Bringing colour into our digital lives

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1 Bringing colour into our digital lives Piet Hein van Dam Wakoopa Warmoesstraat JC Amsterdam The Netherlands Pascal Van Hattum SmartAgent/ Utrecht University Piet Mondriaanplein GZ Amersfoort The Netherlands Paulien Schieven SmartAgent Piet Mondriaanplein GZ Amersfoort The Netherlands Bio: Piet Hein van Dam (PhD in experimental physics) is CEO of Wakoopa in Amsterdam, The Netherlands. Pascal van Hattum (PhD in methodology and statistics) is manager Data Intelligence at The SmartAgent Company in Amersfoort, The Netherlands, and researcher at Utrecht University, The Netherlands. Paulien Schieven is Managing Partner at The SmartAgent Company in Amersfoort, The Netherlands. 1

2 Bringing colour into our digital lives Abstract This paper presents the results of an experiment where an emerging new technology (single source passive metering) has been combined with a well- known socio- psychographic segmentation method. What can be learned when analysing a person s digital footprint while knowing his or her underlying motives? This innovative project is a collaboration between two companies, exploring the richness and application of behavioural data within market research. With this project we will shed light on the behaviours and the underlying drivers of online consumers. Key words: psychographic segmentation, single source behavioural measurement, passive metering, stated versus actual behaviour, Rogers adopter categories. 2

3 1. Introduction In 2008 the World Federation of Advertisers published their famous Blueprint for consumer- centric holistic measurement (WFA, 2008). It outlines the vision, objectives and recommended actions towards the developments of a holistic measurement methodology - for truly understanding the multi- media behaviour of consumers while respecting their privacy. A century earlier, Alfred Adler published the basic principles of what later became the social- psychology theory of individual differences (Callebaut et al., 1999). This is a strong framework for understanding consumers at their deepest level of fears, beliefs and values providing insights into their fundamental motivations that drive (future) purchase decisions. What would happen when we combine both? Suppose we have the insights into consumers with the socio- psychological depth of Adler and we have registered their total online media consumption? Then we know and understand why people do what they do, and how to interact in a way that is meaningful. Wouldn t that be the researchers ultimate dream? This paper presents the results of this experiment. How does the online media consumption differ across four motivational clusters? How is the total online time divided over the different devices and what sort of activities do they prefer to do on each? And how does this relate to their motivations and socio- psychological backgrounds? We will share the operational evaluation of the experiment. How difficult was is, what where the limitations, and what are the implications for further roll- out? 2. Research background In this section we will explore the two underlying frameworks of this study: the psychographic segmentation model and the 2008 blueprint of the World Federation of Advertisers. 2.1 Brand Strategy Research (BSR) Brand Strategy Research (BSR) (Brethouwer et al., 1995 and Van Hattum & Hoijtink, 2008) is a psychographic segmentation model, that has been used in (inter)national research since The BSR model is based on Adler's social- psychology theory (Callebaut et al., 1999) and provides a framework for understanding customers at the 'deepest' level. This level gives insights into consumer's fears, beliefs and values, thus providing an understanding of the fundamental motivations that drive (future) purchase decisions. The BSR framework can be presented as a strategic map divided by who axes, resulting is four quadrants (figure 1). The horizontal axis is called the 'sociological' axis and indicates how a person relates to their social environment: the right side indicates involvement (belonging), the left side indicates independent (affirmation). The vertical axis is called the 'psychological' axis and indicates how a person handles with 'tensions': the top side indicates an expression of 'tensions' (extravert), and the bottom side indicates a suppression or ignorance of 'tensions' (introvert). The result is a four- quadrant map, each quadrant demonstrating unique needs, motivations and drivers. This map offers a basis for developing consumer strategies, aligning the total marketing mix around the consumers needs in the specific domain. 3

