Industrial and Financial Economics Master Thesis No 2005:35. Customer Satisfaction

Industrial and Financial Economics Master Thesis No 2005:35 Customer Satisfaction A case study of customer satisfaction in the Swedish company Mejeribolaget Author: Emil Jornevald

Graduate Business School School of Economics and Commercial Law Göteborg University ISSN 1403-851X Printed by Elanders Novrum

Abstract Since the 70 s the study of customer satisfaction research has risen to become a broad field itself. Customer satisfaction is the main predictor for higher loyalty and retention, issues that are considered to have strong affection on the profitability of a company. Moreover, customer satisfaction is said to be the best tool to measure the success of a company s relationship with its customers. Based on the theory of customer satisfaction and appropriate statistical methods this paper investigates the customer satisfaction in the Swedish company Mejeribolaget and to what extent the customers are satisfied with its products, services and other features and how this can be related to managerial actions. The results from a questionnaire, sent to 1200 respondents with a response rate of approximately 16%, reveal that there are certain areas in the company that can be improved in relation to increasing the overall satisfaction level. However, due to the high unit non-response level, the results are subject to bias and generalizations to the whole population are not possible in a statistical correct manner. Furthermore, input about new issues arises during the analysis which can have affection on the future performance of the company. Key-words: customer satisfaction, product satisfaction, service satisfaction, website satisfaction Page i

LIST OF ATTACHMENTS... VI LIST OF FIGURES... VII LIST OF TABLES... VIII 1. INTRODUCTION... 1 1.1 PURPOSE... 1 1.2 BACKGROUND OF THE RESEARCH PROBLEM COMPANY DESCRIPTION 1 1.3 CURRENT SITUATION AND RESEARCH AREAS... 2 1.4 CONTRIBUTION... 3 1.5 LIMITATIONS... 3 1.6 RESEARCH PROCESS... 4 2. THEORY... 5 2.1 ORIGIN OF CONSUMER RESEARCH... 5 2.2 WHY MEASURE CS?... 5 2.3 CS, LOYALTY AND RETENTION... 7 2.4 CS AND FINANCIAL ASPECTS... 10 2.5 CS IN RELATION TO THE RESEARCH QUESTIONS... 11 2.5.1 CS - Products & Services... 11 2.5.2 CS - Websites... 14 2.6 INTERPRETATION OF CS RESULTS... 15 2.7 SEGMENTATION BASED ON CS... 16 2.8 CONCEPTUAL FRAMEWORK... 17 3. METHOD... 19 3.1 RESEARCH METHODOLOGY... 19 3.1.1 Philosophy of science... 20 3.1.2 Research design... 21 3.1.2.1 Explorative design... 21 3.1.2.2 Descriptive design... 22 3.1.2.3 Causal design... 22 Page ii

3.1.2.4 Summary... 22 3.2 PRIMARY DATA COLLECTION QUESTIONNAIRE... 22 3.2.1 Preparation of the questionnaire... 22 3.2.2 Determine what should be measured... 23 3.2.3 Determine interview method... 23 3.2.4 Determine type of scale... 24 3.2.5 Design and sequence of the questions... 25 3.2.6 Description and explanation of the questions asked... 26 3.2.6.1 Demographics... 26 3.2.6.2 Current Products (seek answers to research question 1) 27 3.2.6.3 New Products (seek answers to research question 2)... 30 3.2.6.4 Website (seek answers to research question 3)... 31 3.2.6.5 Services (seek answers to research question 4)... 32 3.2.6.6 Demographics... 33 3.2.7 Layout of the questionnaire... 33 3.2.8 Pre-testing of the survey... 33 3.3 The sampling process... 34 3.3.1 Definition of the population... 34 3.3.2 Determine sample frame... 34 3.3.3 Sampling method... 34 3.3.4 Sample size... 35 3.3.5 Sample elements and data collection... 36 3.4 RELIABILITY AND VALIDITY... 37 3.5 SOURCE OF ERRORS... 38 3.5.1 Extended non-response error discussion... 40 4. DATA ANALYSIS... 45 4.1 HOMEMADE YOGHURT... 46 4.1.1 Age & Gender... 47 4.1.2 Overall satisfaction... 48 Page iii

4.1.3 Purchase frequency and satisfaction... 48 4.1.4 Satisfaction distribution between genders... 49 4.1.5 Predictors of satisfaction - Homemade Yoghurt segment.. 49 4.2 HEALTH YOGHURT... 51 4.2.1 Age & Gender... 51 4.2.2 Overall satisfaction... 51 4.2.3 Purchase frequency and satisfaction... 52 4.2.4 Gender and Satisfaction... 53 4.2.5 Predictors of satisfaction - Health Yoghurt segment... 53 4.3 SOURDOUGH... 55 4.3.1 Age & Gender... 55 4.3.2 Overall satisfaction... 56 4.3.3 Purchase frequency and satisfaction... 57 4.3.4 Gender and satisfaction... 59 4.3.5 Predictors of satisfaction - Sourdough segment... 59 4.4 NEW PRODUCTS... 60 4.5 COMPANY WEBSITE... 62 4.5.1 Visiting frequency and satisfaction with website features.. 63 4.5.2 Overall satisfaction of the website... 64 4.5.3 Predictors of the website satisfaction... 65 4.6 SATISFACTION WITH SERVICES... 66 4.6.1 Overall satisfaction... 67 4.7 DEMOGRAPHICS... 67 4.7.1 Gender distribution... 67 4.7.2 Age distribution... 68 4.7.3 Occupation... 69 4.7.4 County... 69 4.8 SEGMENTATION... 69 4.8.1 Subscription structure... 69 Page iv

5. DISCUSSION AND CONCLUSION... 71 5.1 SATISFACTION WITH THE HOMEMADE YOGHURT... 71 5.2 SATISFACTION WITH THE HEALTH YOGHURT... 71 5.3 SATISFACTION WITH THE FLAVORS AND CHARACTERISTICS OF THE YOGHURT... 71 5.4 SATISFACTION WITH THE SOURDOUGH... 72 5.5 INTEREST FOR NEW PRODUCTS... 72 5.6 SATISFACTION WITH THE WEBSITE... 73 5.7 SATISFACTION WITH THE SERVICES... 74 5.8 GENERAL DEMOGRAPHICS & SEGMENTATION... 74 5.9 CONCLUDING REMARKS... 75 REFERENCE LIST.... BIBLIOGRAPHY.... Page v

List of attachments Attachment 1 Open textbox questions (In Swedish) Attachment 2 - Questionnaire frequencies Page vi

List of figures Fig 1 The research process Fig 2 Relationship between customer satisfaction & sales Fig 3 Hypothetical satisfaction sample Fig 4 Conceptual framework Fig 5 The research process Fig 6 Sampling method procedure Fig 7 Stratified sample procedure Fig 8 Gender distribution Homemade Yoghurt segment Fig 9 Age distribution Homemade Yoghurt segment Fig 10 Overall customer satisfaction Homemade Yoghurt segment Fig 11 Purchase frequency & satisfaction Homemade Yoghurt segment Fig 12 Age distribution Health Yoghurt segment Fig 13 Overall customer satisfaction Health Yoghurt segment Fig 14 Purchase frequency vs. satisfaction Health Yoghurt segment Fig 15 Yoghurt characteristics Fig 16 Age & gender Sourdough segment Fig 17 Overall customer satisfaction Sourdough segment Fig 18 Purchase frequency & satisfaction Sourdough segment Fig 19 Purchase frequency & baking frequency Sourdough segment Fig 20 Website visiting frequency Fig 21 Overall customer satisfaction website Fig 22 Gender distribution whole population Fig 23 Age distribution whole population Fig 24 Subscription structure Page vii

List of tables Table 1) Population structure in percentage Table 2) Satisfaction vs. Gender Homemade Yoghurt Table 3) Regression summary Homemade Yoghurt Table 4) Predictors of overall satisfaction Homemade Yoghurt Table 5) Satisfaction vs. Gender Health Yoghurt Table 6) Correlation against overall satisfaction for Health Yoghurt Table 7) Satisfaction with flavors Table 8) Satisfaction vs. Gender Sourdough Table 9) Correlation against overall satisfaction for Sourdough Table 10) Level of interest for new products Table 11) Satisfaction with website features Table 12) Interest for new website features Table 13) Regression summary Website Table 14) Predictors of website satisfaction Table 15) Correlation against overall satisfaction for the website Table 16) Satisfaction with services Page viii

