From desktop to supermarket shelf: Eye-tracking exploration on consumer attention and choice

Journal Pre-proofs From desktop to supermarket shelf: Eye-tracking exploration on consumer attention and choice Svetlana Bialkova, Klaus G. Grunert, Hans van Trijp PII: DOI: Reference:

S0950-3293(19)30369-6 https://doi.org/10.1016/j.foodqual.2019.103839 FQAP 103839

To appear in:

Food Quality and Preference

Received Date: Revised Date: Accepted Date:

17 May 2019 3 November 2019 3 November 2019

Please cite this article as: Bialkova, S., Grunert, K.G., van Trijp, H., From desktop to supermarket shelf: Eye-tracking exploration on consumer attention and choice, Food Quality and Preference (2019), doi: https://doi.org/10.1016/ j.foodqual.2019.103839

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Consumer attention and choice

From desktop to supermarket shelf: Eye-tracking exploration on consumer attention and choice

Svetlana Bialkova*a, Klaus G. Grunertb, Hans van Trijpc

a

Utrecht University, The Netherlands b

c

Aarhus University, Denmark

Wageningen University, The Netherlands

Correspondence: Dr. Svetlana Bialkova Utrecht University Princetonlaan 8A, 3584 CB Utrecht email: [email protected]

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Consumer attention and choice ABSTRACT

Determining the key parameters driving attention and choice at the point of sale is a challenging task. To address this challenge, we performed two studies employing eyetracking (ET) as a methodological tool when varying the visual marketing stimuli in a lab-experimental setting and in real supermarket shelf, and thus, facing an important gap in the current body of literature - the need to reconcile ET results from lab and field studies. The first study was conducted in lab settings and explored in a controlled manner the top-down (goal-directed) vs. bottom-up (stimulus-driven) mechanisms of attention and choice. The second study took a step further in investigating these mechanisms in real life settings, namely a supermarket shelf. In both studies the same assortment context was presented (i.e. eight products, four flavours of two brands each). The products varied on their level of healthfulness (i.e. nutrient profile) which was explicitly communicated with nutrition labelling formats displayed front of pack. Participants were asked to select either the healthiest product or a product on their preference (lab settings), and a product of their preference (in-store settings). Fixation duration, number of fixations, and the consumer's choice was recorded. The results show that Brand and Product flavour are leading criteria in driving attention and choice, i.e. the stronger brand and best selected product received higher number of fixations. The shopping goal and label formats also contributed to variation in observed patterns. Brand placement in combination with brand strength had a significant impact in the retail environment. Current outcomes demonstrate the potential of eye-tracking in consumer research, from lab to supermarket shelf. The advanced understanding we offer in attention patterns and consequent decision opens

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Consumer attention and choice promising avenues in successfully applying marketing strategies to navigate consumers’ attention and choice.

Key words: eye-tracking, consumers attention, choice, retail environment

1.

Introduction

Many decisions about the purchase of fast-moving consumer goods are made at the point of purchase (POP), and the product itself is therefore a major channel of communication determining the way consumer choices are affected. The process by which attention is directed towards products, and the cues embedded in them, has been recognized as an important factor predetermining the choices made at the POP (Bialkova & van Trijp, 2011; Bialkova et al., 2014). Yet, a question arises: what drives attention at the POP and what are the key parameters modulating it? Eye-tracking (ET) technology has been used as a methodological tool to address the above questions. Since the very early ET research in the marketing context (Pieters, & Warlop,1999; Russo & Leclerc, 1994), numerous studies have been conducted, looking at various parameters, attributes and potential determinants of consumers’ attention and consequent choice. Nevertheless, the findings are not always consistent, and thus, inviting further exploration. Particularly puzzling is the discrepancy between desktop studies performed in the lab (e.g., Bigné et al., 2016; Chandon et al., 2009; Meißner & Decker, 2010; Van der Lans et al., 2008; Wedel & Pieters, 2008) and studies conducted in a real supermarket environment (e.g., Burke & Leykin, 2014; Clement, Kristensen, & Grønhaug, 2013). Often scholars perform single studies either in the lab or in the supermarket, and in such a way insight about the external validity of the empirical work in these two settings is lacking. Note also the