4 Figure 1: BSR strategic map The four clusters of consumers are: Red World of Vitality: In this world the main drivers are personal growth by exploring, testing boundaries and discovering new things. Typical characteristics are: open- minded, self- conscious, adventurous, passion, energetic, creative, always looking for the unusual. Blue World of Control: Persons from this cluster like to be in control over their emotions and feelings and have a need to stand out from the crowd, intellectually and materially. They have a desire to be seen as successful. Typical characteristics are: individualistic, rational, ambitious, competitive, wise, capable, and career oriented. Yellow World of Harmony: Connecting with other (new) people is a main driver in this world. Persons in this world like to share their life, experiences and emotions with other people in a harmonious way. They can be described as spontaneous, kind, open, enthusiastic, helpful, caring and optimistic. Green World of Safety. Persons from this cluster strive to feel save and protected, and have a need to belong to a certain culture or a group. Order, discipline, routine and following the norms of that group give them stability and structure. They can be described as calm, cautious, conservative and traditional. For a detailed description of the four clusters the reader is referred to Van Hattum and Hoijtink (2009, p.7-10, 26-34) or 1. The BSR questionnaire (Van Hattum, 2009, p.36-37) consists of five validated questions, each containing multiple psychographic items regarding to (1) character, (2) type of household, (3) appealing professions, (4) hobbies and interest and (5) values in life. The respondent can choose the items out of in total 149 items that describe himself best. Based on a latent- class analysis (Kamakura & Wedel, 1997; Vermunt & Magidson, 2000 and Van Hattum & Hoijtink, 2009b), the four clusters of consumers are distinguished. The interested reader is referred to Van Hattum and Hoijtink (2009b) for a detailed description of the statistical procedure of latent- class analysis and the identification of the four motivational clusters. The four clusters within the framework provide a basis for developing consumer strategies, aligning the positioning and total marketing mix around the consumers needs in the specific domain. For proven cases of how the BSR model is used in (differentiated) marketing 1 Using the link it is possible to fill out the BSR questionnaire and discover ones own BSR- colour. 4

5 strategies in order to improve response rates on direct marketing, the reader is referred to Van Hattum and Hoijtink (2008, 2009a) and Van Hattum et al. (2011). Brand Strategy Research (BSR) in general, and the BSR questionnaire in specific, has been subjected to (scientific) research since a few decades. Oppenhuizen (2000, Section 2.5) compares different value inventories, like BSR, List Of Values (Kahle & Kennedy., 1988), Personal Drives Analysis (Vromen, 1995), Socioconsult (Motivaction, 1998) and Rokeach (1973). The comparison and connection between BSR and well- known models like HBDI (Herrmann, 1989), Schwartz (Schwartz, 1992) and Myers- Briggs Type Indicator (Myers & McCaulley, 1985) are subjected to research in Wolters et al. (2007) and Wolters and Van Hattum (2009). In Van Hattum and Hoijtink (2009) the knowledge about associations between BSR items within each BSR cluster is used as input for their Bayesian cluster model. The comparison and connection between BSR and the Big 5 theory (McCrae & John, 1992) is part of an ongoing research program. 2b User side and single source audience measurement The consumption of online media is growing at an enormous pace. Each day, people spend more and more time (and money) online. To be successful online, companies need to know how big their audience is, who they are, and how the online behaviour changes day by day. They need to measure the reach, audience and effects of all their online efforts. Online behaviour can be measured in two ways: by cookie based measurement and by tracker based measurement. Cookie based measurement measures IP- addresses. This approach suffers from a measurement bias: people that use multiple devices to go online are counted more than once. And there is the cookie- double- count artefact when people s cookies are renewed. Although widely accepted as currency, it makes cookie based measurement less suitable for accurately measuring unique visitors. And in some countries, there is also upcoming legislation that could restrict the use of cookies for these purposes. Tracker based measurement, the second approach, uses a small application which is installed on the computer of a panel member that registers his or her online behaviour (websites, search, online ads). This method is suitable for measuring unique visitors, but suffers from potential panel effects (multiple user error and self- selection bias), see Van Dam (2012). One of the advantages of user- side audience measurement is that it measures people, not cookies. This way, the online media consumption of people on any device can be measured single source. When the participants also add their socio- demographic backgrounds to it, full audience measurement is a reality. In June 2008 the World Federation of Advertisers (WFA, 2008) saw that in the attention economy (Davenport, 2002), the consumer s attention was the most precious commodity. Agencies and media suppliers should work together to understand the integrated multi- media solutions. To achieve this, they set several industry goals, among which: 1. Passive measurement systems to better reflect holistic consumer communication behaviour. 2. Faster and continuous provision of measurement information. More granular, weekly, data provision will enable marketers and agencies to apply their sophisticated modelling and analyses tools more effectively. 3. Better linkage of relevant target group descriptions to media measurement capabilities. Today s marketing target group definitions tend to go beyond demographics. The questions used for defining these targets should be asked on a single- source basis in media measurement panels. 4. Agile, fast, competitive and adaptive systems that can move at the speed of marketing models and evolving connection opportunities like emerging media. The emergence of high 5