1. Introduction The expression the customer is always right have been heard in several consensus. Though the expression is not longer new, the satisfaction of customers is increasingly important. The business climate of today is characterized by a dynamic environment and to be successful and competitive, organizations have to adapt their products and services to the changing needs of customers. Measuring customer satisfaction will provide valuable knowledge to the strategic planning and result in an increased company performance (Deschamps & Nayak, 1995; Sing & Ranchold, 2004). 1.1 Purpose The main objective with this thesis is to examine the customer satisfaction in the Swedish company Mejeribolaget. It is of special interest to explore how satisfied the customers of Mejeribolaget are with the current products and see if there is a demand for new products. Another objective is to study the customer satisfaction with the current services offered and the satisfaction of the company s website. The results from the survey will be analyzed based on statistical methods and current theories within the field of customer satisfaction (hereby CS). Another aspect is to look briefly upon segmentation issues and see if there are clusters that have specific characteristics which perhaps can be used for future segmentation activities. 1.2 Background of the research problem Company description Mejeribolaget is a Swedish mail order company which sells the base ingredients for homemade dairy products and sourdough bread, more specific, the bacterial culture for yoghurt and sourdough. It operates within the business to business (B2B) and business to consumer (B2C) segment, where in this thesis the latter will be in focus. Its current product line in the B2C division consists of three products; Homemade Yoghurt, Health Yoghurt and Sourdough Culture. The company operates in a niche market and has no direct competitors within the mail order business which make it quite unique; however, it indirectly competes with all grocery stores and bakeries that sell yoghurt and bread. In addition, it operates in a society where time is a limited good and homemade food is on a decrease in general (www.sbu.se). At the same time, the increasing importance of health issues; both the nutritional perspective and the increase in Page 1

welfare diseases, such as diabetics and allergies are developments that can indicate a business opportunity for the company. Moreover, as a reaction to the fast paste in society, movements such as slow food has risen and increased the value of homemade as well as the appreciation of genuine products. 1.3 Current situation and research areas Mejeribolaget wants to improve its strategies and take advantage of the possibilities that exists in the market. As mentioned above, trends indicate that the home-cooking is on a general decrease in society and the company s success depends on customers who enjoy making homemade food and who appreciates the nutritional value of it. Thus, the more important it is for the company to get to know its customers thoroughly to find out what they like and dislike in order to better adapt its products, services and website. Mejeribolaget is in a phase where it considers launching new products. Due to the uncertainty involved, there is an inquiry about gaining better insight about its customers in order to minimize the risks. Consequently, it is of interest to find out more about the perceptions of the current product line and to examine if there are any particular products or services that seems to be more or less attractive. Products that are being considered are homemade cheese, homemade souring milk and products with low glychemic index (GI). These are products that goes with the existing product line (dairy products and healthy bread) and that the company believes will sell. In addition to the products, insight in the customers opinions about the services offered, such as opening hours at the customer service, delivery time, and so on are of interest to learn more about since these are areas that affect the overall satisfaction and can be used to improve or change existing procedures. The website is the company s face outward and is, apart from telephone and e- mail, the main interaction between the customers and Mejeribolaget. Thus, the CS with the functionality and design is of interest to learn more about. Finally, segmentation is an issue that is being considered, to see if there are some aspects that can be useful for marketing activities. Page 2

On the basis of Mejeribolaget s current situation the following problem statement arises: How satisfied are Mejeribolaget s customers with the company s products, services and website, and is there a demand for new products? The following research question is meant to seek an answer for the problem statement. Are the customers satisfied with the current products? Is there a demand for new products? Are the customers satisfied with the services offered? Are the customers satisfied with the company website? 1.4 Contribution The contribution of this thesis is to provide Mejeribolaget with new insights about the current customer situation in the company and create a fundamental base for new strategy planning and decision making concerning the development of its products, services and website. 1.5 Limitations The field of market orientation covers apart from CS, several other aspects, such as SWOT and PEST analysis. These analyses, when carried out correctly, provide important information needed for decisions considering product development, segmentation, website development etc. CS will rarely be used as a stand-alone fact when deciding on future development. However, due to the broad extent these factors comprehend they are purposely excluded in this thesis while the focus is narrowed to the measurement of CS. Page 3

1.6 Research process The research process depicted herein will be followed throughout the thesis and in this chapter the first two steps, problem statement and research questions have been undergone. The next chapter considers the research design and data collection. In the final chapters the results will be analyzed and discussed. Fig 1) Research process Problem statement Research questions Design and data need Data collection Data analysis Reporting Source: Gripsrud & Olsson, 2000 Page 4

2. Theory 2.1 Origin of consumer research In the post world war 2 decades, US were the leading country in developing new technologies and high quality products. Over decades of superiority many of the US companies did not pay enough attention to their customers and competitors, which eventually lead to a large loss of market shares to foreign companies. The Japanese were exceptional in listening to their customers and by the mid 70 s US had fallen behind the Japanese in both quality and development aspects. As a result and act in panic a restructuring process took place in the US industry. From this era the field of consumer behavior arose, which were required in order to get back on track in the industry, remain competitive and create a better foundation for managerial decisions (Vavra, 1997). 2.2 Why measure CS? Today customers have more power and information than ever and are in a position where they can demand higher quality and lower prices (Schiffman & Kanuk, 2004). The main objective of most firms is to attain, retain and maintain new customers in order to make profit and generate income. To do so it is necessary for companies to listen to their customers and create value that exceeds the customers expectations (Schiffman & Kanuk, 2004). The most valuable asset in a firm is a loyal customer base and the key to a company s success, concerning its customer relationship, is through measuring CS (Reicheld, 1996; Aaker, 2001). The performance of a company can be measured by using a wide range of methods, such as crude tools considering sales, market share and financial ratios. If the market share is declining it is most likely recognized by the crude tools and actions can be taken for restructuring business operations. However, without knowing what caused the decline it can be tough to set up an action plan. Thus, measuring CS can be an alternative tool which can provide an indication of where the company is headed and used to revise current strategies in order to construct a more suited plan (Aaker, 2001). While the crude tools measures what already has happened, CS can be used in a preventive purpose and detect problems before they occur. Page 5

Companies that manage to develop their products and services subsequent to the demands of their customers are more likely to succeed than those who do not (Aaker, 2001). The customers will feel a closer relation to the company as well as acquiring what they want. Measuring CS also detects the reasons behind, to whom and at what time certain customers have chosen to end the relationship with the company. On the basis of this information cost estimations of lost customers can be conducted and drawn in contrast to what they would have generated in revenue if kept within the company. Furthermore the results can work as a fundament for managerial decisions and future actions. Gurău & Ranchhod (2001) states that the technological dynamics in the market environment has led the focus from being product centric to being customer centric and that understanding the customer is the key to be competitive. Insight about customers needs seem to be vital for the business success and by measuring CS a company can use the collected data to improve products, services and company performance (Schiffman & Kanuk, 2004). The consequences of not listening to the customers can be fatal and according to various researchers, the following facts are common practice: Only 4% of all dissatisfied customers complain The average dissatisfied person eventually tells nine other people Satisfied customers tell five other people about their good experience The cost of acquiring a new customer is usually 5-7 times greater than keeping the existing ones These facts point out that ensuring high satisfaction is vital for long-term business survival and profitability (Vavra, 1997; Bhote, 1996; Hoffman & Bateson, 2001). Many companies measure their level of CS in number of complaints received and try to minimize these in order to increase the satisfaction. According to Fecikova (2004) this is not true satisfaction, rather an indicator of dissatisfaction and an issue, which with no doubt, should be eliminated but not used to measure CS upon. She states that true CS can not be achieved by minimizing number of complaints but by offering high quality products and services, which will leave the customer with a feeling of delight. If a company Page 6

fails to meet the expectations of their customers, they will turn to the competitors or just end the relationship with the company (Anderson et al, 2004). This indicates that it is not enough, to only focus a little on the customer or to do as little as possible in order to handle the CS issue. Bhote (1996) makes quite a point out of this and is frustrated that many companies still believes in CS myths, such as price is the only thing that matters and in the 99% syndrome. The 99% syndrome refers to companies who believe that a 99% satisfaction level is good enough and as long as they reach that level the customers will be happy. Bhote argues lively about this fact and draws a parallel between the human and chimpanzee DNA, stating that it is only 1% difference in the DNA structure between the two. In other words, there is no room for mistakes in a highly competitive environment. Dissatisfied customers will spread the negative word of mouth to his or her friends and family which can be very costly for the company. However, if a dissatisfied customer gets help with the particular problem in a pleasing way, he or she usually become more loyal to the company than those who are not dissatisfied (Sing & Ranchold, 2004). 2.3 CS, loyalty and retention In the following section it will be discussed different thoughts and ideas within the fields of CS, loyalty and retention, with main focus on CS literature. The theory of customer loyalty and retention are fields in their own but interacts and has its root in the CS field, thus the necessity to discuss it here and clear out the differences. Definition of CS If the customer s expectations of product quality, service quality and price are exceeded, a firm will achieve high levels of CS and will create "customer delight." Failure to fulfill customers expectation will result in customer dissatisfaction which in turn can lead to customers stop buying from the firm (Marketing Research Encyclopedia, 2004). Page 7

Definition of Loyalty "A feeling or attitude of devoted attachment and affection; or the act of binding oneself (intellectually or emotionally) to a course of action" (Building brands, 2004). Definition of retention The process of building a relationship with the customers and learn as much as possible about them through surveys, demographics and psychographics. Then utilize this information, tailor strategies and communicate these through direct mail, newsletters, telemarketing etc. (www.dmgroup.com, 2004). Holmberg (2004) argues that the most common explanation for high loyalty is high level of satisfaction but points out that the empirical support is diffuse and that it is not easy to draw a parallel between the two. If you eat at a restaurant and are highly satisfied with the dish you had, that doesn t necessarily mean that you will come back to the same restaurant the next time and become a loyal customer. It can, on the other hand, make you speak positively about the restaurant and recommend it to your friends and family which in turn could lead to more customers visiting the restaurant and through that generate higher revenue. The good word of mouth is said to be the best (and cheapest) marketing activity a firm can rely upon. However, a good one-time experience does not necessarily make you loyal but rather indicates that CS can be good for the business. Holmberg (2004) suggests that in order to explain loyalty as a result of CS you have to identify the type of CS indicator that leads to loyalty and she draws a parallel between love for a product and plain satisfaction for a product. It is necessary to find the indicators that make the customer love the product, then loyalty can easier be linked to CS. In Mejeribolaget s case it can therefore be relevant to find the specific characteristics that the customers enjoy. Schiffman & Kanuk (2004) argues that firms need to focus on getting highly satisfied customers and that this is necessary in order to get higher customer retention and loyal customers. Loyal customers buy more, are not as price sensitive and spread the positive word of mouth. Moreover, loyal customers who are familiar with how the company is run are less expensive to service than the ones who are not (Fecikova, 2004). According to Bhote (1996) a 2% increase in customer retention is equivalent to cutting the operating cost by Page 8

