,7% 22,2% 60,0% 32,1% 31,0% 0,0% 16,7% 50,0% 29,5% % Gender 1,1% 2,3% 3,4% 10,2% 10,2% 0,0% 1,1% 1,1% 29,5% Label 3 Count % Label 2,9% 11,8% 2,9% 32,4% 38,2% 5,9% 5,9% 0,0% 100,0% % Element 16,7% 44,4% 20,0% 39,3% 44,8% 66,7% 33,3% 0,0% 38,6% % Gender 1,1% 4,5% 1,1% 12,5% 14,8% 2,3% 2,3% 0,0% 38,6% Total Count % Label 6,8% 10,2% 5,7% 31,8% 33,0% 3,4% 6,8% 2,3% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 6,8% 10,2% 5,7% 31,8% 33,0% 3,4% 6,8% 2,3% 100,0% Total Label 1 Count % Label 10,5% 10,5% 2,6% 31,6% 23,7% 2,6% 13,2% 5,3% 100,0% 82

83 % Element 66,7% 23,5% 16,7% 26,1% 23,1% 25,0% 38,5% 40,0% 27,9% % Gender 2,9% 2,9% 0,7% 8,8% 6,6% 0,7% 3,7% 1,5% 27,9% Label 2 Count % Label 3,2% 9,7% 12,9% 32,3% 29,0% 0,0% 9,7% 3,2% 100,0% % Element 16,7% 17,6% 66,7% 21,7% 23,1% 0,0% 23,1% 20,0% 22,8% % Gender 0,7% 2,2% 2,9% 7,4% 6,6% 0,0% 2,2% 0,7% 22,8% Label 3 Count % Label 1,5% 14,9% 1,5% 35,8% 31,3% 4,5% 7,5% 3,0% 100,0% % Element 16,7% 58,8% 16,7% 52,2% 53,8% 75,0% 38,5% 40,0% 49,3% % Gender 0,7% 7,4% 0,7% 17,6% 15,4% 2,2% 3,7% 1,5% 49,3% Total Count % Label 4,4% 12,5% 4,4% 33,8% 28,7% 2,9% 9,6% 3,7% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 4,4% 12,5% 4,4% 33,8% 28,7% 2,9% 9,6% 3,7% 100,0% Table 41: Gender and labels vs elements set 6 Other important elements None 30,1% place of origin illustration 4,9% 4,9% colours used on the label 18,4% shape of the label 12,9% brand name 3,7% style of the font 20,2% colour of the font 4,9% Figure 14: Other important elements set 6 0,00% 5,00% 10,00% 15,00% 20,00% 25,00% 30,00% 35,00% Other important elements 83

84 Gender Labels Set 6: What other elements are important for you? Total colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin None Man Label 1 Count % Labels 0,0% 0,0% 0,0% 9,1% 27,3% 18,2% 0,0% 45,5% 100,0% % Gender 0,0% 0,0% 0,0% 20,0% 33,3% 100,0% 0,0% 20,0% 11,5% % Total 0,0% 0,0% 0,0% 0,6% 1,8% 1,2% 0,0% 3,1% 6,8% Label 2 Count % Labels 0,0% 0,0% 16,7% 16,7% 16,7% 0,0% 16,7% 33,3% 100,0% % Gender 0,0% 0,0% 50,0% 20,0% 11,1% 0,0% 50,0% 8,0% 11,5% % Total 0,0% 0,0% 0,6% 0,6% 0,6% 0,0% 0,6% 1,2% 3,6% Label 3 Count % Labels 2,9% 17,1% 2,9% 8,6% 14,3% 0,0% 2,9% 5,1% 100,0% % Gender 100,0% 100,0% 50,0% 60,0% 55,6% 0,0% 50,0% 72,0% 67,3% % Total 0,6% 3,6% 0,6% 1,8% 3,1% 0,0% 0,6% 11,0% 21,5% Total Count % Labels 1,9% 11,5% 3,8% 9,6% 17,3% 3,8% 3,8% 48,1% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 0,6% 3,6% 1,2% 3,1% 5,5% 1,2% 1,2% 15,3% 31,9% Woman Label 1 Count % Labels 9,5% 26,2% 7,1% 11,9% 16,7% 7,1% 4,8% 16,7% 100,0% % Gender 57,1% 40,7% 75,0% 31,3% 33,3% 50,0% 33,3% 29,2% 37,8% % Total 4,5% 6,8% 1,8% 3,1% 4,3% 1,8% 1,2% 4,3% 25,8% Label 2 Count % Labels 7,4% 25,9% 3,7% 11,1% 11,1% 7,4% 7,4% 25,9% 100,0% % Gender 28,6% 25,9% 25,0% 18,8% 14,3% 33,3% 33,3% 29,2% 24,3% % Total 1,2% 4,3% 0,6% 1,8% 1,8% 1,2% 1,2% 4,3% 16,6% Label 3 Count % Labels 2,4% 21,4% 0,0% 19,1% 26,2% 2,4% 4,8% 23,8% 100,0% % Gender 14,3% 33,3% 0,0% 50,0% 52,4% 16,7% 33,3% 41,7% 37,8% % Total 0,6% 5,5% 0,0% 4,9% 6,8% 0,6% 1,2% 6,1% 25,8% Total Count % Labels 6,3% 24,3% 3,6% 14,4% 18,9% 5,4% 5,4% 21,6% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 4,3% 16,6% 2,5% 9,8% 12,9% 3,7% 3,7% 14,7% 68,1% Total Label 1 Count % Labels 7,5% 20,7% 5,7% 11,3% 18,9% 9,4% 3,7% 22,6% 100,0% % Gender 50,0% 33,3% 50,0% 28,6% 33,3% 62,5% 25,0% 24,5% 32,5% % Total 2,5% 6,8% 1,8% 3,7% 6,1% 3,1% 1,2% 7,4% 32,5% Label 2 Count % Labels 6,1% 21,2% 6,1% 12,1% 12,1% 6,1% 9,1% 27,3% 100,0% % Gender 25,0% 21,2% 33,3% 19,0% 13,3% 25,0% 37,5% 18,4% 20,3% % Total 1,2% 4,3% 1,2% 2,5% 2,5% 1,2% 1,8% 5,5% 20,3% Label 3 Count % Labels 2,6% 19,5% 1,3% 14,3% 20,8% 1,3% 3,9% 36,4% 100,0% 84

85 % Gender 25,0% 45,5% 16,7% 52,4% 53,3% 12,5% 37,5% 57,1% 47,2% % Total 1,2% 9,2% 0,6% 6,8% 9,8% 0,6% 1,8% 17,2% 47,2% Total Count % Labels 4,9% 20,3% 3,7% 12,9% 18,4% 4,9% 4,9% 30,1% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 4,9% 20,3% 3,7% 12,9% 18,4% 4,9% 4,9% 30,1% 100,0% Table 42: Gender and labels vs. other important elements set 6 Age Set 6: What other elements are important for you? Total colour of the font style of brand shape of colours used on the Place of the font name the label label illustration origin None year Count % Age 7,5% 20,0% 5,0% 13,8% 23,8% 3,8% 6,3% 20,0% 100,0% % Label 75,0% 48,5% 66,7% 52,4% 63,3% 37,5% 62,5% 32,7% 49,1% % Total 3,7% 9,8% 2,5% 6,8% 11,7% 1,8% 3,1% 9,8% 49,1% year Count % Age 0,0% 18,7% 3,1% 6,2% 12,5% 9,4% 0,0% 50,0% 100,0% % Label 0,0% 18,2% 16,7% 9,5% 13,3% 37,5% 0,0% 32,7% 19,6% % Total 0,0% 3,7% 0,6% 1,2% 2,5% 1,8% 0,0% 9,8% 19,6% year Count % Age 0,0% 22,2% 0,0% 18,5% 22,2% 3,7% 0,0% 33,3% 100,0% % Label 0,0% 18,2% 0,0% 23,8% 20,0% 12,5% 0,0% 18,4% 16,6% % Total 0,0% 3,7% 0,0% 3,1% 3,7% 0,6% 0,0% 5,5% 16,6% year Count % Age 4,4% 21,7% 4,4% 13,1% 0,0% 4,4% 13,1% 21,7% 100,0% % Label 12,5% 15,2% 16,7% 14,3% 0,0% 12,5% 37,5% 10,2% 14,1% % Total 0,6% 3,1% 0,6% 1,8% 0,0% 0,6% 1,8% 3,1% 14,1% year Count % Age 0,0% 0,0% 0,0% 0,0% 25,0% 0,0% 0,0% 75,0% 100,0% % Label 0,0% 0,0% 0,0% 0,0% 3,3% 0,0% 0,0% 6,1% 2,5% % Total 0,0% 0,0% 0,0% 0,0% 0,6% 0,0% 0,0% 1,8% 2,5% 70+ year Count % Age 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 12,5% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,6% % Total 0,6% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,6% Total Count % Age 4,9% 20,3% 3,7% 12,9% 18,4% 4,9% 4,9% 30,1% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 4,9% 20,3% 3,7% 12,9% 18,4% 4,9% 4,9% 30,1% 100,0% Table 43: age vs. other important elements set 6 85

86 SET 7 Gender Set 7: Which one of these labels would you choose? Total Label 1 Label 2 Label 3 Man Count % Gender 6,3% 66,7% 27,1% 100,0% % Label 8,3% 43,2% 50,0% 35,3% % Total 2,2% 23,5% 9,6% 35,3% Woman Count % Gender 37,5% 47,7% 14,8% 100,0% % Label 91,7% 56,8% 50,0% 64,7% % Total 24,3% 30,9% 9,6% 64,7% Total Count % Gender 26,5% 54,4% 19,1% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 26,5% 54,4% 19,1% 100,0% Table 44: Gender vs. labels set 7 Favourite label 19,1% 54,4% 26,5% Age Set 7: Which one of these labels would you choose? Total Label 1 Label 2 Label year Count % Age 30,6% 53,2% 16,1% 100,0% % Label 52,8% 44,6% 38,5% 45,6% % Total 14,0% 24,3% 7,4% 45,6% year Count % Age 10,0% 70,0% 20,0% 100,0% % Label 8,3% 28,4% 23,1% 22,1% % Total 2,2% 15,4% 4,4% 22,1% year Count % Age 33,3% 37,5% 29,2% 100,0% % Label 22,2% 12,2% 26,9% 17,6% % Total 5,9% 6,6% 5,1% 17,6% year Count % Age 40,0% 46,7% 13,3% 100,0% % Label 16,7% 9,5% 7,7% 11,0% % Total 4,4% 5,1% 1,5% 11,0% year Count % Age 0,0% 100,0% 0,0% 100,0% % Label 0,0% 5,4% 0,0% 2,9% % Total 0,0% 2,9% 0,0% 2,9% 70+ year Count % Age 0,0% 0,0% 100,0% 100,0% % Label 0,0% 0,0% 3,8% 0,7% % Total 0,0% 0,0% 0,7% 0,7% Total Count % Age 26,5% 54,4% 19,1% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 26,5% 54,4% 19,1% 100,0% Table 45: Age vs. labels set 7 Label 1 Label 2 Label 3 Figure 15: Favourite label set 7 86

87 Age Set 7: What attracted you the most in the chosen label? Total colour of colour of the font style of brand shape of colours used on the Place of the background the font name the label label illustration origin Other year Count % Age 29,0% 6,5% 17,7% 17,7% 1,6% 12,9% 3,2% 8,1% 3,2% 100,0% % Label 40,9% 66,7% 50,0% 61,1% 33,3% 44,4% 25,0% 55,6% 25,0% 45,6% % Total 13,2% 2,9% 8,1% 8,1% 0,7% 5,9% 1,5% 3,7% 1,5% 45,6% year Count % Age 36,7% 3,3% 13,3% 6,7% 0,0% 16,7% 6,7% 10,0% 6,7% 100,0% % Label 25,0% 16,7% 18,2% 11,1% 0,0% 27,8% 25,0% 33,3% 25,0% 22,1% % Total 8,1% 0,7% 2,9% 1,5% 0,0% 3,7% 1,5% 2,2% 1,5% 22,1% year Count % Age 33,3% 0,0% 29,2% 12,5% 4,2% 8,3% 4,2% 0,0% 8,3% 100,0% % Label 18,2% 0,0% 31,8% 16,7% 33,3% 11,1% 12,5% 0,0% 25,0% 17,6% % Total 5,9% 0,0% 5,1% 2,2% 0,7% 1,5% 0,7% 0,0% 1,5% 17,6% year Count % Age 26,7% 0,0% 0,0% 13,3% 6,7% 20,0% 20,0% 6,7% 6,7% 100,0% % Label 9,1% 0,0% 0,0% 11,1% 33,3% 16,7% 37,5% 11,1% 12,5% 11,0% % Total 2,9% 0,0% 0,0% 1,5% 0,7% 2,2% 2,2% 0,7% 0,7% 11,0% year Count % Age 75,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 25,0% 100,0% % Label 6,8% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 12,5% 2,9% % Total 2,2% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% 2,9% 70+ year Count % Age 0,0% 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 0,0% 16,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% % Total 0,0% 0,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% Total Count % Age 32,4% 4,4% 16,2% 13,2% 2,2% 13,2% 5,9% 6,6% 5,9% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 32,4% 4,4% 16,2% 13,2% 2,2% 13,2% 5,9% 6,6% 5,9% 100,0% Table 46: Age vs. elements set 7 Labels Set 7: What attracted you the most in the chosen label? Total colour of colour of the font style of brand shape of colours used on the Place of the background the font name the label label illustration origin Other Label 1 Count % Label 22,2% 0,0% 25,0% 27,8% 8,3% 5,6% 8,3% 0,0% 2,8% 100,0% % Element 18,2% 0,0% 40,9% 55,6% 100,0% 11,1% 37,5% 0,0% 12,5% 26,5% % Total 5,9% 0,0% 6,6% 7,4% 2,2% 1,5% 2,2% 0,0% 0,7% 26,5% Label 2 Count % Label 45,9% 6,8% 9,5% 6,8% 0,0% 16,2% 4,1% 2,7% 8,1% 100,0% % Element 77,3% 83,3% 31,8% 27,8% 0,0% 66,7% 37,5% 22,2% 75,0% 54,4% % Total 25,0% 3,7% 5,1% 3,7% 0,0% 8,8% 2,2% 1,5% 4,4% 54,4% Label 3 Count