6 leverage communication vehicles and changes in emerging media and marketing models are happening faster than ever before. Measurement needs to accommodate this to stay at the forefront of new developments. The WFA promotes passive measurement systems to better reflect holistic consumer communication behaviour and consistent sources of information for a better understanding of the relationship between shopping and media usage. 2.3 Passive metering technology The passive metering technology used in this study was developed by Wakoopa, an Amsterdam based technology firm supplying market research agencies worldwide. The technology is an all- in- one solution for passively measuring the digital footprints of respondents across their devices (pc s, smart phones and tablets) and across their activities (browsing, search, apps usage, ad- and pre- roll exposure). In a privacy- conscious way. All streams are brought together in one analytical dashboard. This is how it works. People are invited to install a small app (or use specific settings) on their PC, on their mobile and their tablet. First, there is a clear explanation of the privacy features of the app; the collected data are anonymous, the tracker app can be paused at any time and sites can be classified as do not track. Next to this, people can see their own digital footprint. Clients using these data are obliged to do that solely for research purposes, and not for commercial lead generation. The app has the required software safety certificates and is lightweight (i.e. it doesn t influence the performance of the devices). When people have seen their own digital footprint, they can decide to exchange it for a reward (mostly monetary). After the app has been installed, it appears as a small icon in the taskbar. People can double click on it to access the privacy options. Once the data is collected in a transparent and controlled way, they are stored on secure webservers at Amazon s cloud computing services. Researchers can access the data through an online analytical dashboard. Built to manage big data, the dashboard gives the researcher the possibility to do near- time analysis on the collected online tracking data. This gives the researcher the unique possibility to really measure the highly intuitive Internet economy, instead of having to rely on the stated behaviour that is collected by traditional survey methods. When the individuals have completed additional surveys on their attitudes, motivations and socio- demographics, these data are also made accessible in the dashboard. This makes it possible to combine behavioural data with attitudinal data, as we have done in this paper. 3. Research design 3.1 Experimental setup Wakoopa is collecting the digital footprints of more than individuals in more than 20 countries. These are mostly proprietary panels from international market research agencies and publishers. In the Netherlands, Wakoopa exploits a syndicated panel of about people (0.1% of the Dutch online population 18+). The panel has been set up in collaboration with a commercial panel supplier and it is a good cross section of the Dutch 18+ online population. The panel members of this so- called Trailspot have installed the PC meter and their online behaviour has been monitored continuously, since end Hundreds of background variables have been collected and uploaded to be connected and analysed in conjunction with the individuals behavioural data. It is single source, so one always can track back the data to a real person. And if desired, one can pose him some additional questions. 6

7 The experiment described in this paper was conducted in the fourth quarter of The Trailspot panel members were invited to complete a questionnaire on their Internet behaviour and attitudes, and to answer the five BSR questions. In total 5,973 panel members completed the questionnaire (response rate of almost 60%). Based on the answers to the five BSR questions all respondents were assigned to one of the four BSR clusters. Subsequently, the answers to the questionnaire and the assigned BSR cluster are linked to the digital footprint, as described in Section 2.3. Separate to this, a selected group was invited to participate in a mobile trial. A few hundred panel members installed the first version of the Wakoopa mobile meter (both Android and ios). In this paper we further analysed the specific behaviour of 107 panel members that have the PC plus the mobile meter installed, and completed the BSR questionnaire. 3.2 Structure of the paper In the next section we will discuss the results of the experiments. In Section 4.1 we will investigate the stated behaviour of panel members versus the motivations according to the BSR segmentation. How do the statements of the panel members on their own internet behaviour compare to their underlying drivers? And what does this tell us about the attitudes and internet consumption of the four different clusters? In Section 4.2 to 4.4 we will investigate how several internet brands such as Facebook and Apple differ in their positioning to the general public following the BSR clusters. And what we can learn from their approach and from their audience. 4. Research results This section shows the results of our experiment. In Section 4.1 we analyse the relation between the BSR segments, as introduced in section 2.1, and the motives for using the internet. Section 4.2 provides a more detailed description of the four BSR clusters in terms of media consumption, internet and mobile communication, as measured by means of an online questionnaires. This section gives good insights in the stated behaviour of the panel members. In other words, what panel members say they are doing on the internet. Section 4.3 to 4.5 deals with the actual behaviour of the panel members. The digital footprint of each panel member is measured using the passive metering technology and analysed in relation with the known BSR cluster. This section gives a good answer whether the panel members actually do on the internet, what they say they are doing in market research, and even more interesting; can we explain their actual behaviour from the psychographic insights the BSR profile provides. 4.1 Motives for using the internet per BSR segment A total of Dutch people within the panel were surveyed about their motivations, attitude and usage of the internet. The questionnaire contained also the five BSR segmentation questions, so each respondent was assigned to one of the BSR segments as described in Section 2.2 (i.e. Red, Yellow, Green or Blue world). In this section we focus on the comparison of the different motives in each segment. Using latent class analysis and correspondence analysis, a BSR segmentation scheme was created from this data set, showing the relation between the psychographic BSR profile and the motivation for the use of the internet. 7