10%, and in times where many companies are cutting costs and lay off workforce, this indicates that retention might be a more profitable action. In other words, keeping customer satisfied and making them want to come back might be as good alternative as cutting costs or even better. Klein & Einstein (2003) 1, states that satisfaction is a measure of what people say, while loyalty is a measure of what they actually do and that measuring CS is measuring an attitude. Attitude is a measure of the most recent transaction with the company and thus not a very accurate measure of whether customers will come back or actually feel the same the next day. On the other hand, they suggest that measuring CS is a good way to let customers vent their feelings and also to find out about problems with products and services. Furthermore, Klein & Einstein (2003) points out that CS is a measure of opinions and therefore not a reliable predictor of future behavior. Instead, they favor loyalty as the predictor for future happenings and actions that the customer will or will not do. In their view, loyalty is not a measure of opinions but rather a measure of commitment which is based on historical facts such as sales data. From this data different consumer patterns can be extracted and used as indicators and predictors, such as defections and revenue lost etc. A loyalty measure embrace the individual more specific rather than the whole population and a tenfold return on investment is not unusual when conducting a loyalty analysis. CS is a temporal measure and thus not static, therefore it is difficult for organizations to base their future strategies on a one time measurement of the market; rather they strive for getting high customer retention and loyal customers since this is proven to increase profits in the company (Vavra, 1997). Continuous measurement of CS will however give an indication of the current situation and over time it will give a clearer picture of how the market and customers perceptions changes. From that, actions can be taken which in turn can lead to increased retention and more loyal customers. Satisfaction, retention 1 Klein & Einstein writes for the strategy+business magazine which is published by the leading global management and technology firm Booz Allen Hamilton. Using all the reporting forms in the editorial arsenal case studies, interviews, scholarly research, journalistic reports, profiles, and first-person accounts s+b delivers penetrating and vital insights and practical guidance about management, innovation, public policy, strategy, and more. Page 9

and loyalty are interconnected and should be taken into consideration when looking at the whole picture. CS might not be an optimal measure to define customer loyalty and retention but it appears to be a valuable tool to obtain indications on what needs to be improved in the business today while loyalty is a better tool to predict future patterns. 2.4 CS and financial aspects Most managers are aware of CS and its importance but perhaps do not always invest enough money and effort in it due to the nature CS constitutes. CS is an intangible measure which makes it more difficult to evaluate and interpret than tangible measures. Consequently, other performance indicators are usually preferred. In order for companies to use CS as a daily motivator to improve performance, it needs to be translated into measurable numbers that easily can be interpreted (Deschamps & Nayak, 1995). Accounting is a central approach to measure company performance and gives valuable insight in a company but cannot substitute the real input and value obtained from direct contact with the customers. However, as long as there is a lack of strong empirical evidence supporting CS as a performance indicator that can improve financial performance, managers will not be interested in adapting it (Anderson et al, 2004). In recent years, there has been quite much research done within this particular area and Anderson et al (2004) refer to various authors and state that many research studies link CS to financial performance, such as operating margin, ROI, accounting returns and that CS reduces the cost of sales, service and communication. According to the Service Management Team (www.servicemanagement.com) the percentage of positive or negative CS move the financial performance in the same direction (see fig 2 next page). Fig 2) Page 10

Relationship Betw een CS and Sales 4,0% 3,0% 3,0% 2,5% 2,0% 1,0% 0,0% -1,0% -2,0% 1,0% 0,7% 1 2 3 4-1,0% -0,9% CS Sales -3,0% -4,0% -3,0% -2,5% CS is an asset which should be taken into consideration when valuating the capital markets and it has such impact on the financial performance that every firm ought to provide a standardized CS index in their financial reporting in order to better inform the capital market (Anderson et al, 2004). Several researchers have concluded that CS influences the performance of a firm and serves as an indicator on how customers perceive the products and services (Lambert, 1998; Smith et al, 2003). Moreover, CS works a base for the development of marketing strategies (Laroche et al, 2004). 2.5 CS in relation to the research questions Mejeribolaget operates in a niche market and is dependent on providing products and services that outperform the regular dairy products in the grocery stores, or being perceived in such way, that its customers decide to use these instead of other alternatives. Having good insight in what the customers think and want, is therefore necessary in order to stay dynamic and profitable. In the following section CS is discussed with a focus on product and service development. 2.5.1 CS - Products & Services According to Aaker (2001) products and services in a company should be carefully and objectively evaluated in relation to its competitors and customers. However, this is not always possible since it might be difficult to be objective toward your own business. There are reasons to believe that the closer you are to your products or services, the less willing you are to see the defects it might Page 11

have. In Sweden the majority of companies are run individually and the closeness to their inventions and products might make it harder to step outside the box and study the organization objectively. Consequently, implementing standard procedures for measuring CS can perhaps work as an evaluation tool and facilitate new ways of input. On the other hand, several companies have direct contact with their customers on a daily basis and obtain, through that, the information needed to focus on their customers preferences. Nonetheless, the importance of knowing your customers still remains, regardless of the chosen approach for taking the pulse of the market. Products The main purpose with measuring CS concerning products is to include the perception of the products in the product development and redesign. Measuring CS takes the pulse of the market and seeks answers and explanations to why or why not customers prefer a product. It is a communication process between the manufacturer and the ones who use the products and it reveals significant facts about the performance in the market (Vavra, 1997). Mejeribolaget is in a phase where it considers launching new products and according to Lehmann & Winer (1997) it is necessary to conduct a customer analysis before the launch takes place. They recommend that companies should study the present usage of the current products in order to determine the customers needs. It is also of importance to measure qualitative and quantitative attitudes towards the products and any perceived importance of certain attributes. In addition, a competitor- and category analysis should be carried out when considering a product launch. A multi-attribute model can be used to understand how and why customers chose a particular product in a company (Lehmann & Winer, 1997). The multiattribute model is built up by assessing certain attributes to the products or the product line. The attributes are decided upon input from collected data from focus groups or from other qualitative data collection methods. The gathering of data is needed in order to find the attributes that are most important for the customers and influences the choice of product. When the attributes have been collected the perception of each attribute can be measured and weighted towards each other in order to obtain an overall picture of the different choices. The perceptions are recommended to be measured on a scale ranking from 1 to 7 where the level of satisfaction of each attribute can be stated. The same Page 12

procedure applies for measuring the importance of the attributes. After this the perception of the attributes and the importance of the attributes are weighted and combined to get a rating score, used for various interpretation and analysis purposes. Multivariate analysis can be used for analyzing multiattribute data while multiple regression analysis can be used when there is a desire to measure the association between a dependent variable and multiple independent variables. The latter will used in the analysis section in this thesis, where it is desired to find relationships between the perception attributes of the products, services and website. Services In contrast to products, services constitute a more intangible nature which means that service quality can not be decided based on physical aspects. The quality is more or less determined by the customers perception of the service (Lehmann & Winer, 1997). Mejeribolaget handles their Customer Service through phone, the website, email or regular mail. It is therefore of interest to measure the perceptions of the services provided to the customers in order to examine areas that could be improved. There exist several methods for measuring service quality, whereas the Servqual (service quality) method is the most known and used (Parasuraman et al, 1985). The Servqual scale is a multiple-item scale that measures quality based on five service quality dimensions in a survey-format. Each dimension includes several questions or statements which have to be answered using a seven-point scale, stretching from strongly disagree to strongly agree. There has been extensive research around the key attributes that lead to service quality. As a result the Servqual approach is now a standardized method of measuring service quality as the difference between the performance that is expected by customers and the delivered performance. The five key dimensions of Servqual are described on the next page to give an insight in what factors that are considered when measuring service quality. Page 13