88 % Label 7,7% 3,8% 23,1% 11,5% 0,0% 15,4% 7,7% 26,9% 3,8% 100,0% % Element 4,5% 16,7% 27,3% 16,7% 0,0% 22,2% 25,0% 77,8% 12,5% 19,1% % Total 1,5% 0,7% 4,4% 2,2% 0,0% 2,9% 1,5% 5,1% 0,7% 19,1% Total Count % Label 32,4% 4,4% 16,2% 13,2% 2,2% 13,2% 5,9% 6,6% 5,9% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 32,4% 4,4% 16,2% 13,2% 2,2% 13,2% 5,9% 6,6% 5,9% 100,0% Table 47: Labels vs. elements set 7 Gender Labels Set 7: What attracted you the most in the chosen label? Total colour of the colour of the font style of brand shape of colours used on the Place of background the font name the label label illustration origin Other Man Label 1 Count % Label 0,0% 0,0% 0,0% 66,7% 0,0% 33,3% 0,0% 0,0% 0,0% 100,0% % Element 0,0% 0,0% 0,0% 40,0% 0,0% 11,1% 0,0% 0,0% 0,0% 6,3% % Gender 0,0% 0,0% 0,0% 4,2% 0,0% 2,1% 0,0% 0,0% 0,0% 6,3% Label 2 Count % Label 37,5% 6,3% 12,5% 6,3% 0,0% 15,6% 6,3% 3,1% 12,5% 100,0% % Element 92,3% 100,0% 57,1% 40,0% 0,0% 55,6% 100,0% 16,7% 100,0% 66,7% % Gender 25,0% 4,2% 8,3% 4,2% 0,0% 10,4% 4,2% 2,1% 8,3% 66,7% Label 3 Count % Label 7,7% 0,0% 23,1% 7,7% 0,0% 23,1% 0,0% 38,5% 0,0% 100,0% % Element 7,7% 0,0% 42,9% 20,0% 0,0% 33,3% 0,0% 83,3% 0,0% 27,1% % Gender 2,1% 0,0% 6,3% 2,1% 0,0% 6,3% 0,0% 10,4% 0,0% 27,1% Total Count % Label 27,1% 4,2% 14,6% 10,4% 0,0% 18,8% 4,2% 12,5% 8,3% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 27,1% 4,2% 14,6% 10,4% 0,0% 18,8% 4,2% 12,5% 8,3% 100,0% Woman Label 1 Count % Label 24,2% 0,0% 27,3% 24,2% 9,1% 3,0% 9,1% 0,0% 3,0% 100,0% % Element 25,8% 0,0% 60,0% 61,5% 100,0% 11,1% 50,0% 0,0% 25,0% 37,5% % Gender 9,1% 0,0% 10,2% 9,1% 3,4% 1,1% 3,4% 0,0% 1,1% 37,5% Label 2 Count % Label 52,4% 7,1% 7,1% 7,1% 0,0% 16,7% 2,4% 2,4% 4,8% 100,0% % Element 71,0% 75,0% 20,0% 23,1% 0,0% 77,8% 16,7% 33,3% 50,0% 47,7% % Gender 25,0% 3,4% 3,4% 3,4% 0,0% 8,0% 1,1% 1,1% 2,3% 47,7% Label 3 Count % Label 7,7% 7,7% 23,1% 15,4% 0,0% 7,7% 15,4% 15,4% 7,7% 100,0% % Element 3,2% 25,0% 20,0% 15,4% 0,0% 11,1% 33,3% 66,7% 25,0% 14,8% % Gender 1,1% 1,1% 3,4% 2,3% 0,0% 1,1% 2,3% 2,3% 1,1% 14,8% Total Count % Label 35,2% 4,5% 17,0% 14,8% 3,4% 10,2% 6,8% 3,4% 4,5% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 35,2% 4,5% 17,0% 14,8% 3,4% 10,2% 6,8% 3,4% 4,5% 100,0% 88

89 Total Label 1 Count % Label 22,2% 0,0% 25,0% 27,8% 8,3% 5,6% 8,3% 0,0% 2,8% 100,0% % Element 18,2% 0,0% 40,9% 55,6% 100,0% 11,1% 37,5% 0,0% 12,5% 26,5% % Gender 5,9% 0,0% 6,6% 7,4% 2,2% 1,5% 2,2% 0,0% 0,7% 26,5% Label 2 Count % Label 45,9% 6,8% 9,5% 6,8% 0,0% 16,2% 4,1% 2,7% 8,1% 100,0% % Element 77,3% 83,3% 31,8% 27,8% 0,0% 66,7% 37,5% 22,2% 75,0% 54,4% % Gender 25,0% 3,7% 5,1% 3,7% 0,0% 8,8% 2,2% 1,5% 4,4% 54,4% Label 3 Count % Label 7,7% 3,8% 23,1% 11,5% 0,0% 15,4% 7,7% 26,9% 3,8% 100,0% % Element 4,5% 16,7% 27,3% 16,7% 0,0% 22,2% 25,0% 77,8% 12,5% 19,1% % Gender 1,5% 0,7% 4,4% 2,2% 0,0% 2,9% 1,5% 5,1% 0,7% 19,1% Total Count % Label 32,4% 4,4% 16,2% 13,2% 2,2% 13,2% 5,9% 6,6% 5,9% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 32,4% 4,4% 16,2% 13,2% 2,2% 13,2% 5,9% 6,6% 5,9% 100,0% Table 48: Gender and labels vs elements set 7 Other important elements None 12,7% place of origin 4,1% illustration 9,6% colours used on the label 13,2% shape of the label 3,6% brand name 7,1% style of the font 24,4% colour of the font 14,2% colour of the background 11,2% 0,00% 5,00% 10,00% 15,00% 20,00% 25,00% 30,00% Other important elements Figure 16: Other important elements set 7 89

90 Gender Labels Set 7: What other elements are important for you? Total colour of the colour of the font style brand shape colours used on the Place of background of the font name of the label label illustration origin None Man Label 1 Count % Labels 0,0% 0,0% 33,3% 0,0% 0,0% 0,0% 0,0% 0,0% 66,7% 100,0% % Gender 0,0% 0,0% 7,7% 0,0% 0,0% 0,0% 0,0% 0,0% 13,3% 4,3% % Total 0,0% 0,0% 0,5% 0,0% 0,0% 0,0% 0,0% 0,0% 1,0% 1,5% Label 2 Count % Labels 5,9% 15,7% 19,6% 5,9% 2,0% 19,6% 13,7% 3,9% 13,7% 100,0% % Gender 50,0% 88,9% 76,9% 75,0% 100,0% 100,0% 87,5% 50,0% 46,7% 72,9% % Total 1,5% 4,1% 5,1% 1,5% 0,5% 5,1% 3,6% 1,0% 3,6% 25,9% Label 3 Count % Labels 18,8% 6,3% 12,5% 6,3% 0,0% 0,0% 6,3% 12,5% 37,5% 100,0% % Gender 50,0% 11,1% 15,4% 25,0% 0,0% 0,0% 12,5% 50,0% 40,0% 22,9% % Total 1,5% 0,5% 1,0% 0,5% 0,0% 0,0% 0,5% 1,0% 3,1% 8,1% Total Count % Labels 8,6% 12,9% 18,6% 5,7% 1,4% 14,3% 11,4% 5,7% 21,4% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 3,1% 4,7% 6,7% 2,0% 0,5% 5,1% 4,1% 2,0% 7,6% 35,5% Woman Label 1 Count % Labels 19,2% 13,5% 28,9% 7,7% 5,8% 11,5% 7,7% 3,9% 1,9% 100,0% % Gender 62,5% 36,8% 42,9% 40,0% 50,0% 37,5% 36,4% 50,0% 10,0% 41,0% % Total 5,1% 3,6% 7,6% 2,0% 1,5% 3,1% 2,0% 1,0% 0,5% 26,4% Label 2 Count % Labels 6,8% 18,6% 28,8% 6,8% 5,1% 11,9% 10,2% 1,7% 10,2% 100,0% % Gender 25,0% 57,9% 48,6% 40,0% 50,0% 43,8% 54,5% 25,0% 60,0% 46,5% % Total 2,0% 5,6% 8,6% 2,0% 1,5% 3,6% 3,1% 0,5% 3,1% 30,0% Label 3 Count % Labels 12,5% 6,3% 18,8% 12,5% 0,0% 18,8% 6,3% 6,3% 18,8% 100,0% % Gender 12,5% 5,3% 8,6% 20,0% 0,0% 18,8% 9,1% 25,0% 30,0% 12,6% % Total 1,0% 0,5% 1,5% 1,0% 0,0% 1,5% 0,5% 0,5% 1,5% 8,1% Total Count % Labels 12,6% 15,0% 27,6% 7,9% 4,7% 12,6% 8,7% 3,2% 7,9% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 8,1% 9,7% 17,8% 5,1% 3,1% 8,1% 5,6% 2,0% 5,1% 64,5% Total Label 1 Count % Labels 18,2% 12,7% 15,6% 7,3% 5,5% 10,9% 7,3% 3,6% 5,5% 100,0% % Gender 45,5% 25,0% 33,3% 28,6% 42,9% 23,1% 21,1% 25,0% 12,0% 27,9% % Total 5,1% 3,6% 8,1% 2,0% 1,5% 3,1% 2,0% 1,0% 1,5% 27,9% Label 2 Count % Labels 6,4% 17,3% 24,6% 6,4% 3,6% 15,5% 11,8% 2,7% 11,8% 100,0% % Gender 31,8% 67,9% 56,3% 50,0% 57,1% 65,4% 68,4% 37,5% 52,0% 55,8% % Total 3,6% 9,7% 13,7% 3,6% 2,0% 8,6% 6,6% 1,5% 6,6% 55,8% Label 3 Count

91 % Labels 15,6% 6,3% 15,6% 9,4% 0,0% 9,4% 6,3% 9,4% 28,1% 100,0% % Gender 22,7% 7,1% 10,4% 21,4% 0,0% 11,5% 10,5% 37,5% 36,0% 16,2% % Total 2,5% 1,0% 2,5% 1,5% 0,0% 1,5% 1,0% 1,5% 4,7% 16,2% Total Count % Labels 11,2% 14,2% 24,4% 7,1% 3,6% 13,2% 9,7% 4,1% 12,7% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 11,2% 14,2% 24,4% 7,1% 3,6% 13,2% 9,7% 4,1% 12,7% 100,0% Table 49: Gender and labels vs. other important elements set 7 Age Set 7: What other elements are important for you? Total colour of colour of the font style of brand shape of colours used on the Place of the background the font name the label label illustration origin None year Count % Age 12,6% 13,7% 25,3% 8,4% 4,2% 13,7% 8,4% 2,1% 11,6% 100,0% % Label 54,5% 46,4% 50,0% 57,1% 57,1% 50,0% 42,1% 25,0% 44,0% 48,2% % Total 6,1% 6,6% 12,2% 4,1% 2,0% 6,6% 4,1% 1,0% 5,6% 48,2% year Count % Age 9,1% 15,9% 22,7% 2,3% 2,3% 11,4% 11,4% 9,1% 15,9% 100,0% % Label 18,2% 25,0% 20,8% 7,1% 14,3% 19,2% 26,3% 50,0% 28,0% 22,3% % Total 2,0% 3,6% 5,1% 0,5% 0,5% 2,5% 2,5% 2,0% 3,6% 22,3% year Count % Age 10,3% 13,8% 20,7% 6,9% 3,5% 20,7% 6,9% 3,5% 13,8% 100,0% % Label 13,6% 14,3% 12,5% 14,3% 14,3% 23,1% 10,5% 12,5% 16,0% 14,7% % Total 1,5% 2,0% 3,1% 1,0% 0,5% 3,1% 1,0% 0,5% 2,0% 14,7% year Count % Age 9,5% 14,3% 23,8% 14,3% 4,8% 9,5% 9,5% 4,8% 9,5% 100,0% % Label 9,1% 10,7% 10,4% 21,4% 14,3% 7,7% 10,5% 12,5% 8,0% 10,7% % Total 1,0% 1,5% 2,5% 1,5% 0,5% 1,0% 1,0% 0,5% 1,0% 10,7% year Count % Age 0,0% 14,3% 42,9% 0,0% 0,0% 0,0% 28,6% 0,0% 14,3% 100,0% % Label 0,0% 3,6% 6,3% 0,0% 0,0% 0,0% 10,5% 0,0% 4,0% 3,6% % Total 0,0% 0,5% 1,5% 0,0% 0,0% 0,0% 1,0% 0,0% 0,5% 3,6% 70+ year Count % Age 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 4,5% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,5% % Total 0,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,5% Total Count % Age 11,2% 14,2% 24,4% 7,1% 3,6% 13,2% 9,7% 4,1% 12,7% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 11,2% 14,2% 24,4% 7,1% 3,6% 13,2% 9,7% 4,1% 12,7% 100,0% Table 50: Age vs other elements set 7 91