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Consumer attention and choice shortage of in-store ET studies. The reason for scarce practical implications of ET observations at the POP is the required time, effort, technical constraints and expenses. Furthermore, ET studies at the POP are often obtrusive for the consumers and retailers, which makes lab studies preferred. Yet the question is whether the results from the two streams of ET explorations, i.e. lab and in-store are comparable and bring the same value. The current study addresses this issue, offering a comparison from desktop to shelf, and thus aiming for an in-depth understanding of fundamental mechanisms of attention and choice at POP. In particular, we explore gaze behaviour (in terms of number of fixations and fixation duration) and purchase decision in the context of fastmoving consumer goods (FMCG). Various visual marketing cues are manipulated in both the lab and the in-store setting, allowing thus a close comparison of the two streams of results.

2. Theoretical background The complexity of the in-store environment and the variability of stimuli competing for consumers’ attention and subsequent choice pose considerable difficulties in exploring these processes in realistic in-store environments. Despite the number of studies employing eye-tracking measures to investigate the relation between attention to these stimuli and the subsequent choice, the findings vary. Furthermore, most of the studies have been conducted in a lab environment, not in a real store setting, and thus raising questions about the external validity of the results.

From attention to choice: Evidences from eye-tracking

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Consumer attention and choice In the consumer behaviour literature, attention is usually associated with the degree to which consumers focus on specific stimuli within their range of exposure (Solomon, Bamossy, & Askegaard, 2002). Therefore, attention has been included as a key component in numerous consumer behaviour models (e.g., Engel, Blackwell, & Miniard, 1995; Hawkins, Best, & Coney, 1992; Peter & Olson, 1998; Schiffman & Kanuk, 2004). Eye tracking technology opened new avenues in exploring consumer behaviour, and in particular, the interplay between attention and choice. Recent studies in the context of FMCG provided evidence that attended stimuli are further processed in order to derive decision on whether to purchase a product (Bialkova & van Trijp, 2011; Bialkova et al., 2014). As attention determines where the eyes go, eye fixations are recognized to measure exposure to specific pieces of information (Rayner, 1998). The information sampled during the eye fixation accumulates evidences needed for the decision stage, as reported from neuroscience studies (Krajbich, Armel, & Rangel, 2010). Furthermore, marketing studies have shown that alternatives that are more likely to be chosen receive more attention (e.g., Bialkova et al., 2014; Pieters & Warlop, 1999; Russo & Leclerc, 1994). Yet, the critical question is: what drives attention? A further question concerns the environmental validity of marketing stimuli, i.e. the need to reconcile ET results from lab and field studies.

From desktop to shelf Two types of studies have been carried out to examine the allocation of attention at the point of purchase: those done in a lab setting and those performed in a real store setting.

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Consumer attention and choice Several lab studies employed eye-tracking methodology to explore how brand, product flavour, product placement and information on the package drive consumers’ attention (e.g., Bialkova & van Trijp, 2011; Bigné et al., 2016; Van der Lans et al., 2008; Wedel & Pieters, 2008), choice (e.g., Chandon et al., 2009; Meißner & Decker, 2010; Russo & Leclerc, 1994), and their interplay (e.g., Bialkova et al., 2014; Pieters & Warlop, 1999). One such study showed that only one third of the brands was noted and just under half of the brands re-examined were considered. Only 2.8 (out of 12) brands were reported to be included in the consideration set, when people were looking at an assortment planogram (Chandon et al., 2009). At first glance the numbers might sound small, but in fact these are even higher than what has been reported with in-store observations. A summary of field trip studies showed that shoppers examined an average of 1.2 brands (Burke & Leykin, 2014). An explanation for the small number of brands examined could be that a complete screening of the assortment might be realized even without complete viewing, e.g., due to the familiarity with a brand, combined with either an expectation or a partial viewing of the shelf layout (Russo & Leclerc, 1994). Naturally then, a decrease in the number of fixations was reported when consumers are familiar with the assortment context due to repeated exposure (Bialkova & van Trijp, 2011). In the same study, it was found that the effect of decreased fixations over repeated exposures is valid for all elements featured FOP. Important to point out here is that lab studies reported a strong relation between attention and choice. Brands (Pieters & Warlop, 1999) and products (Bialkova et al, 2014) fixated at most had the highest probability of being selected. In other words, brand choice can to a large extent be predicted from observations of visual attention patterns, as attention mediates consumer choice.