Tangibility The appearance of physical facilities, equipment, personnel and communication material. Reliability The ability to perform the promised service dependably and accurately. Responsiveness Willingness to help consumers and provide prompt service. Assurance Competence: Possession of the skill and knowledge to perform the service. Courtesy: Politeness, respect, consideration and friendliness of contact staff. Credibility: Trustworthiness, believability and honesty of staff. Security: Freedom from danger, risk or doubt. Empathy Access: Approachability and ease of contact. Communication: Keeping consumers informed in language they understand and listening to them. Understanding the consumer: Making the effort to know the consumer and their needs. As it can be seen, the Servqual method is a survey based method that measures the perceptions of service quality in a very detailed way. Some of these dimensions will be investigated in this thesis but not to the same extent as the full Servqual method. However, if the results from the empirical findings reveal that the level of service satisfaction is not high enough, the Servqual method could be applied in order to acquire a more precise measure and reveal specific information that can be used for revising current strategies. 2.5.2 CS - Websites Today most businesses profile themselves online, including Mejeribolaget and it is therefore of interest to learn more about how the customers perceive the website and its features. The cost of developing a website can be high and it is therefore important to measure the satisfaction with the current website to obtain an enhanced fundament for further development of the website and to target activities more efficiently (Hedman & Pappinen, 1999; Kauffman & Hahn, 2003). The importance of CS applies for websites as well and it comes down to keeping the customers satisfied in order to create retention and improve loyalty. However, there are other dimensions that have to be taken into consideration when measuring the satisfaction of websites. In brief these are; safety of transactions, speed of loading pages, content, frequency of redesign and so on. Various researches suggest that a website layout should be as simple Page 14

and direct as possible without superfluous features. There are different methods suggested for measuring the efficiency of a website but none that is yet generally widespread and accepted. Some methods measure website efficiency through CS, other through service quality, while yet another through measuring the website as a production environment using a data envelopment approach (Kauffman & Hahn, 2003). Due to the research problem of this thesis, a CS approach of measuring website efficiency is preferred since it considers the customers perceptions of the website. 2.6 Interpretation of CS results According to Lehmann & Winer (1997) a survey analysis is useful when there is a wish to generalize the findings upon the whole population. The Likert scale is one of the most common used scales when measuring CS and it is normally divided into five steps ranking from very dissatisfied to very satisfied (Schiffman & Kanuk, 2004). When interpreting the results several aspects must be considered but it is commonly agreed that customers who scores at the highest point (very satisfied) are more loyal and thus generate more income than customers who score at a lower satisfaction levels (Schiffman & Kanuk, 2004; Fecikova, 2004). Bhote (1996) draws a hypothetical example and describes a situation where a company has conducted a CS survey among its customers. The results indicate that most of their customers are satisfied (scores at 6) with the company and the managers at the hypothetical company are very pleased with the results. Fig 3) Hypothetical satisfaction sample Customer Satisfaction # of respondents 60 40 20 0 1 2 3 4 5 6 7 Serie1 Degree of satisfaction (Scoring at 1=very dissatisfied while scoring on 7=very satisfied) However, when provided with additional information about the satisfaction score the managers become really stressed. An additional question asked to the Page 15

satisfied customer segment (score on level 6) reveals that only 70% would return to the company next time they were in need of the same product, while 98% in the very satisfied segment (level 7) said they would come back and buy again. From this example, Bhote (1996) highlights that it is the very satisfied segment that is critical and that it is in this segment the most loyal customers are. For this CS survey it appears to be a good idea to keep in mind that the highest score on the Likert scale is the most important for the company while scores on lower levels should set of the alarm bell, especially if it constitutes the main part of the respondents. 2.7 Segmentation based on CS Segmentation divides the population into smaller clusters where one tries to sort the clusters after homogeneity in various aspects. No customer is the other alike; however, there usually are some characteristics of the population that can be clustered. The purpose of segmentation is to treat customers according to their needs, wishes and level of profitability they generate (Yüksel & Yüksel, 2002). Consequently, it is easier to satisfy the customers when there are clear indications of who wants what and why. When companies invest in their operating activities, the main objective usually is to generate more money than the cost of the investment. For firms with scarce financial and staff resources it is vital that their investments return at least the break even point. In order to reduce the uncertainty of various investments, segmentation becomes an important issue. Companies that have a clear overview of which segments that generate most respectively least revenue can adjust their financing activities thereafter and reduce the risk and rely less on the trial & error method (Yüksel & Yüksel, 2002). According to Fecikova (2004) it usually is a small percentage of the customer base that generate most of the profits to the firm and that it is a competitive advantage to segment the customers. A well know rule, heard in many consensus, is the 20/80 rule which states that 20% of your customers generate 80% of the company revenue. This rule is widely used in many different settings but its importance still remain; it is necessary to find the characteristics of the customers and arrange these in such a way that it can be used strategically to improve the overall company performance. Page 16

It is of interest for Mejeribolaget to learn more about the segmentation issues. However, it is beyond the boundaries of this thesis to conduct a full segmentation analysis but the issue will be briefly discussed in the analysis to see if there are some obvious characteristics that can be used for segmentation purposes. 2.8 Conceptual framework From the theoretical background it can be found that measuring CS is vital for the success of a company and that it is applicable to products, services and websites. High level of CS seems to generate higher profits and better chances for retention and loyalty. With this in mind the model on the next page is set up and explained as follows: Mejeribolaget wish to learn more about its customers and on the background of the CS theory it is found that CS influences company performance. Thus it is necessary to measure how the current customer base perceives Mejeribolaget s products, services and website. In order to measure the CS on each category respectively, a survey was designed and conducted to specifically deal with these three directions (this part is described in the methodology in the next chapter). Based upon the analysis of the results from the survey there will be a discussion of the findings and finally a conclusion will be drawn. Page 17

Fig 4) Conceptual framework model Background Theory What do they think about the company? Customer Base Design Survey Products Services Website Analyze Result General guidelines differentiate, develop and improve products, services and Homepage Page 18

3. Method 3.1 Research methodology The theory on CS strongly indicates that high CS is related to higher sales and more frequent purchases. However, the theory itself is not enough for answering the problem statement but gives a clear insight in what might affect it. Hence, it is necessary to conduct a relatively large primary research where both a descriptive and an explorative design is combined, whereas the research design is based upon consumer- and marketing research. In order to give an answer to the problem statement it is necessary to collect accurate data and to choose the appropriate analysis method. The chosen analysis method should be based on the type of data collected, which in this case are metric data and some qualitative elements. Descriptive statistics and multiple regressions are used to find relationships and connections within the population. Below, the following two steps in the research process will be undergone; design and data and data collection. Fig 5) Research process Problem statement Research questions Design and data Data collection Data analysis Reporting Page 19

3.1.1 Philosophy of science Consumer research describes the processes and tools used to study consumer behavior and the norms of how one should approach in order to retain reliable results. There are mainly two dominant philosophy directions when performing research on a social phenomenon; the positivist approach and the interpretivist approach (Hellevik, 1995). The positivist approach puts emphasize on objectivity, empirical studies and seeks causes to explain behavior. The research has to include larger populations and should be based upon accurate measurements, quantifiable data and statistical analysis because a fact that is not observable is seen as metaphysics (the philosophical study of being and knowing) by the positivists (Grennes, 2001). The positivists often use the statement If you can t count it, it doesn t count The origin for the positivist approach were that all knowledge that could be derived from experience also could be accepted as scientific and that the main objective within the philosophy of science were to clear away all tendencies of metaphysical speculations within scientific research. Thus, they did not accept the theory, stating that the scientific, humanistic, social science methods and methods for scientific work were equivalent. The positivists differ rationally between the researcher as a researcher and the researcher as a citizen. Their fundamental idea is that the research process should be separated from any public or social interest (Grennes, 2001). According to this view; studies that are based upon qualitative data (even the very best) only are good enough for preparing a quantitative research (Holter & Kalleberg, 1996). The other approach for consumer research is the interpretivist approach, which is qualitative and based on small samples of the population where each consumption pattern is unique and where the focus is to find patterns leading to operative values (Schiffman & Kanuk, 2004). While the positivists are concerned about how something actually is, the interpretivists try to explain how the world around them is perceived by the population. In other words, the interpretivist try to explain how these things actually appears and not how it actually is. Their fundamental basis is that social conditions are not irrelevant only because they cannot be associated and interpreted by numbers (Grennes, 2001). They rhetorically answer the positivists expression If you can count it, it doesn t count with It is not only the things that can be counted that counts Page 20

(Holter & Kalleberg, 1996). The main difference between the positivists and the interpretivists is the objectivity in relation to the research process. The positivists suggests that it is possible for the researcher to relate to a situation strictly objectively without being influenced by it, while the interpretivists oppose this, stating that the researcher s subjective references never can be completely excluded resulting in the impossibility of totally objective research methods (Grennes, 2001). Nowadays, most researchers are not so narrowed in their view and the term qualitative and quantitative refers to the nature of the collected data where both usually are integrated in the research process (Holter & Kalleberg, 1996). In this thesis both approaches were combined in a web questionnaire and the main purpose of the asked questions was to collect quantitative data. Furthermore, some qualitative data was also desired and therefore the respondents had the possibility to fill in their own subjective information in open text boxes (attachment 1). Drawn in big terms, quantitative data is characterized by pure numbers or quantity terms, such as many/few, more/less, etc, while data that cannot be expressed in such way are qualitative (Holter & Kalleberg, 1996). 3.1.2 Research design A research design is the main frame of the research and is determined by the character of the problem statement. There are three types of design and depending of which one chosen, certain techniques and methods can be applied for the research process (Selnes, 1994). 3.1.2.1 Explorative design Explorative design is used when the character of the problem is of such art that it is desired to get a deeper insight or understanding of a phenomenon (Selnes, 1994). An explorative design has various qualitative methods of collecting data, such as interviews, focus groups, projective techniques and case studies. These methods are preferred when the researcher Needs deep knowledge that cannot be expressed in numbers and are limited to few research objects Have little knowledge about a social phenomenon Wants deeper knowledge about a phenomenon where it already exists comprehensive statistical data Want to see if there are new or changed explanations in areas where good knowledge already exists (Selnes, 1994). Page 21