92 SET 8 Age Set 8: Which one of these labels would Gender Set 8: Which one of these labels would you choose? Total Label 1 Label 2 Label 3 Man Count % Gender 22,9% 10,4% 66,7% 100,0% % Label 23,9% 38,5% 41,6% 35,3% % Total 8,1% 3,7% 23,5% 35,3% Woman Count % Gender 39,8% 9,1% 51,1% 100,0% % Label 76,1% 61,5% 58,4% 64,7% % Total 25,7% 5,9% 33,1% 64,7% Total Count % Gender 33,8% 9,6% 56,6% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 33,8% 9,6% 56,6% 100,0% Table 51: Gender vs. labels set 8 56,6% Favourite label 33,8% 9,6% Total you choose? Label 1 Label 2 Label year Count % Age 37,1% 11,3% 51,6% 100,0% % Label 50,0% 53,8% 41,6% 45,6% % Total 16,9% 5,1% 23,5% 45,6% year Count % Age 30,0% 6,7% 63,3% 100,0% % Label 19,6% 15,4% 24,7% 22,1% % Total 6,6% 1,5% 14,0% 22,1% year Count % Age 37,5% 4,2% 58,3% 100,0% % Label 19,6% 7,7% 18,2% 17,6% % Total 6,6% 0,7% 10,3% 17,6% year Count % Age 20,0% 20,0% 60,0% 100,0% % Label 6,5% 23,1% 11,7% 11,0% % Total 2,2% 2,2% 6,6% 11,0% year Count % Age 50,0% 0,0% 50,0% 100,0% % Label 4,3% 0,0% 2,6% 2,9% % Total 1,5% 0,0% 1,5% 2,9% 70+ year Count % Age 0,0% 0,0% 100,0% 100,0% % Label 0,0% 0,0% 1,3% 0,7% % Total 0,0% 0,0% 0,7% 0,7% Total Count % Age 33,8% 9,6% 56,6% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 33,8% 9,6% 56,6% 100,0% Table 52: Age vs. labels set 8 Label 1 Label 2 Label 3 Figure 17: Favourite label set 8 92

93 Age Set 8: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Grape varietal Other year Count % Age 4,8% 0,0% 11,3% 24,2% 6,5% 4,8% 32,3% 6,5% 8,1% 1,6% 100,0% % Label 42,9% 0,0% 46,7% 60,0% 57,1% 50,0% 41,7% 57,1% 35,7% 16,7% 45,6% % Total 2,2% 0,0% 5,1% 11,0% 2,9% 2,2% 14,7% 2,9% 3,7% 0,7% 45,6% year Count % Age 0,0% 0,0% 10,0% 16,7% 6,7% 6,7% 36,7% 6,7% 13,3% 3,3% 100,0% % Label 0,0% 0,0% 20,0% 20,0% 28,6% 33,3% 22,9% 28,6% 28,6% 16,7% 22,1% % Total 0,0% 0,0% 2,2% 3,7% 1,5% 1,5% 8,1% 1,5% 2,9% 0,7% 22,1% year Count % Age 4,2% 4,2% 20,8% 20,8% 4,2% 4,2% 20,8% 0,0% 12,5% 8,3% 100,0% % Label 14,3% 100,0% 33,3% 20,0% 14,3% 16,7% 10,4% 0,0% 21,4% 33,3% 17,6% % Total 0,7% 0,7% 3,7% 3,7% 0,7% 0,7% 3,7% 0,0% 2,2% 1,5% 17,6% year Count % Age 13,3% 0,0% 0,0% 0,0% 0,0% 0,0% 60,0% 6,7% 13,3% 6,7% 100,0% % Label 28,6% 0,0% 0,0% 0,0% 0,0% 0,0% 18,8% 14,3% 14,3% 16,7% 11,0% % Total 1,5% 0,0% 0,0% 0,0% 0,0% 0,0% 6,6% 0,7% 1,5% 0,7% 11,0% year Count % Age 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 75,0% 0,0% 0,0% 25,0% 100,0% % Label 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 6,3% 0,0% 0,0% 16,7% 2,9% % Total 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 2,2% 0,0% 0,0% 0,7% 2,9% 70+ year Count % Age 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 14,3% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% % Total 0,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% Total Count % Age 5,1% 0,7% 11,0% 18,4% 5,1% 4,4% 35,3% 5,1% 10,3% 4,4% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 5,1% 0,7% 11,0% 18,4% 5,1% 4,4% 35,3% 5,1% 10,3% 4,4% 100,0% Table 53: Age vs. elements set 8 Labels Set 8: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Grape varietal Other Label 1 Count % Label 4,3% 2,2% 13,0% 4,3% 2,2% 6,5% 52,2% 0,0% 10,9% 4,3% 100,0% % Element 28,6% 100,0% 40,0% 8,0% 14,3% 50,0% 50,0% 0,0% 35,7% 33,3% 33,8% % Total 1,5% 0,7% 4,4% 1,5% 0,7% 2,2% 17,6% 0,0% 3,7% 1,5% 33,8% Label 2 Count % Label 0,0% 0,0% 7,7% 7,7% 0,0% 0,0% 38,5% 30,8% 15,4% 0,0% 100,0% % Element 0,0% 0,0% 6,7% 4,0% 0,0% 0,0% 10,4% 57,1% 14,3% 0,0% 9,6% % Total 0,0% 0,0% 0,7% 0,7% 0,0% 0,0% 3,7% 2,9% 1,5% 0,0% 9,6% Label 3 Count

94 % Label 6,5% 0,0% 10,4% 28,6% 7,8% 3,9% 24,7% 3,9% 9,1% 5,2% 100,0% % Element 71,4% 0,0% 53,3% 88,0% 85,7% 50,0% 39,6% 42,9% 50,0% 66,7% 56,6% % Total 3,7% 0,0% 5,9% 16,2% 4,4% 2,2% 14,0% 2,2% 5,1% 2,9% 56,6% Total Count % Label 5,1% 0,7% 11,0% 18,4% 5,1% 4,4% 35,3% 5,1% 10,3% 4,4% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 5,1% 0,7% 11,0% 18,4% 5,1% 4,4% 35,3% 5,1% 10,3% 4,4% 100,0% Table 54: Labels vs. elements set 8 Gender Labels Set 8: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Grape varietal Other Man Label 1 Count % Label 0,0% 0,0% 0,0% 9,1% 0,0% 18,2% 45,5% 0,0% 18,2% 9,1% 100,0% % Element 0,0% 0,0% 0,0% 14,3% 0,0% 50,0% 35,7% 0,0% 22,2% 25,0% 22,9% % Gender 0,0% 0,0% 0,0% 2,1% 0,0% 4,2% 10,4% 0,0% 4,2% 2,1% 22,9% Label 2 Count % Label 0,0% 0,0% 20,0% 0,0% 0,0% 0,0% 40,0% 20,0% 20,0% 0,0% 100,0% % Element 0,0% 0,0% 20,0% 0,0% 0,0% 0,0% 14,3% 50,0% 11,1% 0,0% 10,4% % Gender 0,0% 0,0% 2,1% 0,0% 0,0% 0,0% 4,2% 2,1% 2,1% 0,0% 10,4% Label 3 Count % Label 0,0% 0,0% 12,5% 18,8% 9,4% 6,3% 21,9% 3,1% 18,8% 9,4% 100,0% % Element 0,0% 0,0% 80,0% 85,7% 100,0% 50,0% 50,0% 50,0% 66,7% 75,0% 66,7% % Gender 0,0% 0,0% 8,3% 12,5% 6,3% 4,2% 14,6% 2,1% 12,5% 6,3% 66,7% Total Count % Label 0,0% 0,0% 10,4% 14,6% 6,3% 8,3% 29,2% 4,2% 18,8% 8,3% 100,0% % Element 0,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 0,0% 0,0% 10,4% 14,6% 6,3% 8,3% 29,2% 4,2% 18,8% 8,3% 100,0% Woman Label 1 Count % Label 5,7% 2,9% 17,1% 2,9% 2,9% 2,9% 54,3% 0,0% 8,6% 2,9% 100,0% % Element 28,6% 100,0% 60,0% 5,6% 25,0% 50,0% 55,9% 0,0% 60,0% 50,0% 39,8% % Gender 2,3% 1,1% 6,8% 1,1% 1,1% 1,1% 21,6% 0,0% 3,4% 1,1% 39,8% Label 2 Count % Label 0,0% 0,0% 0,0% 12,5% 0,0% 0,0% 37,5% 37,5% 12,5% 0,0% 100,0% % Element 0,0% 0,0% 0,0% 5,6% 0,0% 0,0% 8,8% 60,0% 20,0% 0,0% 9,1% % Gender 0,0% 0,0% 0,0% 1,1% 0,0% 0,0% 3,4% 3,4% 1,1% 0,0% 9,1% Label 3 Count % Label 11,1% 0,0% 8,9% 35,6% 6,7% 2,2% 26,7% 4,4% 2,2% 2,2% 100,0% % Element 71,4% 0,0% 40,0% 88,9% 75,0% 50,0% 35,3% 40,0% 20,0% 50,0% 51,1% % Gender 5,7% 0,0% 4,5% 18,2% 3,4% 1,1% 13,6% 2,3% 1,1% 1,1% 51,1% Total Count % Label 8,0% 1,1% 11,4% 20,5% 4,5% 2,3% 38,6% 5,7% 5,7% 2,3% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 8,0% 1,1% 11,4% 20,5% 4,5% 2,3% 38,6% 5,7% 5,7% 2,3% 100,0% 94

95 Total Label 1 Count % Label 4,3% 2,2% 13,0% 4,3% 2,2% 6,5% 52,2% 0,0% 10,9% 4,3% 100,0% % Element 28,6% 100,0% 40,0% 8,0% 14,3% 50,0% 50,0% 0,0% 35,7% 33,3% 33,8% % Gender 1,5% 0,7% 4,4% 1,5% 0,7% 2,2% 17,6% 0,0% 3,7% 1,5% 33,8% Label 2 Count % Label 0,0% 0,0% 7,7% 7,7% 0,0% 0,0% 38,5% 30,8% 15,4% 0,0% 100,0% % Element 0,0% 0,0% 6,7% 4,0% 0,0% 0,0% 10,4% 57,1% 14,3% 0,0% 9,6% % Gender 0,0% 0,0% 0,7% 0,7% 0,0% 0,0% 3,7% 2,9% 1,5% 0,0% 9,6% Label 3 Count % Label 6,5% 0,0% 10,4% 28,6% 7,8% 3,9% 24,7% 3,9% 9,1% 5,2% 100,0% % Element 71,4% 0,0% 53,3% 88,0% 85,7% 50,0% 39,6% 42,9% 50,0% 66,7% 56,6% % Gender 3,7% 0,0% 5,9% 16,2% 4,4% 2,2% 14,0% 2,2% 5,1% 2,9% 56,6% Total Count % Label 5,1% 0,7% 11,0% 18,4% 5,1% 4,4% 35,3% 5,1% 10,3% 4,4% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 5,1% 0,7% 11,0% 18,4% 5,1% 4,4% 35,3% 5,1% 10,3% 4,4% 100,0% Table 55: Gender and labels vs. elements set 8 Other important elements None Grape varietal Place of origin illustration colours used on the label shape of the label brand name style of the font colour of the font colour of the background 4,6% 7,2% 6,7% 6,7% 7,7% 7,2% 10,3% 14,4% 16,4% 19,0% 0,00% 2,00% 4,00% 6,00% 8,00% 10,00% 12,00% 14,00% 16,00% 18,00% 20,00% Favourite label Figure 18: Other important elements set 8 95