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Consumer attention and choice Concerning real store environment, only few ET studies were performed at the point of sale. One of these studies reported that even a small change in a product’s appearance and/or presentation can have a powerful impact on shopper engagement and purchase (Burke & Leykin, 2014). Consumers who had a picture of a desired brand in mind have been faster in finding the item on a store shelf. Other scholars, however, argued that consumers have fragmented visual attention during grocery shopping, and that the shelf display might not just influence but rather disturb attention (Clement, Kristensen, & Grønhaug, 2013). In the same study, brand elements were not found to be significant visual features influencing the later decision process neither to be a final visual clue in the persuasion. These outcomes question the findings reported in lab studies and call for close comparison from desktop to supermarket shelf, investigating the environmental validity of the visual marketing stimuli. Note however that this is a complex comparison as the approaches differ. In the current study we compare the two approaches for two types of attention driven processing (goal-directed vs. stimulus-driven) and four determinants (brand, product flavour, brand placement and label) recognized as key marketing parameters.

Goal directed vs. stimulus driven processing Attention may be directed towards a stimulus because it is meaningful in relation to consumer’s goals, i.e. goal-directed (top-down) attention (Bialkova & van Trijp, 2011), and/or because the stimulus stands out as particularly salient within the visual field, i.e. stimulus-driven (bottom-up) attention (Bialkova, Grunert, & van Trijp, 2013). Goal-directed vs. stimulus driven attention has been addressed in the psychology literature a long time ago (Norman & Shallice, 1986, 2000; Schneider &

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Consumer attention and choice Shiffrin, 1977; Shiffrin & Schneider, 1977). ET research in marketing also acknowledged the importance of both mechanisms, goal-directed and stimulus-driven. The goal of the viewer interacts with stimulus characteristics to influence looking behaviour (Pieter &Wedel, 2007) and the amount of attention devoted to different parts of the marketing stimuli, for example an advertisement (Rayner et al., 2001). Integrating visual search and choice paradigms, it was shown that decision makers attend preferentially to stimuli with higher goal relevance, and show limited attendance or even ignore stimuli with little or no goal relevance (Bialkova & van Trijp, 2011; Bialkova et al., 2014). Concerning the bottom-up mechanisms, various eye-tracking studies reported that attention is captured by the salient stimuli (Bialkova, Grunert & Van Trijp, 2013), product alternatives (Bialkova & Van Trijp, 2011), attributes and brand features (Bigné et al., 2016; Van der Lans, Pieters, & Wedel, 2008). Therefore, the reasonable question arising here is which parameters determine the assortment context saliency, and thus navigate attention and choice.

Factors driving consumers’ attention and choice Consumers usually enter a store with a particular shopping goal in mind, and even with a shopping list. At the point of purchase, however, they have limited time to examine all alternatives competing for attention, given the complexity and variability of modern retailing. Thus, we expect that only specific brands are inspected based on consumers’ shopping plans and prior knowledge/experience, and that for these, only a limited number of cues will attract consumer’s attention. Brand (Pieters & Warlop, 1998, van der Lans, Pieters, & Wedel, 2008), product type (Chandon et al., 2009, Russo & Leclerc, 1994), product presentation (Bigné, Llinares, Torrecilla, 2016; Burke & Leykin, 2014), and elements featured on the front