3.1.2.2 Descriptive design If the purpose with the research is to map one or many variables and/or explain the relationship between them, a descriptive design is usually preferred (Selnes, 1994). A questionnaire is a preferred method for collecting data in a descriptive design and in order to shed light on the problem statement it is important to focus on certain facts, break it down to numbers and then measure the observations. Descriptive design uses quantitative data and are used when the researcher; Wants knowledge that can be generalized to many units Wants knowledge that can constitute a fundamental base for statistical calculations (Gripsrud & Olsson, 1999) 3.1.2.3 Causal design In order to research causal connections causal design is often used and which is conducted by experiment in the field or in a laboratory. Of the three mentioned designs, the causal design is used the least (Gripsrud & Olsson, 1999). 3.1.2.4 Summary In this thesis it was desired to get information that made statistical calculations possible and that the information could be generalized in order to get a clearer picture of the whole population (the customers of Mejeribolaget). In addition, it was of interest to obtain additional information that could shed new light on the problem statement. With the theoretical background in the consumer and marketing research field, a survey collection method was chosen with a descriptive research design including some elements of explorative design. 3.2 Primary data collection Questionnaire It is a common practice in marketing research to use questionnaires when collecting data. It is a convenient tool to use and it makes the communication between the interviewer and the respondent standardized (Gripsrud & Olsson, 2000). It is though, many aspects that has to be considered before using a questionnaire as a method and herein it will be explained how the questionnaire was built up through various criteria and factors. 3.2.1 Preparation of the questionnaire The operations involved in the preparation of a questionnaire usually consist of six steps (Gripsrud & Olsson, 1999; Selnes, 1994). However, in this thesis an Page 22

additional step was added Description and explanation of the questions asked making it 7 steps. This was added to achieve a better structure and deeper understanding of the questions asked. 1) Determine what should be measured 2) Determine interview method 3) Determine scale 4) Design and sequence of the questions 5) Description and explanation of the questions asked 6) Layout of the questionnaire 7) Pre-testing 3.2.2 Determine what should be measured One of the most important facts within the field of market orientation is to find what information that needs to be collected in order to solve the problem statement. To cover the problem statement it is common to divide it into smaller research questions which make it more convenient to base the questions in the survey upon (Selnes, 1994). 3.2.3 Determine interview method There are various methods for collecting primary data and within the questionnaire research there are mainly three ways of collecting data; through personal interviews, postal interviews or telephone interviews. Each of these methods has its advantages and disadvantages considering time, money and suitability and are related to which research design that is used. A descriptive design was used in this thesis and it was decided to use a postal interview method based on the following reasons: It is rather low cost involved compared to the other alternatives Complex and thoroughly questions can be asked and the respondents have time to think through the questions before answering and are more amenable to answer sensitive questions. Since the main objective is to measure the customers perceptions, a very sensitive issue, this method was considered to be the most appropriate one. One should however, be aware of the following facts about postal interviews: It can take a long time to conduct It is difficult to be sure that the right respondent answers it Page 23

There is no real-time guidance if there are uncertainties about how to answer certain questions or other general issues considering the questionnaire. There is usually a low response rate (Gripsrud & Olsson, 2000) A postal interview can either be conducted by regular post or electronic post. In this case the latter was used and the data collection was conducted through a web questionnaire. The respondents were notified by post and then instructed to go online and answer the questionnaire via Internet. The normal response rate of a postal survey is around 10-15% (Gripsrud & Olsson, 2000) and in order to make sure that at least this percentage was achieved and possible a higher level, a lottery contest with prices were proclaimed in connection with the survey. 3.2.4 Determine type of scale A survey usually tries to grasp various aspects of a situation and often includes different elements, such as facts, attitudes, perceptions etc. Measuring CS is the main purpose of this thesis and with an intangible, such as CS, it is necessary to use a scale which makes the transformation into metric data possible. According to Gripsrud & Olsson (2000) you have to use metric data in order to be able to say anything about the distance between the separate values of the variables and to do statistical calculations. One usually differs between two types of scales; non-comparative and comparative scales. The non-comparative scale allow the respondents to evaluate the specific situation independently of the other objects in the study and to generate absolute results, while the comparative scale allow the respondents to compare one alternative over another such as; do you prefer this over that, is this product better than that and so on (www.marketingpower.com). In addition, one differs between single-item or multi-item scales whereas the latter is used for measuring different aspects of a situation/phenomenon (Gripsrud & Olsson, 2000). Multi-item scales are combined single-item scales and the two most common of these are the Likert scale and the semantic differential scale. The Likert scale is used for measuring perceptions, attitudes etc. and it was decided to use a non-comparative direction with a seven-point Likert scale since it stretches further than the five-point, including the very dissatisfied at the one end to the very satisfied at the other end. Page 24

3.2.5 Design and sequence of the questions As a general rule surveys should be easy and short so that the respondents will not let be to answer it. Due to this fact, the survey consisted of 33 questions that where put in such sequence that if the respondent answered yes respectively no on certain questions they automatically skipped the underlying questions which made the questionnaire more convenient to use and to answer. According to Gripsrud & Olsson (2000) single respondents can feel that the specified answers in a survey not always covers the subject good enough and therefore skip the question or certain areas. It was of interest to collect information from those respondents that had additional information and open text box questions were added to the survey (attachment 1). How the questions are formulated, set up and presented affects how the respondents perceive and answer the survey. Research has shown that if a question is formulated in a negative way the respondents attitudes toward that specific issue also become more negative than it would have been otherwise, while it is the other way around when the question is formulated in a positive way (Gripsrud & Olsson, 1999). Consequently, the language were considered very important and the questions were formulated to leave as little room for misinterpretations as possible and set up to be as easy understandable as possible for the respondents. The sequence was built up to have a natural connection and to answering the research questions. The questionnaire started with some demographic data followed by product specific data within the yoghurt segment, Sourdough segment, website, services, and was finally rounded off with some more demographical questions. Demographics Current Products research question 1 New Products research question 2 Website research question 3 Services research question 4 Demographics From the respondent s viewpoint the sequence of the questions varied depending on how he or she answered. For example, if the respondent answered no on one question he or she were not shown the underlying Page 25

questions for the yes alternative and were automatically skipped to the next section in the survey. If the respondent used all products and answered yes on all questions he or she would have had to answer all the 33 questions. However, it was more common that they used one or a few products, thus did not have to answer all of them. The reason for setting up the survey in this way was to get as accurate answers as possible and to make the survey appear as short as possible. Normally, it is common to put the demographical data at the very end of a survey since the respondent usually is less focused at the end and it is easier to answer such questions instead of the ones which you need to think a lot around before answering (Gripsrud & Olsson, 2000). However, since the questionnaire was conducted over the Internet some demographics were put in the very beginning so that the respondent would get a feeling for how the online questionnaire worked before the more concrete questions appeared. 3.2.6 Description and explanation of the questions asked In this section a description of the questions asked is undergone and follows the same structure as depicted on the previous page. It especially considers why these questions can be useful for the company and how they relate to the problem statement and the research questions. The phrase to what degree/extent How important etc will be used in the explanation below and refers to what extent the respondents like or dislike a statement in a specific question, using the Likert scale ranging from 1-7 where 1 is the lowest and 7 is the highest (very dissatisfied/very satisfied, little important/very important, low degree/high degree etc.). 3.2.6.1 Demographics Please state gender Useful to see the spread in the population and to test if there are significant relationships between the gender and level of satisfaction Please state age Can be used in testing the relationship between age and level of satisfaction. To see the spread in the population, can be used for segmentation activities Page 26

How did you get in contact with Mejeribolaget? Can be useful for finding which channel that has attracted the most satisfied customers and target the marketing activities toward these. (This question doesn t fit any particular category in the survey but makes a natural fit here) 3.2.6.2 Current Products (seek answers to research question 1) The product line consists of three different products, Homemade Yoghurt, Health Yoghurt and Sourdough Culture. The questions asked for the Homemade Yoghurt and Health Yoghurt is similar and will therefore be explained at the same time. It did not; however, appear this way in the questionnaire. If the respondent, for example, only marked Homemade Yoghurt he or she were shown questions only concerning this product. Homemade Yoghurt & Health Yoghurt Do you use any of the following products from Mejeribolaget today? Used to see the distribution of products in the sample population, also to guide the respondents to the right stage in the questionnaire. Depending on which products the respondent used, he/she was automatically directed to the right part of the survey. How often do you order Homemade/Health Yoghurt? Interesting to see the purchase frequency and also to be able to test the level of satisfaction against amount purchased and to see if there is a relation To what degree are you satisfied or dissatisfied with Mejeribolaget s Homemade/Health Yoghurt? This is really one of the main questions in answering the problem statement since it directly asks the level of satisfaction of the specific product. Can be used in the regression analysis for testing variables that might explain the satisfaction. To what degree are you satisfied or dissatisfied with the following characteristics? (Considers the consistence and the acidity of the yoghurt) A good indicator to see if the products need improvement Page 27