96 Gender Labels Set 8: What are other important elements for you? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Grape varietal None Man Label 1 Count % Labels 7,8% 0,0% 15,4% 0,0% 0,0% 15,4% 15,4% 0,0% 7,8% 38,5% 100,0% % Gender 33,3% 0,0% 22,2% 0,0% 0,0% 33,3% 15,4% 0,0% 16,7% 35,7% 19,7% % Total 0,5% 0,0% 1,0% 0,0% 0,0% 1,0% 1,0% 0,0% 0,5% 2,6% 6,7% Label 2 Count % Labels 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 20,0% 20,0% 0,0% 60,0% 100,0% % Gender 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 7,7% 33,3% 0,0% 21,4% 7,6% % Total 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,5% 0,5% 0,0% 1,5% 2,6% Label 3 Count % Labels 4,2% 6,3% 15,6% 8,3% 10,4% 8,3% 20,8% 4,2% 10,4% 12,5% 100,0% % Gender 66,7% 100,0% 77,8% 100,0% 100,0% 66,7% 76,9% 66,7% 83,3% 42,9% 72,7% % Total 1,0% 1,5% 3,6% 2,1% 2,6% 2,1% 5,1% 1,0% 2,6% 3,1% 24,6% Total Count % Labels 4,6% 4,6% 13,6% 6,1% 7,6% 9,1% 19,7% 4,6% 9,1% 21,2% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 33,9% % Total 1,5% 1,5% 4,6% 2,1% 2,6% 3,1% 6,7% 1,5% 3,1% 7,2% 33,9% Woman Label 1 Count % Labels 10,6% 10,6% 25,5% 4,3% 6,4% 12,8% 17,0% 2,1% 4,3% 6,4% 100,0% % Gender 50,0% 50,0% 52,2% 20,0% 30,0% 42,9% 33,3% 16,7% 25,0% 21,4% 36,4% % Total 2,6% 2,6% 6,2% 1,0% 1,5% 3,1% 4,1% 0,5% 1,0% 1,5% 24,1% Label 2 Count % Labels 6,3% 6,3% 12,5% 6,3% 12,5% 12,5% 18,8% 6,3% 6,3% 12,5% 100,0% % Gender 10,0% 10,0% 8,7% 10,0% 20,0% 14,3% 12,5% 16,7% 12,5% 14,3% 12,4% % Total 0,5% 0,5% 1,0% 0,5% 1,0% 1,0% 1,5% 0,5% 0,5% 1,0% 8,2% Label 3 Count % Labels 6,1% 6,1% 13,6% 10,6% 7,6% 9,1% 19,7% 6,1% 7,6% 13,6% 100,0% % Gender 40,0% 40,0% 39,1% 70,0% 50,0% 42,9% 54,2% 66,7% 62,5% 64,3% 51,2% % Total 2,1% 2,1% 4,6% 3,6% 2,6% 3,1% 6,7% 2,1% 2,6% 4,6% 33,8% Total Count % Labels 7,7% 7,7% 17,8% 7,7% 7,7% 10,9% 18,6% 6,7% 6,2% 10,9% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 5,1% 5,1% 11,8% 5,1% 5,1% 7,2% 12,3% 3,1% 4,1% 7,2% 66,2% Total Label 1 Count % Labels 10,0% 8,3% 23,3% 3,3% 5,0% 13,3% 16,7% 1,7% 5,0% 13,3% 100,0% % Gender 46,2% 38,5% 43,8% 14,3% 20,0% 40,0% 27,0% 11,1% 21,4% 28,6% 30,8% % Total 3,1% 2,6% 7,2% 1,0% 1,5% 4,1% 5,1% 0,5% 1,5% 4,1% 30,8% Label 2 Count % Labels 4,8% 4,8% 9,5% 4,8% 9,5% 9,5% 19,1% 9,5% 4,8% 23,8% 100,0% % Gender 7,7% 7,7% 6,3% 7,1% 13,3% 10,0% 10,8% 22,2% 7,1% 17,9% 10,8% % Total 0,5% 0,5% 1,0% 0,5% 1,0% 1,0% 2,1% 1,0% 0,5% 2,6% 10,8% Label 3 Count

97 % Labels 5,3% 6,1% 14,0% 9,7% 8,8% 8,8% 20,2% 5,3% 8,8% 13,2% 100,0% % Gender 46,2% 53,8% 50,0% 78,6% 66,7% 50,0% 62,2% 66,7% 71,4% 53,6% 58,5% % Total 3,1% 3,6% 8,2% 5,6% 5,1% 5,1% 11,8% 3,1% 5,1% 7,7% 58,5% Total Count % Labels 6,7% 6,7% 16,4% 7,2% 7,7% 10,3% 19,0% 4,6% 7,2% 14,4% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 6,7% 6,7% 16,4% 7,2% 7,7% 10,3% 19,0% 4,6% 7,2% 14,4% 100,0% Table 56: Gender and labels vs. other important elements set 8 Age Set 8: What are other important elements for you? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Grape varietal None year Count % Age 6,2% 7,2% 18,6% 5,2% 7,2% 11,3% 20,6% 4,1% 4,1% 15,5% 100,0% % Label 46,2% 53,8% 56,3% 35,7% 46,7% 55,0% 54,1% 44,4% 28,6% 53,6% 49,7% % Total 3,1% 3,6% 9,2% 2,6% 3,6% 5,6% 10,3% 2,1% 2,1% 7,7% 49,7% year Count % Age 12,2% 2,4% 19,5% 9,8% 7,3% 4,9% 17,1% 7,3% 7,3% 12,2% 100,0% % Label 38,5% 7,7% 25,0% 28,6% 20,0% 10,0% 18,9% 33,3% 21,4% 17,9% 21,0% % Total 2,6% 0,5% 4,1% 2,1% 1,5% 1,0% 3,6% 1,5% 1,5% 2,6% 21,0% year Count % Age 3,0% 9,1% 9,1% 9,1% 9,1% 21,2% 21,2% 3,0% 9,1% 6,1% 100,0% % Label 7,7% 23,1% 9,4% 21,4% 20,0% 35,0% 18,9% 11,1% 21,4% 7,1% 16,9% % Total 0,5% 1,5% 1,5% 1,5% 1,5% 3,6% 3,6% 0,5% 1,5% 1,0% 16,9% year Count % Age 5,3% 5,3% 10,5% 10,5% 10,5% 0,0% 15,8% 5,3% 15,8% 21,1% 100,0% % Label 7,7% 7,7% 6,3% 14,3% 13,3% 0,0% 8,1% 11,1% 21,4% 14,3% 9,7% % Total 0,5% 0,5% 1,0% 1,0% 1,0% 0,0% 1,5% 0,5% 1,5% 2,1% 9,7% year Count % Age 0,0% 0,0% 25,0% 0,0% 0,0% 0,0% 0,0% 0,0% 25,0% 50,0% 100,0% % Label 0,0% 0,0% 3,1% 0,0% 0,0% 0,0% 0,0% 0,0% 7,1% 7,1% 2,1% % Total 0,0% 0,0% 0,5% 0,0% 0,0% 0,0% 0,0% 0,0% 0,5% 1,0% 2,1% 70+ year Count % Age 0,0% 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 0,0% 7,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,5% % Total 0,0% 0,5% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,5% Total Count % Age 6,7% 6,7% 16,4% 7,2% 7,7% 10,3% 19,0% 4,6% 7,2% 14,4% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 6,7% 6,7% 16,4% 7,2% 7,7% 10,3% 19,0% 4,6% 7,2% 14,4% 100,0% Table 57: age vs. other important elements set 8 97

98 SET 9 Gender Set 9: Which one of these labels would you choose? Total Label 1 Label 2 Label 3 Man Count % Gender 43,8% 33,3% 22,9% 100,0% % Label 40,4% 32,7% 31,4% 35,3% % Total 15,4% 11,8% 8,1% 35,3% Woman Count % Gender 35,2% 37,5% 27,3% 100,0% % Label 59,6% 67,3% 68,6% 64,7% % Total 22,8% 24,3% 17,6% 64,7% Total Count % Gender 38,2% 36,0% 25,7% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 38,2% 36,0% 25,7% 100,0% Table 58: Gender vs. labels set 9 Favourite label 25,7% 38,2% Age Set 9: Which one of these labels would you choose? Total Label 1 Label 2 Label year Count % Age 29,0% 40,3% 30,6% 100,0% % Label 34,6% 51,0% 54,3% 45,6% % Total 13,2% 18,4% 14,0% 45,6% year Count % Age 40,0% 36,7% 23,3% 100,0% % Label 23,1% 22,4% 20,0% 22,1% % Total 8,8% 8,1% 5,1% 22,1% year Count % Age 54,2% 25,0% 20,8% 100,0% % Label 25,0% 12,2% 14,3% 17,6% % Total 9,6% 4,4% 3,7% 17,6% year Count % Age 46,7% 33,3% 20,0% 100,0% % Label 13,5% 10,2% 8,6% 11,0% % Total 5,1% 3,7% 2,2% 11,0% year Count % Age 50,0% 50,0% 0,0% 100,0% % Label 3,8% 4,1% 0,0% 2,9% % Total 1,5% 1,5% 0,0% 2,9% 70+ year Count % Age 0,0% 0,0% 100,0% 100,0% % Label 0,0% 0,0% 2,9% 0,7% % Total 0,0% 0,0% 0,7% 0,7% Total Count % Age 38,2% 36,0% 25,7% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 38,2% 36,0% 25,7% 100,0% Table 59: Age vs. labels set 9 36,0% Label 1 Label 2 Label 3 Figure 19: Favourite label set 9 98

99 Age Set 9: What attracted you the most in the chosen label? Total colour of the colour of the font style of brand shape of colours used on the Place of background the font name the label label illustration origin Other year Count % Age 14,5% 3,2% 11,3% 3,2% 0,0% 9,7% 45,2% 12,9% 0,0% 100,0% % Label 37,5% 66,7% 46,7% 50,0% 0,0% 46,2% 50,9% 50,0% 0,0% 45,6% % Total 6,6% 1,5% 5,1% 1,5% 0,0% 4,4% 20,6% 5,9% 0,0% 45,6% year Count % Age 20,0% 0,0% 13,3% 0,0% 0,0% 10,0% 36,7% 13,3% 6,7% 100,0% % Label 25,0% 0,0% 26,7% 0,0% 0,0% 23,1% 20,0% 25,0% 40,0% 22,1% % Total 4,4% 0,0% 2,9% 0,0% 0,0% 2,2% 8,1% 2,9% 1,5% 22,1% year Count % Age 25,0% 0,0% 12,5% 8,3% 4,2% 12,5% 25,0% 0,0% 12,5% 100,0% % Label 25,0% 0,0% 20,0% 50,0% 100,0% 23,1% 10,9% 0,0% 60,0% 17,6% % Total 4,4% 0,0% 2,2% 1,5% 0,7% 2,2% 4,4% 0,0% 2,2% 17,6% year Count % Age 20,0% 0,0% 0,0% 0,0% 0,0% 0,0% 53,3% 26,7% 0,0% 100,0% % Label 12,5% 0,0% 0,0% 0,0% 0,0% 0,0% 14,5% 25,0% 0,0% 11,0% % Total 2,2% 0,0% 0,0% 0,0% 0,0% 0,0% 5,9% 2,9% 0,0% 11,0% year Count % Age 0,0% 0,0% 25,0% 0,0% 0,0% 25,0% 50,0% 0,0% 0,0% 100,0% % Label 0,0% 0,0% 6,7% 0,0% 0,0% 7,7% 3,6% 0,0% 0,0% 2,9% % Total 0,0% 0,0% 0,7% 0,0% 0,0% 0,7% 1,5% 0,0% 0,0% 2,9% 70+ year Count % Age 0,0% 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 0,0% 33,3% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% % Total 0,0% 0,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% Total Count % Age 17,6% 2,2% 11,0% 2,9% 0,7% 9,6% 40,4% 11,8% 3,7% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 17,6% 2,2% 11,0% 2,9% 0,7% 9,6% 40,4% 11,8% 3,7% 100,0% Table 60: Age vs. elements set 9 Labels Set 9: What attracted you the most in the chosen label? Total colour of colour of the font style of brand shape of colours used on the Place of the background the font name the label label illustration origin Other Label 1 Count % Label 19,2% 0,0% 3,8% 1,9% 0,0% 9,6% 44,2% 13,5% 7,7% 100,0% % Element 41,7% 0,0% 13,3% 25,0% 0,0% 38,5% 41,8% 43,8% 80,0% 38,2% % Total 7,4% 0,0% 1,5% 0,7% 0,0% 3,7% 16,9% 5,1% 2,9% 38,2% Label 2 Count % Label 10,2% 4,1% 26,5% 0,0% 2,0% 14,3% 24,5% 18,4% 0,0% 100,0% % Element 20,8% 66,7% 86,7% 0,0% 100,0% 53,8% 21,8% 56,3% 0,0% 36,0% % Total 3,7% 1,5% 9,6% 0,0% 0,7% 5,1% 8,8% 6,6% 0,0% 36,0% Label 3 Count