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Consumer attention and choice of the package (Bialkova & van Trijp, 2011, Bialkova et al., 2014) have been addressed in previous ET work in order to disentangle what attracts attention most. Therefore, in the following, we will specifically address the role of brand, product flavour, labels and placement. Brand is the most extensively investigated marketing parameter and is assumed to be a key factor navigating where the eyes go, and thus, to determine attention and choice. A high level of attention to a brand and slow eye movements between brands led to additional brand purchases within the same product category (Bigné et al., 2016). The chosen brand received significantly more intra-brand and inter-brand saccades and longer fixation durations than the non-chosen brand, irrespective of task motivation (Pieters & Warlop, 1998). While task motivation (low vs. high involvement) did not modulate brand inspection, in the same study it was reported that consumers select certain cues over others, e.g., the brand name, pictorial and textual information of a brand package. Package design has further been recognised as a bottom-up component of brand saliency, while the top-down component of brand saliency was supposed to reflect out-of-store marketing activities such as advertising (Van der Lans, et al., 2008). Product flavour determines how consumers make comparisons between alternatives and thus derive purchase decisions, as it is well known from the marketing literature. Variety is a key factor enhancing variety seeking (Van Trijp, Hoyer, & Inman, 1996). It was reported however that greater familiarity with a product category can shorten the choice process, as reflected in eye-fixation patterns (Russo & Leclerc, 1994). Furthermore, once consumers choose to shop in a specific category, they follow similar attention-grabbing strategies, i.e., uniformity in patterns over the three product categories explored has been shown in earlier ET research (Russo & Leclerc, 1994).

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Consumer attention and choice Latter studies also reported that essentially identical patterns are observed for different product categories displayed to participants (Chandon et al., 2009). Therefore, understanding what are the attention-grabbing features within a product category is a challenge. Although visual differentiation was pointed out to play a role in managing the product line length (Van der Lans et al., 2008), it is still puzzling how to best present a product. This is especially valid, taken that the visual attention to the shelf is a fast sweep, due to a high number of fixations per second (Bigné et al., 2016). Labels. Communicating specific features and benefits of the product, e.g., by standardized cues may also play a role. Examples of such cues are nutrition labels on food packages, environmental labels, ethical labels and health symbols. In the context of FMCG, nutrition labels have been shown to attract consumer attention, as reflected in the number of fixations and time spent in the particular area of interest, namely the label (Bialkova & van Trijp, 2011). The effect of a nutrition label is modulated by the shopping goal (Bialkova & van Trijp, 2011; Bialkova et al., 2014), consumer’ involvement and self-control (Koenigstorfer, Groeppel-Klein & Kamm, 2014). More attention was allocated to labels communicating the nutrient profile of a product when consumers have to select the healthiest option within the assortment set (Bialkova et al., 2014). The bottom-up stream of attention-getting properties of the label also have been demonstrated by the same work, i.e. products carrying colour-coded (than monochromatic) labels attracted more attention (irrespective of brand and product flavour effects). Brand/product placement within the assortment context has also been reported to play a role in attention and choice. Brands were more likely to be noted and reexamined when they were near the centre of the shelf than when they were located at its extremities (Chandon et al., 2009). However, the effects of shelf position, explored

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Consumer attention and choice in the same study, were mixed. While the top shelf and near the centre positioning improved both attention and evaluation, positioning products on the middle shelves helped attention but without improving evaluation. Left (vs. right) hand side of the shelf positioning did not make a difference to either attention or evaluation. Prior studies, however, reported that consumers tend to use left-right (than right-left) zigzag strategy when searching for a product (Van der Lans et al., 2008). The search strategy is based on the layout of the display, in particular the horizontal organization of product shelves in supermarkets. A plausible explanation for discrepancies in findings of the two studies reported above could be the assortment organization. Another explanation that could be relevant is that both studies are performed in lab, and thus it would be worth exploring what would be the actual pattern at the POP. Put differently, further caution that has to be taken into account is whether brand placement is perceived in the same way at lab and in-store. To test whether and how the above parameters, recognized as key marketing vehicles, determine consumers attention and choice at POP, we explore gaze behaviour in both the lab and the in-store setting. The suggested approach will provide a close comparison of the two streams of results, and thus allow to bridge an important gap in the current body of literature, namely, the need to reconcile ET results from lab and field studies. In particular, we ask: RQ1. Whether lab and in-store results streams come to the same conclusions? RQ2. Which parameters determine the assortment context saliency and thus navigate attention and choice? Are the effects of these parameters consistent in lab and in-store settings? RQ3. Whether and how shopping goal modulates the above parameters in guiding attention and choice?

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Consumer attention and choice To address the above questions, we conducted two consecutive studies, respectively, lab (study 1) and in-store (study2), as described in detail below.

3. Study 1 Participants Thirty students of a German university (10 men, 20 women, age below 35 years) took part in the study for a monetary reward of EUR 5. All had normal or corrected-tonormal vision, and full colour vision (checked prior to the study by the Ishihara colour plates test).