How satisfied or dissatisfied are you with the following of Mejeribolaget s flavors? Indicates how the current flavors are being perceived and if there are any flavor that needs to be taken away or improved. Can be tested against the overall satisfaction of the product and see if the flavors influence it. Do you use your own flavors when you make your yoghurt? Interesting in relation to the question above. If there is a general dissatisfaction of the current flavors and in addition a high level of customers who uses their own flavors it can strengthen the theory that something might be improved and the other way around. Which flavors do you usually use? (If yes on the above question) Can work as a guide if it becomes relevant to produce new or additional flavors Sourdough Culture Do you use Mejeribolaget s Sourdough Culture today? Used to see the distribution of products in the sample population. How often do you order Mejeribolaget s Sourdough? Interesting to see the purchase frequency and also to be able to test the level of satisfaction against amount purchased and to see if there is a relation. Moreover, it can be used for economical cost estimations. To what degree are you satisfied or dissatisfied with Mejeribolaget s Sourdough? Also one of the most fundamental and important questions in the survey, due to the direct relation to the problem statement. Can be used in the regression analysis for testing variables that might explain the level of satisfaction. How often to you bake bread? Gives indications of the frequency of bread baking in general in the population and can be used for evaluating the recipe collection and if there is a market for more recipes. Can also be compared to the purchase frequency and see if there is room for more sales. Page 28

How often do you bake the following bread? (A list of different bread choices were shown to the respondents) (is in relation to the above question) Makes it possible to extract the type of bread that the respondents actually prefer to bake and can be used in connection of developing new and more targeted recipes. In addition, it might reveal whether the respondents are concerned with health issues. If the level of white bread are high, it might be an indication that the respondent are not too concerned about the health aspect, while high interest for dark bread might be an indication for interest in health aspects. Also an issue that might affect the satisfaction in the end. How satisfied or dissatisfied are you with the following of Mejeribolaget s bread recipes? (This category is divided into, dark bread, white bread and special bread) The recipes are a in near relation with the Sourdough concept and a good and satisfactory assortment is assumed to affect the frequency and interest in ordering and baking bread with Sourdough, thus this question reveals the customers thoughts and perception on it and can be used to modify, add, take away certain recipes or find which category that is most appreciated. In addition, the answers from this question can be crosschecked with the question concerning what type of bread the respondents prefer to bake and see if they are consistent in their choices. Do you have any ideas/comments about Mejeribolaget s bread recipes that you would like to add? This is the first open textbox question in the survey and was put there in order to get qualitative data on the field that can be used to get a deeper understanding for the whole bread concept and shed new light on the issue and reveal things that is out of the frame of the pre-determined questions. The open textbox results will not be the main focus in the analysis but might be mentioned if there are some returning issues that seems to be important. Page 29

To what extent do the following factors influence your choice of making Homemade Yoghurt/Health Yoghurt/Sourdough? (A list of seven facts were listed, such as: taste, economy, healthiness etc.) Used to get a out of the box perspective and give insights on what drives the interest of doing Homemade food, a very important issue for understanding the customers and can be used to target the marketing more specifically in the future which in turn can lead to higher satisfaction. 3.2.6.3 New Products (seek answers to research question 2) Would it been of interest with a larger product line at Mejeribolaget? (Only yes or no shown) Will reveal the interest of getting a larger product line and is linked to more thoroughly questions on the field if answering yes. Can reveal issues about the satisfaction, if there is a high wish for more products this can be checked against level of satisfaction of the product line and thus work as fundamental for future decisions. If Mejeribolaget extend their product line what to you prefer most? (Here is five different alternatives shown for the respondent) Is used to find which is preferred; new products or extensions on the current line. This question can be checked with the less satisfied customers and see if there is a correlation between low satisfaction and different wishes/orientations about new product. To what extent do the following products attract/interest you? (Here a list of 11 different products were shown) Used to reveal the interest for certain products and categories, set up in relation to potential new products that could be distributed via Mejeribolaget and to see if there is some kind of characteristics that can be extracted. Are there any specific products that you would like to see distributed via Mejeribolaget? This is the second open textbox question in the survey and put here to get a deeper insight about the respondents own opinions if they had something to add and useful for the management in Mejeribolaget to interpret when/if deciding upon new products or removal of existing Page 30

ones. Cannot be calculated in a statistical manner but be used as a qualitative input. In addition, all the open textbox questions can be used in future set-up of questionnaires and research since it includes the customers thoughts and are not only limited to the company s and the researcher s preferences. 3.2.6.4 Website (seek answers to research question 3) The third research question considers the company website and is important since it is the main interface for Mejeribolaget s customers. There are no physical stores they can go to within Mejeribolaget and thus it is the only interaction the customer s get except from telephone and e-mail. This could probably go under the service concept but were chosen to be put in a separate category and studied more thoroughly. Have you visited Mejeribolaget s website before? (Yes or no only) To get an overview of how many that has been there. How often do you visit Mejeribolaget s website (only if yes) Used to find the mean frequency of visits and can be used to decide how appropriate the website is as a sales channel considering frequency and probability of sales. Can be related to how the customers got in contact with Mejeribolaget, and see which distribution channel is best when targeting marketing activities. Seen to the problem statement; if satisfaction on the website is low, is it related to visit frequency? Please state to what extent you are satisfied or dissatisfied with the following aspects concerning Mejeribolaget s website? (Here current basics features of the website is shown) Used to get better insight in the specific features and to see which features that are appreciated and not. Can be directly related to the overall satisfaction of the website and actions can be taken to reconstruct the website in such way that it suits the customers better. To what extent would it have been interesting to have the following features on Mejeribolaget s website? Used to test pre-determined features that have been considered for implementation on the website. If found high interest for, it can be used Page 31

to reconstruct the website and perhaps increase the level of satisfaction for the website. Are there some content or feature that you feel are missing at Mejeribolaget s website? This is the third open-textbox question and is used to see if there are issues that not have been considered in the pre-determined questions above. A qualitative input that can be valuable when brainstorming about new features, changes and other things. In addition, a way for the respondent to comment their own ideas, thus increasing the interest for the survey. 3.2.6.5 Services (seek answers to research question 4) This area is somewhat brief and not going to deep into the specifics but still gives valuable information for the problem statement and was put somewhat shorter due to the overall length of the survey. Too long surveys decrease the respondents rate of interest and thereby the quality of the answers. Please state to what extent you are satisfied or dissatisfied with the following of Mejeribolaget s services. (Here the following questions were asked, opening hours at customer service, customer service, delivery times, product line, website, and payment method) The final of the very most important questions in relation to the problem statement. Here the respondent gives their opinion on overall satisfaction of two of the more thoroughly undergone fields, products and website and on the main services. By using the satisfaction level of these different categories, it can be tested upon various aspects and relations between them. Do you have any comments in general about Mejeribolaget that you would like to add? This is the fourth and final open textbox question and is used to see if there is anything else that the respondent wants to comment. Together with the three other open textbox questions they constitute a qualitative base for designing new questionnaires in the future and as an overview that stretches beyond the boundaries of this questionnaire. Page 32

3.2.6.6 Demographics Civil status (here the respondent are asked about their civil status and whether they have any children who at the present time live at home, multiple answers possible) Rounding off questions to let the respondent know that the survey is almost done. Also interesting from a marketing perspective where it can be possible to see the most common family situation within the customers of Mejeribolaget Please state your county The final question, used to get an overview and possibility to segment the population and also see if there are any particular places in Sweden that seems to have more satisfied customers than others. 3.2.7 Layout of the questionnaire The questionnaire was, as mentioned earlier, conducted and developed through Questback (www.questback.com). The reason for using this program was that it was free of use for a certain period, it has a good reputation in the market and the organization behind cooperates with over 450 industries that use their program. Moreover, the design is simple, professional and user-friendly. In the beginning of the questionnaire it was put an instruction that described why the survey was conducted, the process of how to answer the questions and an explanation of the usage of the respondents e-mail address. The e-mail address was needed in order to get unique id numbers for each respondent and to be able to separate them in the analysis. The respondents were, however, informed that the use of their e-mail was their lottery ticket for the contest and contact-id in case of a win. The e-mail address was mandatory and it was not possible to skip this question. The other questions could also be set to be mandatory but since this can be very frustrating if you don t know the answer or do not want to answer there is a risk that the respondent just leave the survey. 3.2.8 Pre-testing of the survey Pre-testing of the survey was not conducted in a large dimension, however it was revised certain times through brainstorming with the owner of the company and by input from Ph.D. Björn Lantz, senior lecturer at the department of business administration at Gothenburg University. In addition to Page 33

this, it was run a pre-test online in order to determine the time it would take to answer the survey and it was set to 5-10 minutes depending of products used in the company and personal ability to conduct it. 3.3 The sampling process When conducting a survey it is necessary to have some kind of sample of the population or the whole population itself (which often is not possible due to the size). Consequently, there are different ways to extract a sample from the population, which also depends on the objective with the survey. Herein is the sampling process depicted (Gripsrud & Olsson, 2000) and will explained more thoroughly in the coming sections. 1) Definition of the population 2) Determine sample frame 3) Sampling method 4) Sample size 5) Sample elements and data collection 3.3.1 Definition of the population The population in this context was defined as all the customers of Mejeribolaget, because it was of interest to get a general picture of what the population thought about the company. It would however, been too costly both in time and money to include the whole population in the study; therefore the questionnaire was based on a sample of the population. 3.3.2 Determine sample frame The sample frame lists the elements that are included in the population and its main purpose is to get a sample that is as similar as the whole population as possible. This seldom occurs in practice but the aim should always be to reach that (Selnes, 1994). Updated lists of the customer base with active customers were used in order to determine the sample and the exact procedure will be explained hereunder. 3.3.3 Sampling method In order to be able to generalize the whole population based upon the findings, it is necessary to use a probability sample (Schiffman & Kanuk, 2004). The criterion for a probability sample is that it should in advance be possible to decide how probable it is that each element is drawn and that the probability of doing so is greater than zero (Gripsrud & Olsson, 2000). There are two Page 34