8 As shown in figure 2, this analysis indicates that the two basic dimensions of the BSR model can with regard to explaining the use of internet be translated as follows: Psychological dimension: What can Internet do for myself? internet = emotion, freedom vs Internet = functional / control Social dimension: What can Internet show about myself? internet = social affirmation / manifestation vs internet = social integration / belong Fig 2: BSR motivational frame of reference The results indicate that each BSR segment have specific motives for using the internet. For example, as shown in Fig 3, the main driving force behind internet use in the Yellow segment is social interaction and making connection with (existing) friends, actively share your life and experiences with friends, both offline and online. In the Red segment, internet is heavily used to fulfil the personal need for communication with (new) friends, discover the world as well as a medium for self- expression, by showing what you think and create. In the Green and Blue segments, the main driving forces to use the internet are more related to functional needs, like information seeking (Green) and organising things (products, services but also their newsfeed) in an efficient way (Blue) to save time and money. 8

9 Fig. 3: The score on the statement per BSR segment compared to average score on this statement derived from the total sample (index, average = 0) 4.2 Internet use - stated behaviour What do people do on the internet? Or better: what do they say they do on the internet, as measured in our study. In this section we will further describe the four BSR segment in terms of stated behaviour, but also some interesting psychographics on media and brand use. As shown in figure 4, one can see large differences between the BSR segments with regard to the stated behaviour. For example; segment Blue say they regularly shop online. They think it is easy and safe. Besides, they don t like go out for shopping. Segment Yellow likes to spend time on Facebook; interacting with their (large) social network, and playing online games together. In segment Blue LinkedIn is the place to be; it is also about communication, but more in an goal- oriented and controlled way, compared to Facebook. Red has a need to enrich the world with their opinions and 9

10 thoughts on Twitter. And Green, they still think the internet is quite complicated and they need some time to find out what you actually can do with / on it, they don t want to miss the boat. Fig 3: Stated behaviour per BSR segment compared to average score on this statement derived from the total sample (index, average = 0) Only six statements are shown in Figure 4, as an illustration. In the next paragraphs we will give descriptions of the segments with all the information gathered from the online survey is used. Persons from the Red world are heavy users of internet. For these persons internet broadens up their horizons, off the beaten track. They surf on the internet for hours. More than the persons from the other clusters they say that they are addicted to internet. They are continuously looking for new 10

11 and innovative websites. They think that if you make clever use of internet, it could be beneficial for yourself. They frequently watch television and films on the internet. Also YouTube is a familiar site for them. These persons are very familiar with buying things on the internet. Online shopping is found easy and is a way of life for them. For Red persons, internet is an easy and quick medium for maintaining their large (mostly social, but also business) network. Twittering, chatting, Skype- ing and updating their profile sites (mostly Facebook and LinkedIn) are activities they are very familiar with. Persons from this cluster also want to share and take part of interesting topics on the internet. This results in activities like updating their own weblog, writing reviews, following and participating in discussions. As heavy users, Red persons want to be on the internet at any time and in any place. From all clusters they use the most online devices. Whether it is a laptop, smartphone or tablet, there must be an access to the internet and preferably a fast one. Apple is a typical brand for their devices. Not only the MacBook, but also the ipod, iphone, ipad and Apple TV. In most cases they use a large part of the Apple product range. In terms of Rogers adopter categories (Rogers, 1962, p. 150), Red persons can be identified as the Innovators. Persons from the Blue world are also frequent users of internet. However, not as frequent as Red persons. Blue persons use the internet more dedicated for business. They follow the news on the internet. Blue persons think internet can be beneficial because it helps you to organise things in a quick and efficient way. Websites that compare products and services among each other are frequently visited. Persons from this cluster do not have problems with financial transactions. In fact, they think that people make a fuss of privacy on the internet problem in general and on online payments in specific. Blue persons think that paying and banking over the internet is safe and they have no problem with buying products and services and doing their administration using an online banker. Skype is an effective communications for them. Twitter is another medium to keep informed and to show your knowledge, your own ideas and your own wellbeing. More than the persons from the other clusters Blue persons make use of LinkedIn. They use LinkedIn to update their record, to express their knowledge and skills and to find (new) business partners. Like the persons from the Red world, Blue persons want to be on the internet at any time and in any place. The also possess multiple online devices, like a laptop, smartphone and tablet. Brand names are less outspoken than in the Red world, but are certainly the well- known, large brands. In this cluster you find also Apple products, but not the whole products range. IPhone and ipad are familiar products. In terms of Rogers adopter categories, Blue persons can be identified as the Early adopters. Blue persons keep a close watch on the Red world. If Blue persons think that certain new trends, products or services are more or less safe to use, free of the teething problems or beneficial for their prestige or authority, they will adopt that particular trend, product or service. Persons from the Yellow world use the internet mainly for social interaction with friends and family. Internet is fun for them. Most of the time, the same and known websites are visited. In particular the social media site Facebook is used to keep in touch with friends and family. Their Facebook profile is frequently updated with news, status updates and photos. Also news flashes, status updates, photos from their friends are being tracked. Photos are also uploaded to other photo sharing sites. Another activity Yellow person do on the internet is gaming. However, shopping on the internet is not a thing for Yellow persons. They look at the internet for nice bargains (i.e. via EBay or Marktplaats), but they rather prefer a day shopping with friends. Shopping is a social event. The number of devices with which it is possible to be online is average. More than other clusters Yellow persons only have a desktop computer to go online. And more than other clusters, they do not have a smartphone, but a normal mobile phone. In terms of Rogers adopter categories Yellow persons can be identified as (Early and Late) majority. As said, Yellow looks for bargains. Not only on the internet, but also in shops. Whenever products and services are produced for mass consumption (and consequently reduced in price or subjected to bargains), it is most likely Yellow persons start to consume these particular products and services. 11