100 % Label 25,7% 2,9% 0,0% 8,6% 0,0% 2,9% 57,1% 0,0% 2,9% 100,0% % Element 37,5% 33,3% 0,0% 75,0% 0,0% 7,7% 36,4% 0,0% 20,0% 25,7% % Total 6,6% 0,7% 0,0% 2,2% 0,0% 0,7% 14,7% 0,0% 0,7% 25,7% Total Count % Label 17,6% 2,2% 11,0% 2,9% 0,7% 9,6% 40,4% 11,8% 3,7% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 17,6% 2,2% 11,0% 2,9% 0,7% 9,6% 40,4% 11,8% 3,7% 100,0% Table 61: Labels vs. elements set 9 Gender Labels Set 9: What attracted you the most in the chosen label? Total colour of the colour of the font style of brand shape of colours used on the Place of background the font name the label label illustration origin Other Man Label 1 Count % Label 4,8% 0,0% 0,0% 0,0% 0,0% 9,5% 57,1% 14,3% 14,3% 100,0% % Element 12,5% 0,0% 0,0% 0,0% 0,0% 40,0% 70,6% 42,9% 75,0% 43,8% % Gender 2,1% 0,0% 0,0% 0,0% 0,0% 4,2% 25,0% 6,3% 6,3% 43,8% Label 2 Count % Label 18,8% 0,0% 31,3% 0,0% 0,0% 18,8% 6,3% 25,0% 0,0% 100,0% % Element 37,5% 0,0% 100,0% 0,0% 0,0% 60,0% 5,9% 57,1% 0,0% 33,3% % Gender 6,3% 0,0% 10,4% 0,0% 0,0% 6,3% 2,1% 8,3% 0,0% 33,3% Label 3 Count % Label 36,4% 0,0% 0,0% 18,2% 0,0% 0,0% 36,4% 0,0% 9,1% 100,0% % Element 50,0% 0,0% 0,0% 100,0% 0,0% 0,0% 23,5% 0,0% 25,0% 22,9% % Gender 8,3% 0,0% 0,0% 4,2% 0,0% 0,0% 8,3% 0,0% 2,1% 22,9% Total Count % Label 16,7% 0,0% 10,4% 4,2% 0,0% 10,4% 35,4% 14,6% 8,3% 100,0% % Element 100,0% 0,0% 100,0% 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 16,7% 0,0% 10,4% 4,2% 0,0% 10,4% 35,4% 14,6% 8,3% 100,0% Woman Label 1 Count % Label 29,0% 0,0% 6,5% 3,2% 0,0% 9,7% 35,5% 12,9% 3,2% 100,0% % Element 56,3% 0,0% 20,0% 50,0% 0,0% 37,5% 28,9% 44,4% 100,0% 35,2% % Gender 10,2% 0,0% 2,3% 1,1% 0,0% 3,4% 12,5% 4,5% 1,1% 35,2% Label 2 Count % Label 6,1% 6,1% 24,2% 0,0% 3,0% 12,1% 33,3% 15,2% 0,0% 100,0% % Element 12,5% 66,7% 80,0% 0,0% 100,0% 50,0% 28,9% 55,6% 0,0% 37,5% % Gender 2,3% 2,3% 9,1% 0,0% 1,1% 4,5% 12,5% 5,7% 0,0% 37,5% Label 3 Count % Label 20,8% 4,2% 0,0% 4,2% 0,0% 4,2% 66,7% 0,0% 0,0% 100,0% % Element 31,3% 33,3% 0,0% 50,0% 0,0% 12,5% 42,1% 0,0% 0,0% 27,3% % Gender 5,7% 1,1% 0,0% 1,1% 0,0% 1,1% 18,2% 0,0% 0,0% 27,3% Total Count % Label 18,2% 3,4% 11,4% 2,3% 1,1% 9,1% 43,2% 10,2% 1,1% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 18,2% 3,4% 11,4% 2,3% 1,1% 9,1% 43,2% 10,2% 1,1% 100,0% 100

101 Total Label 1 Count % Label 19,2% 0,0% 3,8% 1,9% 0,0% 9,6% 44,2% 13,5% 7,7% 100,0% % Element 41,7% 0,0% 13,3% 25,0% 0,0% 38,5% 41,8% 43,8% 80,0% 38,2% % Gender 7,4% 0,0% 1,5% 0,7% 0,0% 3,7% 16,9% 5,1% 2,9% 38,2% Label 2 Count % Label 10,2% 4,1% 26,5% 0,0% 2,0% 14,3% 24,5% 18,4% 0,0% 100,0% % Element 20,8% 66,7% 86,7% 0,0% 100,0% 53,8% 21,8% 56,3% 0,0% 36,0% % Gender 3,7% 1,5% 9,6% 0,0% 0,7% 5,1% 8,8% 6,6% 0,0% 36,0% Label 3 Count % Label 25,7% 2,9% 0,0% 8,6% 0,0% 2,9% 57,1% 0,0% 2,9% 100,0% % Element 37,5% 33,3% 0,0% 75,0% 0,0% 7,7% 36,4% 0,0% 20,0% 25,7% % Gender 6,6% 0,7% 0,0% 2,2% 0,0% 0,7% 14,7% 0,0% 0,7% 25,7% Total Count % Label 17,6% 2,2% 11,0% 2,9% 0,7% 9,6% 40,4% 11,8% 3,7% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 17,6% 2,2% 11,0% 2,9% 0,7% 9,6% 40,4% 11,8% 3,7% 100,0% Table 62: Gender and labels vs. elements set 9 Other important element None 12,9% place of origin 9,1% illustration 17,7% colours used on the labels 14,8% shape of the label 1,9% brand name 5,3% style of the font 19,6% colour of the font 8,1% colour of the background 10,5% 0,00% 5,00% 10,00% 15,00% 20,00% 25,00% Other important element Figure 20: other important elements set 9 101

102 Gender Labels Set 9: What are other important elements for you? Total colour of the colour style brand shape of the label colours used on the Place of origin background of the font of the font name label illustration None Man Label 1 Count % Labels 8,3% 4,2% 8,3% 8,3% 0,0% 12,5% 16,7% 4,2% 37,5% 100,0% % Gender 25,0% 20,0% 15,4% 40,0% 0,0% 33,3% 30,8% 16,7% 69,2% 33,3% % Total 1,0% 0,5% 1,0% 1,0% 0,0% 1,4% 1,9% 0,5% 4,3% 11,5% Label 2 Count % Labels 12,5% 18,8% 43,8% 6,3% 0,0% 17,9% 17,9% 12,5% 18,8% 100,0% % Gender 25,0% 60,0% 53,8% 20,0% 0,0% 55,6% 38,5% 33,3% 23,1% 38,9% % Total 1,0% 1,4% 3,4% 0,5% 0,0% 2,4% 2,4% 1,0% 1,4% 13,4% Label 3 Count % Labels 20,0% 5,0% 20,0% 10,0% 0,0% 5,0% 20,0% 15,0% 5,0% 100,0% % Gender 50,0% 20,0% 30,8% 40,0% 0,0% 11,1% 30,8% 50,0% 7,7% 27,8% % Total 1,9% 0,5% 1,9% 1,0% 0,0% 0,5% 1,9% 1,4% 0,5% 9,6% Total Count % Labels 11,1% 6,9% 18,1% 6,9% 0,0% 12,5% 18,1% 8,3% 18,1% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 34,5% % Total 3,8% 2,4% 6,2% 2,4% 0,0% 4,3% 6,2% 2,9% 6,2% 34,5% Woman Label 1 Count % Labels 7,5% 12,5% 25,0% 2,5% 0,0% 10,0% 20,0% 10,0% 12,5% 100,0% % Gender 21,4% 41,7% 35,7% 16,7% 0,0% 18,2% 33,3% 30,8% 35,7% 29,2% % Total 1,4% 2,4% 4,8% 0,5% 0,0% 1,9% 3,8% 1,9% 2,4% 19,1% Label 2 Count % Labels 7,8% 7,8% 20,3% 3,1% 4,7% 21,9% 17,2% 7,8% 9,4% 100,0% % Gender 35,7% 41,7% 46,4% 33,3% 75,0% 63,6% 45,8% 38,5% 42,9% 46,7% % Total 2,4% 2,4% 6,2% 1,0% 1,4% 6,7% 5,3% 2,4% 2,9% 30,6% Label 3 Count % Labels 18,2% 6,1% 15,2% 9,1% 3,0% 12,1% 15,2% 12,1% 9,1% 100,0% % Gender 42,9% 16,7% 17,9% 50,0% 25,0% 18,2% 20,8% 30,8% 21,4% 24,1% % Total 2,9% 1,0% 2,4% 1,4% 0,5% 1,9% 2,4% 1,9% 1,4% 15,8% Total Count % Labels 10,2% 8,8% 20,4% 4,4% 2,9% 16,1% 17,5% 9,5% 10,2% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 65,6% % Total 6,7% 5,7% 13,4% 2,9% 1,9% 10,5% 11,5% 6,2% 6,7% 65,6% Total Label 1 Count % Labels 7,8% 9,4% 18,8% 4,7% 0,0% 10,9% 18,8% 7,8% 21,9% 100,0% % Gender 22,7% 35,3% 29,3% 27,3% 0,0% 22,6% 32,4% 26,3% 51,9% 30,7% % Total 2,4% 2,9% 5,7% 1,4% 0,0% 3,4% 5,7% 2,4% 6,7% 30,7% Label 2 Count % Labels 7,6% 8,7% 21,7% 3,3% 3,3% 20,7% 17,4% 7,6% 9,8% 100,0% % Gender 31,8% 47,1% 48,8% 27,3% 75,0% 61,3% 43,2% 36,8% 33,3% 44,0% % Total 3,4% 3,8% 9,6% 1,4% 1,4% 9,1% 7,7% 3,4% 4,3% 44,0% Label 3 Count

103 % Labels 18,9% 5,7% 17,0% 9,4% 1,9% 9,4% 17,0% 13,2% 7,6% 100,0% % Gender 45,5% 17,6% 22,0% 45,5% 25,0% 16,1% 24,3% 36,8% 14,8% 25,4% % Total 4,8% 1,4% 4,3% 2,4% 0,5% 2,4% 4,3% 3,4% 1,9% 25,4% Total Count % Labels 10,5% 8,1% 19,7% 5,3% 1,9% 14,8% 17,7% 9,1% 12,9% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 10,5% 8,1% 19,7% 5,3% 1,9% 14,8% 17,7% 9,1% 12,9% 100,0% Table 63: Gender and labels vs. other elements set 9 Age Set 9: What are other important elements for you? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin None year Count % Age 12,0% 5,6% 22,2% 6,5% 1,9% 15,7% 17,6% 8,3% 10,2% 100,0% % Label 59,1% 35,3% 58,5% 63,6% 50,0% 54,8% 51,4% 47,4% 40,7% 51,7% % Total 6,2% 2,9% 11,5% 3,4% 1,0% 8,1% 9,1% 4,3% 5,3% 51,7% year Count % Age 10,0% 7,5% 15,0% 7,5% 0,0% 7,5% 22,5% 7,5% 22,5% 100,0% % Label 18,2% 17,6% 14,6% 27,3% 0,0% 9,7% 24,3% 15,8% 33,3% 19,1% % Total 1,9% 1,4% 2,9% 1,4% 0,0% 1,4% 4,3% 1,4% 4,3% 19,1% year Count % Age 11,8% 8,8% 14,7% 0,0% 5,9% 26,5% 17,7% 8,8% 5,9% 100,0% % Label 18,2% 17,6% 12,2% 0,0% 50,0% 29,0% 16,2% 15,8% 7,4% 16,3% % Total 1,9% 1,4% 2,4% 0,0% 1,0% 4,3% 2,9% 1,4% 1,0% 16,3% year Count % Age 5,3% 21,1% 21,5% 5,3% 0,0% 5,3% 10,5% 10,5% 21,5% 100,0% % Label 4,5% 23,5% 9,8% 9,1% 0,0% 3,2% 5,4% 10,5% 14,8% 9,1% % Total 0,5% 1,9% 1,9% 0,5% 0,0% 0,5% 1,0% 1,0% 1,9% 9,1% year Count % Age 0,0% 14,3% 14,3% 0,0% 0,0% 14,3% 14,3% 28,6% 14,3% 100,0% % Label 0,0% 5,9% 2,4% 0,0% 0,0% 3,2% 2,7% 10,5% 3,7% 3,4% % Total 0,0% 0,5% 0,5% 0,0% 0,0% 0,5% 0,5% 1,0% 0,5% 3,4% 70+ year Count % Age 0,0% 0,0% 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 0,0% 0,0% 2,4% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,5% % Total 0,0% 0,0% 0,5% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,5% Total Count % Age 10,5% 8,1% 19,7% 5,3% 1,9% 14,8% 17,7% 9,1% 12,9% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 10,5% 8,1% 19,7% 5,3% 1,9% 14,8% 17,7% 9,1% 12,9% 100,0% Table 64: Age vs. other elements set 9 103