directions in the sampling procedure and below is depicted a chart of which direction is chosen in this thesis (cursive, bold and arrows). Fig 6) Population Nonprobability Sample Probability Sample Convenience sample Simple random sample Judgment sample Systematic random sample Quota sample Stratified random sample Cluster sample A stratified random sample was used and within this, three different strata (subpopulations) were extracted. Stratified random samples are characterized by dividing the whole population into exclusively covered strata and then use simple random selection within each to get a representative sample. Stratified sampling techniques are generally used when the population is heterogeneous where certain homogeneous or similar groups can be isolated (strata). In addition, as mentioned previously, a probability sample is needed in order to be able to calculate statistical relations and since the purpose is to measure the CS and find variables that explain it, this type of sampling technique was chosen. In section 3.3.5 a thorough description of the stratified random sample procedure is undergone. 3.3.4 Sample size When deciding upon sample size there are various factors to consider and the main ones are discussed in this section. The resources for conducting the survey was at the beginning somewhat scarce, especially in relation to money but the company under investigation paid the postal fees of getting in contact with the respondents, the copy material and contest prices, all which made it possible to conduct a relatively large primary research. Page 35

It is a rule of thumb to have approximately 100 observations within each main group that are being analyzed, while 20-50 is appropriate when breaking it down to smaller clusters (Gripsrud & Olsson, 1999). There are three different products offered at Mejeribolaget and for each product it is an individually subscription, no matter if you order one or many products. Consequently, it made it convenient to divide the population after type of subscription, which covers the whole population. However, this doesn t exclude the fact that some customers actually subscribes to more than one product but the subscription procedure is set this way so it was decided that this was the most convenient option for extracting a representative sample. The grouping after type of subscription is not the main interest for the analysis but rather a way to generate a sample that is recognizable for the whole population and that can be used for smaller analysis concerning various aspects. Due to this fact, it was considered to be enough with 200-250 answers to base the analysis upon and with an expected response rate of 15-20% the number 1200 hundred was set to cover the needed size. 3.3.5 Sample elements and data collection A web questionnaire was used to collect the data and to get a statistical representative sample; probability sampling was used with a stratified random sample. A list from the company database was used to divide all active customers after type of subscription, which counted to three groupings, covering the whole population. The total percentage each group constituted were then calculated in the following way: Total number of subscribers in each specific group / total number of subscribers. The percentages from each group were then multiplied with the number of respondents who were to be in the survey, namely 1200 (see fig below). Due to the integrity of the company, total numbers of customers is not revealed. Instead, the classification is shown in percentage. Table 1) Population structure in percentage Sourdough 59,5% 714 Health 16,7% 200 Home 23,8% 286 100,00% 1200 Page 36

Given these exact numbers, random selection was conducted within each main stratum until these numbers were reached. After the random selection within each stratum was done the final sample appeared and the respondents within this were then notified by regular post and instructed to go online and conduct the survey. Fig) 7 The stratified sample procedure: Population 1 2 3 Sourdough Homemade Yoghurt Homemade Health Yoghurt 59,5% 23,8% 16,7% (% x 1200) Stratified Random Sample1200 3.4 Reliability and validity The reliability and validity concerns the research in the way of how good one measure and conduct it. According to Grennes (2001) each research has defects to some extent, thus the importance to go through these two concepts and relate them to the research. Reliability is defined as: The extent to which an experiment, test, or other measuring procedure yields the same results on repeated trials (nces.ed.gov), while validity is defined as: An indication of how well an assessment actually measures what it is supposed to measure. A valid assessment measures what it is supposed to measure and not extraneous features (syrce.org3). Page 37

To ensure the validity of the research, a probability sample was extracted from the population where each element in it had the same probability to be drawn. The process has been described above and according to the statistical laws this strengthens the validity of the research (Wenstøp, 1997). Reliability considers to what extent a measurement/experiment will be the same if it is conducted many times (Gripsrud & Olsson, 1999). According to Selnes (1994) the reliability of a research has to do with how the research is conducted and discusses reliability from three different views; in relation to the measurement tools, the data collection and the treatment of the data. The research method is also described above and works as an instruction guide of how to the survey is put up and how the data is collected. In the analysis the statistical software SPSS (www.spss.com) is used to measure relations between certain variables and will be depicted in such way that it is possible to redo the exact same procedure again. In addition to SPSS, the data collection program Questback has a function that makes it possible to transfer the data into different file formats. This is then used for presentation and analysis purposes and is also redo-able. 3.5 Source of errors According to Grennes (2001) a survey method always has errors to some extent and when using this type of method one has to be aware of the sources of errors that exist. There are mainly two sources of errors, whereas one concerns missing observations while the other concerns errors in the measuring part. The missing observation part considers; cover errors, none response errors and sample errors. Cover errors results when the population that is under investigation is not covered well enough. If the lists of customers in Mejeribolaget for some reason would not be updated and a sample is extracted from this, it would be an example of cover error. Non- response errors occurs when some of the respondents in the survey let be to answer it. If the respondent started to answer the survey but for some reason did not fulfill it, it was not recorded. The survey was sent to the server only when the final question was answered. The expected response rate was 15-20% and it turned out to be 16% after cleaning the data (a more thorough discussion about non-response errors is undergone in section 3.5.1). Sample errors can arise if one makes statement of the whole population on the background on the Page 38

sample population. Even if the sample method works properly, systematically errors can appear in the sample as a consequence of a high drop-out rate. The drop-out can either be explained by that the respondent does not want to participate in the survey or that the respondent forget to answer it (Selnes, 1994). Another type of sample error could be that the respondent answers the survey many times. This could have been the case here since the only id for the respondent was their e-mail. The respondent were sent information about the survey through post and then referred to an online address. Moreover, there is a slight chance that non-qualified people are included in the sample since the survey was put on the website, with open access to the public. 22 respondents were purposely excluded from the survey with the suspicion of being nonqualified. These respondents had not filled in that they used any of Mejeribolaget s products, which cannot be the case, since the notification of participating in the survey was sent to active customers only. However, there are slight chances that some of the respondents have entered through the website and indeed answered these questions even though they were not qualified to participate. If this is the case, it most likely is a result of the contest and the prizes which could be won due to participation. In addition, 227 respondents had to be eliminated from the survey due to a hacker activity. There was somebody who had copied the link of the survey and put it on another server letting non-qualified respondents participate and this was detected when there suddenly (over a two day period) started to pop in hundreds of answer with a short time interval between each. The survey had been online approximately two weeks when this occurred and according to the statistics from the previous days it was more common with 6-14 completed answers each day. In order to make the survey correct all the answers registered during these two days were eliminated and the survey was shut down. As a consequence, some correct answers registered within these two days also had to be taken away. Furthermore, if the survey could have been online for another week or two it probably would have generated around another 50-60 additional qualified answers. Nonetheless, after cleaning the data the remaining set of qualified answers added up to 191, which are the fundament for the analysis in the next chapter. Page 39

The other main source of error is measuring errors and these errors are characterized by the gap that arises between the actual collected information and the information initially wanted. The gap is usually detected after the data is collected. The reason for this can either be that the questions are leading/hard to understand or it can be errors in the communication between the respondent and the interviewer (Gripsrud & Olsson, 1999). Another error can occur when the respondent actually cannot answer the question, does not want to answer it or does not want to state the underlying truth. It should therefore be considered how sensitive or complicated the questions asked, are being perceived by the respondents. In order to minimize the effect of this, the survey was, as mentioned previously, pre-tested to some extent and rearranged thereafter. 3.5.1 Extended non-response error discussion In the recent years it has become more difficult to obtain high response rates for surveys in general. This is said to be due to various factors such as overflow of surveys in the market, bad design of the surveys, low personal interest for the research field and more. Response rates of 10-30% are common when carrying out customer satisfaction surveys and marketing research surveys with postal or web-based collections methods (www.customer-feedback-surveys.net; Dutka, 1994). Such response rates are very low and normally indicate biased results. Ultimately it could be said that this would never provide any clear insight in what the whole population actually thinks about the company. On the other hand, since it is difficult to reach very high response rates, some insight is usually better than none and even low response rates can provide the company with valuable information which it otherwise would not have got. The thing to keep in mind though, is that these results usually are biased and beneath the implications of low response rates will be discussed. Non-response error is usually divided into two categories, namely item nonresponse and unit non-response. Item non-response is related to the internal incompleteness of each respondents answering. The internal incompleteness in this survey was low and differed only with a few respondents skipping some questions, thus not affecting the overall accuracy in a significant way. However, the unit non-response was high in this survey as a result of the low response rate and biases the results. Unit non-response refers to respondents who do not answer the questionnaire and the response rate in the survey reached 16% which the analysis in the next chapter is based upon. Around 80% of the respondents are subject to unit non-response which makes the accuracy Page 40