12 Persons from the Green are the least familiar with internet and mobile communications. They think that using the internet is a bit scary. Using the internet is a necessary evil for them and not to their attention. However, when using the internet, persons from this cluster do a direct search on particular information. Most of the time, the same and known websites are visited. They also use the internet to be at the times. In fact, they are actually curious what internet has more to offer for them. Internet is also a medium to keep in touch with others. The social media site Facebook is too far and hard for them. They are more familiar with Hyves, in which they are not very active uploaders, status updaters. It is more often a medium to be informed. Green persons use the internet in order to orient themselves on products and services. However, products are bought in the actual shops. They would like to touch, see and feel the product before they buy it. Buying online is often too scary. The Green persons are the persons with the least online devices. Most of them are online using a desktop computer. Smartphone are too far away and too complicated. If they have a mobile phone it is a normal one. In terms of Rogers adopter categories Green persons can be identified as Late majority and Laggards. Whenever products and services are produced for mass consumption (and consequently reduced in price or subjected to bargains) and, moreover, particular not of interest for the Red (and in a less extent for the Blue ) persons, it is most likely Green persons start to consume these particular products and services. 4.3 Internet use - actual behaviour General internet consumption patterns of the four BSR clusters In October 2012, Trailspot contained unique active participants. During this month, they were 2.4 billion seconds online (75 years in total) and they visited 72.8 million webpages. Per person they were 58 hours online, and on average they visited 7 pages per visit. A visit is a series of page views under one main domain (within a group of URLs) from the same participant with a time of no more than 30 minutes between each page view. These data contain two important parameters for internet usage: the time each person spends online and the attention that person has per visited site. Think of it as volume and stickiness. How much does a person consume, and for how long has a certain object attracted his attention. We have used these two parameters as a benchmark to compare the internet consumption patterns of the four clusters (see Table 1). The average of the total panel is set to 100. Index Panel average Vital Red Contol Blue Social Yellow Safe Green Relative time spent online (hours) Relative attention span (pages per visit) Table 1: Comparison of internet indexes among BSR clusters. One can see that the attention span decreases regularly from Red to Green, while the time spent online varies. The same pattern we found when we analysed other months in In Figure 5, the data are shown in a so- called internet usage comparison chart; plotting the relative time spent online against the relative attention span. 12

13 Figure 5: Internet usage comparison plot with the four BSR clusters total internet usage Internet consumption patterns Facebook Now it is interesting to see how the usage patterns of the four clusters look when it doesn t concern their total internet usage, but specific parts of their online activities, such as the time they spend on Facebook. In October 2012, the Trailspot panel members spent on average 13.5 hours on Facebook, with an average length of 19.3 pages per visit. When we compare the panel averages with the averages of the four BSR clusters, we obtain the data shown in Figure 6. Please note that the scales have enhanced compared to Figure 5 (zoomed out). Figure 6: Internet usage comparison plot with the four BSR clusters Facebook.com The figure clearly shows that Social- Yellow has a preference for Facebook, which is not a real surprise, because Facebook has become mainstream and fits perfectly in their lifestyle to share their daily life events with family and friends. Their time on site is 19% larger than average. Control- Blue clearly doesn t use Facebook (anymore) and Vital- Red uses Facebook intensively, but only for specific 13

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