Stimuli Eight muesli bars that differed in brand (Corny and Sirius) and flavours (apple, banana, red fruits, and chocolate) were used. Brand selection was done to assure that we have both a strong and a weak brand. In Germany, Corrny has the highest market share (for this product category) and is the most popular classical brand, whereas Sirius is a private label being less popular. Product flavour selection was also reflected by the products available currently on the market. Each product carried a nutrition label. Taken the great diversity of cereal bars, and the variance of their nutrient profile (Aleksejeva et al., 2017), we dedicated special attention to the level of healthfulness of the product, as reflected in the numbers shown on the nutrition label for calories, saturated fats, sugar, and salt. Considering the label formats available on the market, monochrome and colour-coded guideline daily amount (GDA) label formats were selected for the purpose of the current research. Scans of the original packages were obtained, and nutrition labels were implemented on the packages at a consistent position (down right corner FOP) via

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Consumer attention and choice computer artwork. On each trial the pictures of all products (two per columns and four per row) were displayed on a 40” TV screen, in full colours and real pack size. The brand placement was fixed, Corny-Sirius (left - right). For each trial, the products of one brand received a different labelling system than the other brand, i.e. either monochrome or colour-coded GDAs (respectively left vs. right side of the screen) or the reverse positioning. See Figure 1 for an example of the screen display.

-------------------------------Insert Figure 1 about here --------------------------------

Design and procedure A 2 (Brand: stronger vs. weaker) x 4 (Product flavour: apple, banana, red fruits, and chocolate muesli bar) x 2 (Label: monochrome vs. traffic light colour-coded GDAs) within-participants design was employed. Brand placement was kept constant in this study. Between participants the shopping goal was manipulated, i.e. half of the participants had to select the healthiest product, and the other half a product of their preference. The experiment took place in a quiet room, dimmed during the eye-tracking recordings. Participants were told that the goal of the study is to analyse how

consumers select food products, while their gaze is recorded and therefore a written consent was requested. Participants were seated comfortably at about 1 meter from a TV screen. Between the participant and the TV screen, there was a remote ET device (SMI, Berlin, Germany; sampling rate 50 Hz). Before the stimuli display, a 9-point

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Consumer attention and choice calibration procedure was run, average error in gaze position less than 0.5°(following a procedure described in Bialkova & van Trijp, 2011). The beginning of the experiment was announced with the word “Start” displayed on the screen in self-paced mode. Then an initial trial (where no labels appear) was presented, followed by the assortment trials (where labels appear on products). Trials were presented one by one in a fixed order, each preceded by a fixation cross displayed for 600 ms. Half of the participants had to select the healthiest product in the assortment and the other half the product of their preference. Participants were informed that they have to say aloud the chosen product (e.g., Corny apple, Sirius banana) and to press the space bar of a key board to get the next assortment of eight products. When the participant stated the chosen product and pressed the space bar, the next assortment appeared automatically. An experimenter sitting in the back of the room recorded the answers. The experiment ended with the sentence “Experiment over” displayed on the screen. Then a personal interview took place, followed by a debriefing.

Results Eye-tracking measures. Two ANOVAs explored, respectively, the number of fixations and the total fixation duration per product (means), as a function of Brand, Product flavour, Label and shopping Goal. Concerning the number of fixations, the main effects of Brand (F(1, 28) = 9.43 p < .005), Product flavour (F(3, 84) = 14.71, p < .0001), and Label (F(1, 28) = 8.54, p < .01) were significant. Although there was a tendency for higher number of fixations with health rather than preference goal in mind, the main effect of Goal was not substantiated statistically, p > .1 (see Table 1 for summary of the statistics).

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Consumer attention and choice Products carrying colour-coded GDAs got more fixations than those carrying monochrome GDAs (M = 6.47 vs. M = 5.20). The stronger brand attracted more fixations than its competitor (M = 6.62 vs. M = 5.05). The Brand effect was more pronounced with preference goal in mind, as seen from the marginal interaction Goal by Brand, F(1, 28) = 4.28, p = .048. Figure 2, top panel shows the Number of fixations as a function of Brand, Goal and Label (Appendix A provides the descriptive statistics). Shopping goal also modulated the effect of Product flavour, F(3, 84) = 6.56, p < .0001. Apple flavour product received most fixations, and chocolate least. This effect was strongly pronounced with the health goal in mind, while with a preference goal in mind, this effect disappeared. No other interaction was reliable, all p’s > .1.