for generalizations to the whole population of Mejeribolaget s customer base difficult. Since the survey had to be shut down earlier than planned, some respondents did not get the possibility to participate. Consequently, they are not considered subject to non-response error, rather fault to unforeseen events and the 80% estimation is based upon the estimated response rate of 15-20% with the shut-down of the survey in mind. It is not correct to say that the point of view of the 16% who answered is the same as for the remaining respondents who did not and there is no way to find out about this unless an analysis of the non-responders is conducted and then compared to the results of the 16% who did answer. There are various aspects of why and why not people do not participate in a survey and some researchers suggest that it is the very most satisfied customers that usually participate since they are most loyal to the company. In contradict other researchers suggest that it is the most dissatisfied customers who mainly participate since this gives them an opportunity to reveal their dissatisfaction toward the company (Hoffman & Bateman, 2001). Non-response has two effects on the data: first it introduces bias in estimates when non-respondents differ from respondents in the characteristics measured; and second, it contributes to an increase in the sampling variance of the estimates because the effective sample size is reduced from that originally sought. The accuracy of a sample is based on its absolute size and not its proportion to the population. A larger sample will always be more reliable than a smaller sample whatever the total size of the population. The size of a sample is usually put to around 200 as a minimum to give a reliable sample size (Hill et al., 1999). In this case the response rate was expected to be around 15-20% and with a confidence level of 95% with an error level of 7% it would be required to get approximately 189 answers to get an accurate sample size. In order to get the required amount of answers the survey was sent to 1200 people who were selected through a stratified random sample selection procedure as described previously. The theory suggests that it is the very most satisfied, most dissatisfied, people with higher education and higher income that usually answers to a survey when the response rate is low. Since the sample size is appropriate to base statistical foundations upon it is possible to generalize the results found in the analysis to the mentioned participants above to the similar groups in the whole population Page 41

but not the whole population itself. However, since there are no specific identification factors for these groups in the sample and no other factors that reveal any specific characteristics 2 it is difficult to state with precision which part of the population the results can be generalized to. In order to generalize the whole sample result to the whole population, the response rate should have been at least 50% and in theory 100% which rarely is the case (Hill et al., 1999). It is common to conduct a so called unit nonresponse analysis (analyze the ones who do not answer) and try to find similarities or differences between these and the ones who answered in order to square out the non-response bias. When conducting such analysis, it is of interest to send out reminders to the ones who did not answer or get in contact with them in some other way. The Questback software can send out reminders to the ones who do not answer the survey, given that the invitation to the survey is sent to the participant specific e-mail. Since no list of e-mail addresses to the customers existed this could not be conducted. Instead, the survey had to be entered through the website directly and the opportunity to use the reminder function for analysing the non-respondents as well as for increasing the response rate was not an option. Moreover, demographical facts of the non-respondents can also reveal differences. However, the fundament for conducting such analysis was not strong enough since no identification was kept of the selected participants and no demographical data could be withdrawn for comparison. In addition, no identification was recorded when answering the survey (in order to remain the anonymity of the participant) except the respondents e-mail address. The response rate was initially meant to be somewhat higher and incentives such as designing the survey in a satisfactory way, pre-notification via regular mail and a contest with prizes was used in order to obtain a higher rate. However, due to the hacking activity, the survey had to be shut down earlier than planned, which resulted in a lower response rate. Furthermore, the contest was meant to attract participants regardless of extremes in attitudes and to obtain a better overall spread in the sample but as mentioned above, this cannot be analyzed properly in order to find specific groups of the population. 2 No demographic factors revealed any divergent findings in the analysis and no socioeconomic factors were included in the survey, which made this issue more difficult to analyse. Page 42

In the analysis in the next chapter, the spread of the ones who answered will be undergone and the results of these answers are still an important indicator of how the business is perceived. However, is it necessary to bear in mind that the final results and conclusion are based on the 16% who answered and that they do not count for the whole population, thus generalizations should be approached with caution. The stratified sample was divided after type of subscription and it was found that the distribution was the following: Sourdough - 59,5% Homemade Yoghurt - 23,8% Health Yoghurt 16,7% Number of respondents turned out to be 191 after some data cleaning and the distribution did not turn out to be the same as in the original sample. It had the following distribution in the 191 sample: Sourdough - 41% Homemade Yoghurt - 37% Health Yoghurt 16% Health+Home 6% It can be seen that the Sourdough segment is underrepresented while the homemade yoghurt is overrepresented. The reason why this have occurred, besides the facts discussed above, might be related to the fact that many of the Sourdough customers are new customers in the company and thus not feel that they can contribute or be able to answer the questions in a satisfactory way. As a consequence they might have chosen not to participate. The Homemade Yoghurt segment have more respondents and this could indicate that there is a higher interest to participate due to dissatisfaction or satisfaction, in addition to the fact that Homemade Yoghurt customers have been in the company for a longer time and perhaps feel that they can contribute more to the survey than the Sourdough customers. As will be seen in the analysis in the next chapter, the age distribution between the Sourdough and Homemade Yoghurt segments is the same, which indicates that the bias does not seem to be affected by age. The Health Yoghurt segment has the same distribution. Page 43

The over- and underrepresentation in the Sourdough and Homemade Yoghurt segment makes clear generalizations to the whole population difficult and the results from the analysis within these can only be used to draw parallels in the examined sample. This still gives valuable insight, but not to the same extent as it would if being generalized to the whole population. The Health Yoghurt segment can be generalized to some parts of the population but not to the whole population as a consequence of the low response rate. Page 44

4. Data analysis This chapter will test and go through various aspects of the data collected through the survey and be put in relation to the research questions. There was a desire to generalize these results to the whole population and in the methodology it was described how the sampling procedure was conducted in order to extract a statistical correct test sample that would mirror the whole population. However, due to the high rate of non-response and over- and underrepresentation in the sample, this was not doable. Instead the analysis is related to this particular sample and generalizations should be approached with caution. Descriptive statistics, cross-tabulations and multiple regression was used for analyzing the data. Multiple regression (the estimated relationship between a dependent variable and more than one explanatory variable) was used to test which variables that predicted the product satisfaction and website satisfaction. All the data, except the data from the open box questions, was transformed into scale level, in order to be able to be regressed. Many of these were originally on a nominal level but were forced into scale level by dummy variables. By transforming the nominal data into scale it could be used to interpret certain data easier and to do statistical calculations. For example; ordering frequency is not on a scale level but by assessing dummy variables it is possible to find the mean for it and then approximate where among the different alternatives most customers score. It should however, be pointed out that this is not in order with a true statistical mean and thus used very skeptically and only applied where there is no room for misinterpretations. To find the variables that significantly predicts the dependent variable the t- number, depicted in the regression analysis output, was used in the selection. The procedure of finding the predictors was done by running regression tests in each of the six different categories depicted below which more or less followed the structure of the survey. Demographics and other features Yoghurt features Sourdough features Website features Product development features Service features Page 45

By testing within each category it was more probable to find the right variables and after finding these (if there was any) they were then regressed with stepwise selection until the independent variables that best predicted the dependent variable appeared. The significance level was set to a 5% level and the t-number varied depending on number of observations (degrees of freedom) and was read out from the standard t-distribution chart. Some tests that were conducted in this chapter had different number of observations which had to be confirmed with the right t-number since it differs from number of observations. If no detection occurred, correlation was used to detect if there was some variables in relation to another that were significantly high. Correlation does not, however, imply any direct causation but if found very high, can be further investigated to see what causes it. Parts of the data cleaning where described in the previous chapter stating that some respondents had to be manually deleted due to suspicion of being nonqualified respondents (refer to this part for a closer description). In addition to deleting those respondents, the data set has undergone eye scanning and where necessary, rearranged in a correct way. As an example; if the respondent did not fill in anything on the age category, this was coded into the do not want to state option. If this was not done, it would have generated an extra bar in the charts which is unnecessary. Furthermore, these types of errors where adjusted when detected in the frequency and descriptive run in SPSS. Remaining missing values that could not be rearranged were coded as discrete values in the analysis when necessary. Research Q1 - Are the customers satisfied with the current products? Section 4.1-4.3 will go through the three different products offered at Mejeribolaget and try to answer this research question. 4.1 Homemade Yoghurt This is one of the three products offered at Mejeribolaget and this section goes through various aspects of the Homemade Yoghurt segment, whereas some are more detailed than other. Not all of these are directly related to the problem statement but are convenient to look closer upon in order to make assumptions that can be related to it. In this case the data set was split to include only the customers who ordered Homemade Yoghurt and customers who ordered the combination Homemade Yoghurt+Health Yoghurt. The number of Page 46

observations was 79 whereas 68 was plain Homemade and the remaining 11 was combined Home+Health customers. 4.1.1 Age & Gender The age distribution (fig 9) had its high peaks stretching from 40-59, while the gender distribution was 91% females and 9% males. For the whole population sample (see section 4.7.1) the gender distribution was 83/17. This indicates that there are more women in this cluster and can be an important issue for Mejeribolaget to consider in the marketing activities. Fig 8) Gender distribution Homemade Yoghurt Segment Fig 9) Age distribution Homemade Yoghurt Segment Page 47