104 SET 10 Gender Set 10: Which one of these labels would Total you choose? Label 1 Label 2 Label 3 Man Count % Gender 20,8% 37,5% 41,7% 100,0% % Label 35,7% 33,3% 37,0% 35,3% % Total 7,4% 13,2% 14,7% 35,3% Woman Count % Gender 20,5% 40,9% 38,6% 100,0% % Label 64,3% 66,7% 63,0% 64,7% % Total 13,2% 26,5% 25,0% 64,7% Total Count % Gender 20,6% 39,7% 39,7% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 20,6% 39,7% 39,7% 100,0% Table 65: Gender vs. labels set 10 39,7% Favourite label 20,6% 39,7% Label 1 Label 2 Label 3 Age Set 10: Which one of these labels would you choose? Total Label 1 Label 2 Label year Count % Age 27,4% 30,6% 41,9% 100,0% % Label 60,7% 35,2% 48,1% 45,6% % Total 12,5% 14,0% 19,1% 45,6% year Count % Age 13,3% 53,3% 33,3% 100,0% % Label 14,3% 29,6% 18,5% 22,1% % Total 2,9% 11,8% 7,4% 22,1% year Count % Age 12,5% 45,8% 41,7% 100,0% % Label 10,7% 20,4% 18,5% 17,6% % Total 2,2% 8,1% 7,4% 17,6% year Count % Age 26,7% 33,3% 40,0% 100,0% % Label 14,3% 9,3% 11,1% 11,0% % Total 2,9% 3,7% 4,4% 11,0% year Count % Age 0,0% 50,0% 50,0% 100,0% % Label 0,0% 3,7% 3,7% 2,9% % Total 0,0% 1,5% 1,5% 2,9% 70+ year Count % Age 0,0% 100,0% 0,0% 100,0% % Label 0,0% 1,9% 0,0% 0,7% % Total 0,0% 0,7% 0,0% 0,7% Total Count % Age 20,6% 39,7% 39,7% 100,0% % Label 100,0% 100,0% 100,0% 100,0% % Total 20,6% 39,7% 39,7% 100,0% Table 66: Age vs. labels set 10 Figure 21: favourite label set

105 Age Set 10: What attracted you the most in the chosen label? Total colour of the colour of style of the brand shape of colours used on the Place of Grape varietal background the font font name the label label illustration origin Other year Count % Age 11,3% 4,8% 17,7% 17,7% 0,0% 11,3% 17,7% 8,1% 8,1% 3,2% 100,0% % Label 43,8% 50,0% 47,8% 40,7% 0,0% 50,0% 55,0% 33,3% 55,6% 40,0% 45,6% % Total 5,1% 2,2% 8,1% 8,1% 0,0% 5,1% 8,1% 3,7% 3,7% 1,5% 45,6% year Count % Age 10,0% 6,7% 16,7% 26,7% 0,0% 6,7% 13,3% 16,7% 3,3% 0,0% 100,0% % Label 18,8% 33,3% 21,7% 29,6% 0,0% 14,3% 20,0% 33,3% 11,1% 0,0% 22,1% % Total 2,2% 1,5% 3,7% 5,9% 0,0% 1,5% 2,9% 3,7% 0,7% 0,0% 22,1% year Count % Age 12,5% 0,0% 20,8% 20,8% 4,2% 8,3% 4,2% 8,3% 12,5% 8,3% 100,0% % Label 18,8% 0,0% 21,7% 18,5% 100,0% 14,3% 5,0% 13,3% 33,3% 40,0% 17,6% % Total 2,2% 0,0% 3,7% 3,7% 0,7% 1,5% 0,7% 1,5% 2,2% 1,5% 17,6% year Count % Age 20,0% 0,0% 6,7% 13,3% 0,0% 13,3% 26,7% 20,0% 0,0% 0,0% 100,0% % Label 18,8% 0,0% 4,3% 7,4% 0,0% 14,3% 20,0% 20,0% 0,0% 0,0% 11,0% % Total 2,2% 0,0% 0,7% 1,5% 0,0% 1,5% 2,9% 2,2% 0,0% 0,0% 11,0% year Count % Age 0,0% 0,0% 25,0% 25,0% 0,0% 25,0% 0,0% 0,0% 0,0% 25,0% 100,0% % Label 0,0% 0,0% 4,3% 3,7% 0,0% 7,1% 0,0% 0,0% 0,0% 20,0% 2,9% % Total 0,0% 0,0% 0,7% 0,7% 0,0% 0,7% 0,0% 0,0% 0,0% 0,7% 2,9% 70+ year Count % Age 0,0% 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 0,0% 16,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% % Total 0,0% 0,7% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,7% Total Count % Age 11,8% 4,4% 16,9% 19,9% 0,7% 10,3% 14,7% 11,0% 6,6% 3,7% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 11,8% 4,4% 16,9% 19,9% 0,7% 10,3% 14,7% 11,0% 6,6% 3,7% 100,0% Table 67: Age vs elements set 10 Labels Set 10: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Grape varietal Other Label 1 Count % Label 7,1% 0,0% 10,7% 14,3% 0,0% 10,7% 39,3% 0,0% 7,1% 10,7% 100,0% % Element 12,5% 0,0% 13,0% 14,8% 0,0% 21,4% 55,0% 0,0% 22,2% 60,0% 20,6% % Total 1,5% 0,0% 2,2% 2,9% 0,0% 2,2% 8,1% 0,0% 1,5% 2,2% 20,6% Label 2 Count % Label 16,7% 7,4% 11,1% 16,7% 1,9% 13,0% 14,8% 13,0% 5,6% 0,0% 100,0% % Element 56,3% 66,7% 26,1% 33,3% 100,0% 50,0% 40,0% 46,7% 33,3% 0,0% 39,7% % Total 6,6% 2,9% 4,4% 6,6% 0,7% 5,1% 5,9% 5,1% 2,2% 0,0% 39,7% Label 3 Count % Label 9,3% 3,7% 25,9% 25,9% 0,0% 7,4% 1,9% 14,8% 7,4% 3,7% 100,0% 105

106 % Element 31,3% 33,3% 60,9% 51,9% 0,0% 28,6% 5,0% 53,3% 44,4% 40,0% 39,7% % Total 3,7% 1,5% 10,3% 10,3% 0,0% 2,9% 0,7% 5,9% 2,9% 1,5% 39,7% Total Count % Label 11,8% 4,4% 16,9% 19,9% 0,7% 10,3% 14,7% 11,0% 6,6% 3,7% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 11,8% 4,4% 16,9% 19,9% 0,7% 10,3% 14,7% 11,0% 6,6% 3,7% 100,0% Table 68: Labels vs elements set 10 Gender Labels Set 10: What attracted you the most in the chosen label? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Grape varietal Other Man Label 1 Count % Label 10,0% 0,0% 10,0% 20,0% 0,0% 10,0% 30,0% 0,0% 10,0% 10,0% 100,0% % Element 25,0% 0,0% 12,5% 18,2% 0,0% 16,7% 50,0% 0,0% 33,3% 33,3% 20,8% % Gender 2,1% 0,0% 2,1% 4,2% 0,0% 2,1% 6,3% 0,0% 2,1% 2,1% 20,8% Label 2 Count % Label 16,7% 5,6% 5,6% 16,7% 0,0% 16,7% 16,7% 11,1% 11,1% 0,0% 100,0% % Element 75,0% 50,0% 12,5% 27,3% 0,0% 50,0% 50,0% 40,0% 66,7% 0,0% 37,5% % Gender 6,3% 2,1% 2,1% 6,3% 0,0% 6,3% 6,3% 4,2% 4,2% 0,0% 37,5% Label 3 Count % Label 0,0% 5,0% 30,0% 30,0% 0,0% 10,0% 0,0% 15,0% 0,0% 10,0% 100,0% % Element 0,0% 50,0% 75,0% 54,5% 0,0% 33,3% 0,0% 60,0% 0,0% 66,7% 41,7% % Gender 0,0% 2,1% 12,5% 12,5% 0,0% 4,2% 0,0% 6,3% 0,0% 4,2% 41,7% Total Count % Label 8,3% 4,2% 16,7% 22,9% 0,0% 12,5% 12,5% 10,4% 6,3% 6,3% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 0,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 8,3% 4,2% 16,7% 22,9% 0,0% 12,5% 12,5% 10,4% 6,3% 6,3% 100,0% Woman Label 1 Count % Label 5,6% 0,0% 11,1% 11,1% 0,0% 11,1% 44,4% 0,0% 5,6% 11,1% 100,0% % Element 8,3% 0,0% 13,3% 12,5% 0,0% 25,0% 57,1% 0,0% 16,7% 100,0% 20,5% % Gender 1,1% 0,0% 2,3% 2,3% 0,0% 2,3% 9,1% 0,0% 1,1% 2,3% 20,5% Label 2 Count % Label 16,7% 8,3% 13,9% 16,7% 2,8% 11,1% 13,9% 13,9% 2,8% 0,0% 100,0% % Element 50,0% 75,0% 33,3% 37,5% 100,0% 50,0% 35,7% 50,0% 16,7% 0,0% 40,9% % Gender 6,8% 3,4% 5,7% 6,8% 1,1% 4,5% 5,7% 5,7% 1,1% 0,0% 40,9% Label 3 Count % Label 14,7% 2,9% 23,5% 23,5% 0,0% 5,9% 2,9% 14,7% 11,8% 0,0% 100,0% % Element 41,7% 25,0% 53,3% 50,0% 0,0% 25,0% 7,1% 50,0% 66,7% 0,0% 38,6% % Gender 5,7% 1,1% 9,1% 9,1% 0,0% 2,3% 1,1% 5,7% 4,5% 0,0% 38,6% Total Count % Label 13,6% 4,5% 17,0% 18,2% 1,1% 9,1% 15,9% 11,4% 6,8% 2,3% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 13,6% 4,5% 17,0% 18,2% 1,1% 9,1% 15,9% 11,4% 6,8% 2,3% 100,0% Total Label 1 Count % Label 7,1% 0,0% 10,7% 14,3% 0,0% 10,7% 39,3% 0,0% 7,1% 10,7% 100,0% 106

107 % Element 12,5% 0,0% 13,0% 14,8% 0,0% 21,4% 55,0% 0,0% 22,2% 60,0% 20,6% % Gender 1,5% 0,0% 2,2% 2,9% 0,0% 2,2% 8,1% 0,0% 1,5% 2,2% 20,6% Label 2 Count % Label 16,7% 7,4% 11,1% 16,7% 1,9% 13,0% 14,8% 13,0% 5,6% 0,0% 100,0% % Element 56,3% 66,7% 26,1% 33,3% 100,0% 50,0% 40,0% 46,7% 33,3% 0,0% 39,7% % Gender 6,6% 2,9% 4,4% 6,6% 0,7% 5,1% 5,9% 5,1% 2,2% 0,0% 39,7% Label 3 Count % Label 9,3% 3,7% 25,9% 25,9% 0,0% 7,4% 1,9% 14,8% 7,4% 3,7% 100,0% % Element 31,3% 33,3% 60,9% 51,9% 0,0% 28,6% 5,0% 53,3% 44,4% 40,0% 39,7% % Gender 3,7% 1,5% 10,3% 10,3% 0,0% 2,9% 0,7% 5,9% 2,9% 1,5% 39,7% Total Count % Label 11,8% 4,4% 16,9% 19,9% 0,7% 10,3% 14,7% 11,0% 6,6% 3,7% 100,0% % Element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Gender 11,8% 4,4% 16,9% 19,9% 0,7% 10,3% 14,7% 11,0% 6,6% 3,7% 100,0% Table 69: Gender and labels vs. elements set 10 Other important elements None grape varietal place of origin illustration colours used on the label shape of the label brand name style of the font colour of the font colour of the background 2,7% 6,1% 5,4% 8,2% 8,2% 8,8% 6,8% 12,9% 16,3% 24,5% 0,00% 5,00% 10,00% 15,00% 20,00% 25,00% 30,00% Other important elements Figure 22: Other important elements set