-------------------------------Insert Figure 2 about here --------------------------------

Concerning the fixation duration, the main effects of Brand (F(1, 28) = 6.84 p < .01), and Product flavour (F(3, 84) = 16.01, p < .0001) were reliable. The stronger brand attracted longer fixations than its competitor (M = 1784 ms vs. M = 1357 ms). Apple flavour product received longest fixations, and chocolate the shortest. However, this effect was pronounced only with the health goal in mind, as revealed by the significant interaction Product flavour by Goal, F(3, 84) = 5.79, p < .001. The main effect of Label was not reliable (p > .1), but the triple interaction Product flavour, Goal and Label was significant, F(3, 84) = 3.31, p < .05. With health goal in mind, Apple flavour product got the longest fixation duration, and this effect was found with both label formats. With preference goal in mind, Apple got longest fixation duration, but

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Consumer attention and choice only for products labelled with monochrome GDAs. When traffic light colour-coded GDAs appeared, all products seem to get equal attention.

-------------------------------Insert Table 1 about here --------------------------------

Choice made. Loglinear analyses were performed to explore the choice made, as a function of the manipulated factors (Brand, Product flavour, Label and shopping Goal). The main effects of Brand (χ2(1) = 15.69, p < .0001), and product flavour (χ2(3) = 26.11, p < .0001) were significant. The stronger brand outperformed the weaker one, being selected in 75% of the cases. Apple flavour product was selected in the majority of the cases. However, this effect was only pronounced with the health goal in mind, as reflected in the significant interaction Goal by Product flavour, χ2(3) = 18.13, p < .0001. With preference goal in mind, the four flavours were selected with equal probability. Neither the main effect of Label nor Goal reached significance, but the interaction Goal by Label was reliable, χ2(1) = 9.72, p < .005. With health goal in mind, products carrying colour-coded GDAs were selected in the majority of the cases. With preference goal in mind, the probability of selecting a product did not depend on the label format.

4. Study 2 Participants One hundred twenty people (29 men; median age: 30 years, ranging from 16 to 69 years) who are responsible for the grocery shopping in their household completed the 16

Consumer attention and choice study for a monetary reward of EUR 5. All participants had full colour vision (tested prior to the study by the Ishihara colour plates) and none of the participants was wearing contact lenses or glasses. Data from one participant were excluded from further analyses, as they have not met the inclusion criteria (cut off - minimum fixation duration of 80 ms).

Stimuli The same brands and the same products as used in Study 1 were selected for Study 2. Again, monochrome and traffic light colour-coded GDA label formats were used (although a slightly different scheme in comparison to study 1), and thus we could test how label colour (namely monochrome vs. colour coded) played a role. The values shown on the nutrition labels (e.g., for calories, saturated fats, sugar and salt) were adopted from the manufacturers’ actual nutrient tables. Computer artwork was used to create the front-of packs, which were printed on stickers and put on the products so they looked like the real products. The front package of the products was 15.4 × 14.4 cm in size. The label was positioned in the down right corner of the product, covering a surface of 2.2 × 4.6 cm. The products – two per column and four per row – were arranged on a shelf (80 cm width, 200 cm height) where no other products were located (see Figure 3 for an example). To check the environmental validity of the mock-up products, at the end of the survey, two open-ended questions asked the participants if they had noticed anything unusual during the shopping trip, and if any of the products appeared weird to them. As none of the participants mentioned that the products or the nutrition labels were manipulated, we assume that the stimuli were considered realistic by the consumer sample.