108 Gender Labels Set 10: What are other important elements for you? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Grape varietal None Man Label 1 Count % Labels 0,0% 7,8% 16,0% 38,5% 0,0% 0,0% 0,0% 0,0% 0,0% 38,5% 100,0% % Gender 0,0% 33,3% 20,0% 62,5% 0,0% 0,0% 0,0% 0,0% 0,0% 22,7% 22,0% % Total 0,0% 0,6% 1,2% 3,0% 0,0% 0,0% 0,0% 0,0% 0,0% 3,0% 7,8% Label 2 Count % Labels 10,0% 0,0% 5,0% 15,0% 0,0% 5,0% 10,0% 5,0% 5,0% 45,0% 100,0% % Gender 66,7% 0,0% 10,0% 37,5% 0,0% 33,3% 100,0% 33,3% 25,0% 40,9% 33,9% % Total 1,2% 0,0% 0,6% 1,8% 0,0% 0,6% 1,2% 0,6% 0,6% 5,3% 11,8% Label 3 Count % Labels 3,9% 7,7% 26,9% 0,0% 3,9% 7,7% 0,0% 7,7% 11,5% 30,8% 100,0% % Gender 33,3% 66,7% 70,0% 0,0% 100,0% 66,7% 0,0% 66,7% 75,0% 36,4% 44,1% % Total 0,6% 1,2% 4,1% 0,0% 0,6% 1,2% 0,0% 1,2% 1,8% 4,7% 15,4% Total Count % Labels 5,1% 5,1% 17,0% 13,6% 1,7% 5,1% 3,4% 5,1% 6,8% 37,3% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 1,8% 1,8% 5,9% 4,7% 0,6% 1,8% 1,2% 1,8% 2,4% 13,0% 34,9% Woman Label 1 Count % Labels 4,4% 8,7% 8,7% 8,7% 4,4% 17,4% 13,0% 4,4% 8,7% 21,7% 100,0% % Gender 12,5% 20,0% 10,5% 28,6% 20,0% 21,1% 30,0% 16,7% 33,3% 25,0% 20,9% % Total 0,6% 1,2% 1,2% 1,2% 0,6% 2,4% 1,8% 0,6% 1,2% 3,0% 13,6% Label 2 Count % Labels 11,1% 13,3% 15,6% 2,2% 4,4% 20,0% 13,3% 2,2% 0,0% 17,8% 100,0% % Gender 62,5% 60,0% 36,8% 14,3% 40,0% 47,4% 60,0% 16,7% 0,0% 40,0% 40,9% % Total 4,6% 3,6% 4,1% 0,6% 1,2% 5,3% 3,6% 0,6% 0,0% 4,7% 26,6% Label 3 Count % Labels 4,8% 4,8% 23,8% 9,5% 4,8% 14,3% 2,4% 9,5% 9,5% 16,7% 100,0% % Gender 25,0% 20,0% 52,6% 57,1% 40,0% 31,6% 10,0% 66,7% 66,7% 35,0% 38,2% % Total 1,2% 1,2% 5,9% 2,4% 1,2% 3,6% 0,6% 2,4% 2,4% 4,1% 24,9% Total Count % Labels 7,3% 9,1% 17,3% 6,4% 4,6% 17,3% 9,1% 5,5% 5,5% 18,2% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 4,7% 5,9% 11,2% 4,1% 3,0% 11,2% 5,9% 3,6% 3,6% 11,8% 65,1% Total Label 1 Count % Labels 2,8% 8,3% 11,1% 19,4% 2,8% 11,1% 8,3% 2,8% 5,6% 27,8% 100,0% % Gender 9,1% 23,1% 13,8% 46,7% 16,7% 18,2% 25,0% 11,1% 20,0% 23,8% 21,3% % Total 0,6% 1,8% 2,4% 4,1% 0,6% 2,4% 1,8% 0,6% 1,2% 5,9% 21,3% Label 2 Count % Labels 10,8% 9,2% 12,3% 6,2% 3,1% 15,4% 12,3% 3,1% 1,5% 26,2% 100,0% % Gender 63,6% 46,2% 27,6% 26,7% 33,3% 45,5% 66,7% 22,2% 10,0% 40,5% 38,5% % Total 4,1% 3,6% 4,7% 2,4% 1,2% 5,9% 4,7% 1,2% 0,6% 10,1% 38,5% Label 3 Count

109 % Labels 4,4% 5,9% 25,0% 5,9% 4,4% 11,8% 1,5% 8,8% 10,3% 22,1% 100,0% % Gender 27,3% 30,8% 58,6% 26,7% 50,0% 36,4% 8,3% 66,7% 70,0% 35,7% 40,2% % Total 1,8% 2,4% 10,1% 2,4% 1,8% 4,7% 0,6% 3,6% 4,1% 8,9% 40,2% Total Count % Labels 6,5% 7,8% 17,2% 8,9% 3,6% 13,0% 7,1% 5,3% 5,9% 24,9% 100,0% % Gender 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 6,5% 7,8% 17,2% 8,9% 3,6% 13,0% 7,1% 5,3% 5,9% 24,9% 100,0% Table 70: Gender and labels vs. other elements set 10 Age Set 10: What are other important elements for you? Total colour of the background colour of the font style of the font brand name shape of the label colours used on the label illustration Place of origin Grape varietal None year Count % Age 8,4% 9,6% 20,5% 6,0% 4,8% 14,5% 4,8% 6,0% 4,8% 20,5% 100,0% % Label 63,6% 61,5% 58,6% 33,3% 66,7% 54,5% 33,3% 55,6% 40,0% 40,5% 49,1% % Total 4,1% 4,7% 10,1% 3,0% 2,4% 7,1% 2,4% 3,0% 2,4% 10,1% 49,1% year Count % Age 3,0% 3,0% 9,1% 12,1% 0,0% 9,1% 9,1% 9,1% 9,1% 36,4% 100,0% % Label 9,1% 7,7% 10,3% 26,7% 0,0% 13,6% 25,0% 33,3% 30,0% 28,6% 19,5% % Total 0,6% 0,6% 1,8% 2,4% 0,0% 1,8% 1,8% 1,8% 1,8% 7,1% 19,5% year Count % Age 3,3% 6,7% 16,7% 13,3% 6,7% 16,7% 10,0% 0,0% 0,0% 26,7% 100,0% % Label 9,1% 15,4% 17,2% 26,7% 33,3% 22,7% 25,0% 0,0% 0,0% 19,0% 17,8% % Total 0,6% 1,2% 3,0% 2,4% 1,2% 3,0% 1,8% 0,0% 0,0% 4,7% 17,8% year Count % Age 0,0% 11,8% 17,7% 5,9% 0,0% 11,8% 11,8% 5,9% 17,7% 17,7% 100,0% % Label 0,0% 15,4% 10,3% 6,7% 0,0% 9,1% 16,7% 11,1% 30,0% 7,1% 10,1% % Total 0,0% 1,2% 1,8% 0,6% 0,0% 1,2% 1,2% 0,6% 1,8% 1,8% 10,1% year Count % Age 20,0% 0,0% 20,0% 20,0% 0,0% 0,0% 0,0% 0,0% 0,0% 40,0% 100,0% % Label 9,1% 0,0% 3,4% 6,7% 0,0% 0,0% 0,0% 0,0% 0,0% 4,8% 3,0% % Total 0,6% 0,0% 0,6% 0,6% 0,0% 0,0% 0,0% 0,0% 0,0% 1,2% 3,0% 70+ year Count % Age 100,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 100,0% % Label 9,1% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,6% % Total 0,6% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,0% 0,6% Total Count % Age 6,5% 7,8% 17,2% 8,9% 3,6% 13,0% 7,1% 5,3% 5,9% 24,9% 100,0% % Label 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % Total 6,5% 7,8% 17,2% 8,9% 3,6% 13,0% 7,1% 5,3% 5,9% 24,9% 100,0% Table 71: age vs. other elements set

110 Last question Not important Less important How important are the following elements in your choice for a wine? colour style colours of the colour of of the brand shape of used on the background the font font name the label label illustration place of origin grape variety Count % opinion 6,7% 13,3% 3,8% 10,5% 13,3% 6,7% 4,8% 20,0% 21,0% 100,0% % element 5,1% 10,3% 2,9% 8,1% 10,3% 5,1% 3,7% 15,4% 16,2% 8,6% % total 0,6% 1,2% 0,3% 0,9% 1,2% 0,6% 0,4% 1,7% 1,8% 8,6% Count % opinion 8,8% 18,1% 9,9% 11,5% 16,5% 8,2% 5,0% 9,9% 12,1% 100,0% % element 11,8% 24,3% 13,2% 15,4% 22,1% 11,0% 6,7% 13,2% 16,2% 14,9% % total 1,3% 2,7% 1,5% 1,7% 2,5% 1,2% 0,7% 1,5% 1,8% 14,9% Neutral Count % opinion 8,7% 11,9% 9,5% 14,6% 15,0% 11,5% 9,5% 8,7% 10,7% 100,0% % element 16,2% 22,1% 17,6% 27,2% 27,9% 21,3% 17,8% 16,2% 19,9% 20,7% % total 1,8% 2,5% 2,0% 3,0% 3,1% 2,4% 2,0% 1,8% 2,2% 20,7% Important Count % opinion 12,7% 12,4% 15,0% 9,3% 10,9% 14,0% 14,2% 6,5% 5,2% 100,0% % element 36,0% 35,3% 42,6% 26,5% 30,9% 39,7% 40,7% 18,4% 14,7% 31,6% % total 4,0% 3,9% 4,7% 2,9% 3,4% 4,4% 4,5% 2,0% 1,6% 31,6% Very important Count % opinion 14,2% 3,7% 10,8% 10,5% 4,1% 10,5% 14,2% 16,9% 15,2% 100,0% % element 30,9% 8,1% 23,5% 22,8% 8,8% 22,8% 31,1% 36,8% 33,1 24,2% % total 3,4% 0,9% 2,6% 2,5% 1,0% 2,5% 3,4% 4,1% 3,7% 24,2% Total Count % opinion 11,1% 11,1% 11,1% 11,1% 11,1% 11,1% 11,1% 11,1% 11,1% 100,0% % element 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% 100,0% % total 11,1% 11,1% 11,1% 11,1% 11,1% 11,1% 11,1% 11,1% 11,1% 100,0% Table 72: Individual importance of elements Total 110

111 RUNNING HEAD: THESIS JESSICA KOOIJMAN, Interviews Interview questions 1. Wat voor wijn koop je meestal in de supermarkt? (doorvragen over: Lettertype, achtergrond kleur, merknaam) 2. Waar let je op als je voor het wijnschap staat in de supermarkt? (etiketten, schap labels, aanbiedingen, druivensoort, regio) 3. Hoe lang doe je er ongeveer over om een wijn uit te kiezen? (Vooraf al, tijdens de boodschappen, voor jezelf, voor iemand anders) 4. Hoe ziet het etiket van een goede wijn voor jou eruit? Labels Important aspects of labels Unimportant aspects of labels Other influences on the buying process Code book Labels Aspects Explanation Important aspects of labels - Bright coloured label - Gold and yellow accents on the label - Modern styled - For white - Elegant font - Must be easy to read - Black coloured font - Not too many text - Grey font - Darker label - On white wine - Indicates heavy (red) wines - Funny names attract attention - Triggers curiosity to see what it is - Often given as gift with S-A wines Unimportant aspects of labels - Previously bought wines get preference over trying a new wine - Fitting with funny illustration - Recognition of brand name - Recognition of grape - Recognition of place of origin - Label needs to show class - Gives idea of better taste - Information about the wine - Name of the wine - Place of origin - Grape varietal - Year - Classical label - With curly font - For red wines - Crème/beige background - Subtle decorations - Different shape than rectangular - Name that fits with the wine - Relevant illustrations - That fit with the name - That fit with the place of origin - That fit with the grape - No curly fonts - Not too many decorations - Labels filled with decorations and text are not attractive - Not easy to read

112 Other influences of labels Table 73: Codebook interviews - Not only attracted to names - No funny names - No prominent illustrations - of animals - of landscapes - of pink stars - of ribbons - of crowns - Good region is no reason to pay more - Colour of the bottle - Order in the wine aisle - By country - By taste (labels on the shelf) - Eyeheight = best prices - Extra information on the shelves (text by Harold Hammersma) - Not always clear = irritation - Deals get first attention - Read before shopping in the brochure/ - Wine and food pairings is reason for buying wine - Information on the label - Information in the aisle on the shelves or above - Short time in picking a wine - Gifts are bought in wine store - Wines bought per six bottles - Price of the wine is important - Height on shelf - Upper shelves are expensive - Lowest shelves are cheap sweet wines - Middle shelves are best priced - Wines on the middle shelves are easiest to reach - Depends on the occasion - Tips from other people 112

113 RUNNING HEAD: THESIS JESSICA KOOIJMAN, Content analysis Total wines Supermarkets: Total wines counted Total Albert Heijn Jumbo Emté Count % Count % Count % Count % White 97 54,8% 29 16,4% 51 28,8% ,4% Red ,6% 78 33,1% 48 20,3% ,6% Rosé 24 32,9% 28 38,4% 21 28,8% 73 15,0% Total ,5% ,8% ,7% ,0% Table 74: Total wines counted Colour of the background Background colour Total Albert Heijn Jumbo Emté Count % Count % Count % Count % White ,9% ,5% 92 25,4% ,3% See-trough 3 75% 0 0,0% 1 25,0% 4 0,8% Silver 5 100,0% 0 0,0% 0 0,0% 5 1,0% Black 11 55,0% 6 30,0% 3 15,0% 20 4,1% Red 6 75,0% 2 25,0% 0 0,0% 8 1,7% Green 9 81,8% 1 9,1% 1 9,1% 11 2,3% Orange 3 100,0% 0 0,0% 0 0,0% 3 0,6% Blue 3 42,9% 3 42,9% 1 14,3% 7 1,4% Grey 2 50,0% 2 50,0% 0 0,0% 4 0,8% Yellow 2 33,3% 3 50,0% 1 16,7% 6 1,2% Créme/beige 19 38,0% 10 20,0% 21 42,0% 50 10,3% Purple 1 25,0% 3 75,0% 0 0,0% 4 0,8% Gold 1 100,0% 0 0,0% 0 0,0% 1 0,2% Brown 0 0,0% 1 100,0% 0 0,0% 1 0,2% Total ,5% ,8% ,7% ,0% Table 75: Total background colours counted Second background colour Second background colour Total Albert Heijn Jumbo Emté Count % Count % Count % Count % Orange 8 61,5% 2 15,4% 3 23,1% 13 5,3% Pink 2 11,1% 9 50,0% 7 38,9% 18 7,3% Red 29 67,4% 11 25,6% 3 7,0% 43 17,5% Gold 9 45,0% 9 45,0% 2 10,0% 20 8,1% Grey 7 70,0% 1 10,0% 2 20,0% 10 4,1%

114 Green 15 60,0% 3 12,0% 7 28,0% 25 10,2% Black 27 44,3% 19 31,2% 15 24,6% 61 24,8% White 11 91,7% 0 0,0% 1 8,3% 12 4,9% Yellow 3 75,0% 1 25,0% 0 0,0% 4 1,6% Blue 11 50,0% 6 27,3% 5 22,7% 22 8,9% Beige/brown 5 83,3% 1 16,7% 0 0,0% 6 2,4% Purple 3 25,0% 6 50,0% 3 25,0% 12 4,9% Total ,9% 59 24,0% 48 19,5% ,0% Table 76: Total second background colours counted Visual design Visual design individual count Total Albert Heijn Jumbo Emté Count % of image Count % of image Count % of image Count % of total Flower 4 57,1% 2 28,6% 1 14,3% 7 1,8% Leaves 4 66,7% 0 0,0% 2 33,3% 6 1,5% Abstract 23 62,2% 10 27,0% 4 14,8% 37 9,4% Logo 28 43,1% 24 36,9% 13 20,0% 65 16,5% Animal 19 38,8% 24 49,0% 7 14,3% 49 12,4% Ribbon 3 100,0% 0 0,0% 0 0,0% 3 0,8% Grapes 6 28,6% 1 4,8% 14 66,7% 21 5,3% Person 6 33,3% 5 27,8% 7 38,9% 18 4,6% Shield 2 13,3% 3 20,0% 10 66,7% 15 3,8% Wine drops 2 100,0% 0 0,0% 0 0,0% 2 0,5% Estate 3 18,9% 5 31,3% 8 50,0% 16 4,1% Tree 2 100,0% 0 0,0% 0 0,0% 2 0,5% Mountains 19 59,4% 8 25,0% 5 15,6% 32 8,1% House 1 100,0% 0 0,0% 0 0,0% 1 0,3% Vinyard 16 41,0% 6 15,4% 17 43,6% 39 9,9% Map 2 20,0% 8 80,0% 0 0,0% 10 2,5% Tree 13 72,2% 1 5,6% 4 22,2% 18 4,6% Village 1 33,3% 0 0,0% 2 66,7% 3 0,8% Letter 11 40,7% 13 48,2% 3 11,1% 27 6,8% Hands 1 100,0% 0 0,0% 0 0,0% 1 0,3% Mill 1 100,0% 0 0,0% 0 0,0% 1 0,3% Snowflake 1 100,0% 0 0,0% 0 0,0% 1 0,3% Crown 0 0,0% 2 100,0% 0 0,0% 2 0,5% Foot 0 0,0% 2 66,7% 1 33,3% 3 0,8% Sun 0 0,0% 1 16,7% 5 83,3% 6 1,5% Boat(s) 0 0,0% 0 0,0% 4 100,0% 4 1,0% Truffel 0 0,0% 0 0,0% 1 100,0% 1 0,3% Moon 0 0,0% 0 0,0% 3 100,0% 3 0,8% Flag 0 0,0% 0 0,0% 2 100,0% 2 0,5% Total ,5% ,1% ,6% ,0% Table 77: Total visual designs counted 114

115 Summarized visual design Visual design summarized Count % of total Abstract 37 9,4% Logo s 65 16,5% Pictures/illustrations 293 Count % of pictures 74,2% - Plants (flowers, leaves, trees, 55 18,8% 13,9% grapes) - Items 51 17,4% 12,9% - Landscape (estate, vineyard, 93 31,7% 23,5% mountains) - People 18 6,1% 4,6% - Animals 49 16,7% 12,4% - Letter 27 9,2% 6,8% Total ,0% 100,0% Table 78: Summarized visual designs Visual text Verbal text - all Total Wine company Brand name Grape/type Quality Region Wine description Font type Count % font Count % font Count % font Count % font Count % font Count % font Count % of total Italic serif 0 0,0% 25 12,0% 10 4,8% 52 24,9% 25 12,0% 97 46,4% ,8% Italic sans serif 0 0,0% 0 0,0% 0 0,0% 0 0,0% 2 66,7% 1 33,3% 3 0,2% Italic other 0 0,0% 5 55,6% 1 11,1% 0 0,0% 3 33,3% 0 0,0% 9 0,5% Total 0 0,0% 30 13,6% 11 5,0% 52 23,5% 30 13,6% 98 44,3% ,5% Bold serif 13 1,8% ,0% ,9% 90 12,6% ,5% 8 1,1% ,0% Bold sans serif 3 0,5% ,9% ,9% ,0% ,4% 20 3,3% ,2% Bold other 3 6,7% 29 64,4% 0 0,0% 4 8,9% 5 11,1% 4 8,9% 45 2,5% Total 19 1,4% ,1% ,5% ,5% ,3% 32 2,4% ,0% Standard serif 0 0,0% 35 34,0% 26 25,2% 12 11,7% 23 22,3% 7 6,8% 103 5,8% Standard sans serif 0 0,0% 16 25,4% 23 36,5% 7 11,1% 17 27,0% 0 0,0% 63 3,5% Standard other 2 10,0% 15 75,0% 3 15,0% 0 0,0% 0 0,0% 0 0,0% 20 1,1% Total 2 1,1% 66 35,5% 52 28,0% 19 10,2% 40 21,5% 7 3,8% ,5% Total 21 1,2% ,8% ,5% ,1% ,7% 137 7,8% ,0% Table 79: Total visual texts counted per style and type 115

116 Verbal text Albert Heijn Total Wine company Brand name Grape/type Quality Region Wine description Font type Count % font Count % font Count % font Count % font Count % font Count % font Count % of total Italic serif 0 0,0% 8 8,1% 4 4,0% 27 27,3% 11 11,1% 49 49,5% 99 11,4% Italic sans serif 0 0,0% 0 0,0% 0 0,0% 0 0,0% 0 0,0% 1 100,0% 1 0,1% Italic other 0 0,0% 2 100,0% 0 0,0% 0 0,0% 0 0,0% 0 0,0% 2 0,2% Total 0 0,0% 10 9,8% 4 3,9% 27 26,5% 11 10,8% 50 49,0% ,7% Bold serif 13 3,9% ,8% 89 26,7% 37 11,1% 88 26,3% 4 1,2% ,4% Bold sans serif 3 0,9% 75 22,5% ,2% 52 15,6% 89 26,7% 14 4,2% ,4% Bold other 0 0,0% 12 70,6% 0 0,0% 2 11,8% 0 0,0% 3 17,7% 17 2,0% Total 16 2,5% ,7% ,7% 91 13,3% ,8% 21 3,1% ,8% Standard serif 0 0,0% 28 43,1% 15 23,1% 6 9,2% 11 16,9% 5 7,7% 65 7,5% Standard sans serif 0 0,0% 5 45,5% 4 36,4% 2 18,2% 0 0,0% 0 0,0% 11 1,3% Standard other 2 33,3% 3 50,0% 1 16,7% 0 0,0% 0 0,0% 0 0,0% 6 0,7% Total 2 2,4% 36 43,9% 20 24,4% 8 9,8% 11 13,4% 5 6,1% 82 9,4% Total 18 2,1% ,2% ,6% ,5% ,9% 76 8,7% ,0% Table 80: Total visual texts counted per style and type - Albert Heijn Verbal text - Jumbo Total Wine company Brand name Grape/type Quality Region Wine description Font type Count % font Count % font Count % font Count % font Count % font Count % font Count % of total Italic serif 0 0,0% % 4 7,7% 11 21,2% 11 21,2% 18 34,6% 52 10,9% Italic sans serif 0 0,0% 0 0,0% 0 0,0% 0 0,0% 2 100,0% 0 0,0% 2 0,4% Italic other 0 0,0% 3 75,0% 1 25,0% 0 0,0% 0 0,0% 0 0,0% 4 0,8% Total 0 0,0% 11 19,0% 5 8,6% 11 19,0% 13 22,4% 18 31,0% 58 12,1% Bold serif 0 0,0% 59 33,3% 59 33,3% 25 14,1% 33 18,6% 1 0,6% ,9% Bold sans serif 0 0,0% 32 22,1% 37 25,5% 27 18,6% 43 29,7% 6 4,1% ,3% Bold other 3 100,0% 15 57,7% 0 0,0% 2 7,7% 5 19,2% 1 3,9% 26 5,4% Total 3 0,9% ,5% 96 27,6% 54 15,5% 81 23,3% 8 2,3% ,7% Standard serif 0 0,0% 5 22,7% 8 36,4% 2 9,0% 6 27,3% 1 4,6% 22 4,6% Standard sans serif 0 0,0% 9 16,6% 17 37,0% 5 10,9% 15 32,6% 0 0,0% 46 9,6% Standard other 0 0,0% 5 100,0% 0 0,0% 0 0,0% 0 0,0% 0 0,0% 5 1,0% Total 0 0,0% 19 26,0% 25 34,3% 7 9,6% 21 28,8% 1 1,3% 73 15,2% Total 3 0,6% ,4% ,3% 72 15,0% ,0% 27 5,6% ,0% Table 81: Total visual texts counted per style and type - Jumbo 116

117 Verbal text - Emté Total Wine company Brand name Grape/type Quality Region Wine description Font type Count % font Count % font Count % font Count % font Count % font Count % font Count % of total Italic serif 0 0,0% 9 15,5% 2 3,5% 14 24,1% 3 5,2% 30 51,7% 58 13,7% Italic sans serif 0 0,0% 0 0,0% 0 0,0% 0 0,0% 0 0,0% 0 0,0% 0 0,0% Italic other 0 0,0% 0 0,0% 0 0,0% 0 0,0% 3 100,0% 0 0,0% 3 0,7% Total 0 0,0% 9 14,8% 2 3,3% 14 23,0% 6 9,8% 30 49,2% 61 14,5% Bold serif 0 0,0% 66 32,8% 65 32,3% 28 13,9% 39 19,4% 3 1,5% ,6% Bold sans serif 0 0,0% 32 25,2% 37 29,1% 24 18,9% 34 26,8% 0 0,0% ,1% Bold other 0 0,0% 2 100,0% 0 0,0% 0 0,0% 0 0,0% 0 0,0% 2 0,5% Total 0 0,0% ,3% ,9% 52 15,8% 73 22,1% 3 0,9% ,2% Standard serif 0 0,0% 2 12,5% 3 18,8% 4 25,0% 6 37,5% 1 6,3% 16 3,8% Standard sans serif 0 0,0% 2 33,3% 2 33,3% 0 0,0% 2 33,3% 0 0,0% 6 1,4% Standard other 0 0,0% 7 77,8% 2 22,2% 0 0,0% 0 0,0% 0 0,0% 9 2,1% Total 0 0,0% 11 35,8% 7 22,6% 4 12,9% 8 25,8% 1 3,2% 31 7,4% Total 0 0,0% ,4% ,3% 70 16,6% 87 20,6% 34 8,1% ,0% Table 82: Total visual texts counted per style and type - Emté Verbal text - Total types Albert Heijn Jumbo Emté Total Count % type Count % type Count % type Count % total Serif ,6% ,5% ,9% ,9% Sans serif ,5% ,7% ,8% ,0% Other 25 33,8% 35 47,3% 14 18,9% 74 4,1% Total ,1% ,1% ,8% ,0% Table 83: Summarized visual text styles 117