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Consumer attention and choice -------------------------------Insert Figure 3 about here --------------------------------

Design and Procedure An assortment consisting of 2 (Brand: stronger vs. weaker) x 4 (Product flavour: apple, banana, red fruits, and chocolate muesli bar) was shown to all participants. The Label format (monochrome GDA system vs. traffic light colour-coded GDAs) was a between-participants factor. Brand placement was manipulated across participants, i.e. half of the participants were presented with Brand placement Corny-Sirius (respectively left vs. right side of the shelf) and the other half of the participants saw the reverse placement. Consumers were recruited right after entering a grocery store (located in Southern Germany). The recruitment took place on weekdays from 9am to 6pm. Consumers were informed that the study was about their orientation behaviour in supermarket environments, and were led to the mock up store of the retailer, reflecting real shopping environment. Each participant filled in and signed an informed consent form prior to the participation in the study. To assess participants’ attention, we used the monocular, pupil corneareflection based system (SMI, Berlin, Germany; sampling rate 25 Hz). ET glasses were used, which allows individuals free movements between the shelves. ET resolution was 0.1°, and gaze accuracy between 0.5 and 1°. The calibration of the system was performed while the participants were seated and had a fixed distance of 60 cm (measured at eye level) to a DIN A1 white board. The board showed five black crosses, one in the middle, and four in a virtual rectangle (28 cm × 20 cm). If the calibration 18

Consumer attention and choice was successful, participants were next instructed to purchase some pre-defined food products. Participants received a shopping list with four products on it (three of which were filler products) and were asked to buy a product of their choice, one from each product category. The reason to focus on selecting a product on their choice (note that in the lab, study 1, half of the participants had to select the healthiest option) was to keep the in-store behaviour as close as possible to the actual behaviour consumers have in a supermarket. A shopping basket was given to the participants and they were told that they should behave as they would normally do, and that if they want, they could actually buy any product they get during the shopping trip from their monetary incentive. To assure that participants walk normally through the mock-up store, and to keep a constant distance to the shelf, a carpet (40 cm in width) was placed on the floor, in 40 cm distance to the shelf. The shelf with the muesli bars was approached from the left side. Participants were instructed to come back to the experimenter, after finishing their shopping. The food choices were recorded, a personal interview was conducted and the participants were debriefed at the end of the study. The coding of the video recording was done with The Observer XT 10 software (Noldus IT, Wageningen, The Netherlands). As the video sequences were coded manually, coding rules were developed and the coders were trained to apply these rules (following a procedure described in Koenigstorfer, Groeppel-Klein & Kamm, 2014).

Results

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Consumer attention and choice Eye-tracking measures. Two ANOVAs explored, respectively, the number of fixations and fixation duration per product (means), as a function of Brand, Product flavour, Label and brand Placement. Concerning the mean number of fixations, the main effects of Brand (F(1, 115) = 37.60, p < .0001), and Product flavour (F(3, 345) = 5.23, p < .005) were significant. The effect of Label was not significant (p > .3), but the interaction Brand by Label was at the margin, F(1, 115) = 4.31, p = .040. Again, the stronger brand received a higher number of fixations, in comparison to its competitor (M = 6.24 vs. M = 4.64). This effect was more pronounced for monochrome than for colour-coded GDAs (see Figure 4, Top panel). The interaction Product flavour by Label was also reliable, F(3, 345) = 7.03, p < .001. Chocolate and banana flavour products received higher number of fixations (in comparison to apple and red fruits), but this effect was only pronounced for colour-coded GDAs. The main effect of brand Placement was not significant (p > .2), but the interaction Brand by brand Placement was, F(1, 115) = 12.78, p < .001. The stronger Brand received a higher number of fixations when being positioned on the right (than left) side of the shelf.

-------------------------------Insert Figure 4 about here --------------------------------

Concerning the fixation duration, the main effects of Brand (F(1, 115) = 20.66, p < .0001) and Product flavour (F(3, 345) = 6.59, p < .0001) were significant. Again, the main effect of Label was not reliable (p > .1), but the interaction Product flavour by Label (F(3, 345) = 5.72, p < .001) was significant. Fixation duration was longer for

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Consumer attention and choice chocolate and banana flavour products (in comparison to the other two products), but this effect was only pronounced for colour-coded GDAs formatting. The interaction Brand by brand Placement was also significant, F(1, 115) = 18.55, p < .0001. The stronger Brand received longer fixations when being positioned on the right (than left) side of the shelf.

-------------------------------Insert Table 2 about here --------------------------------

Choice made. The Loglinear analyses were performed as a function of the manipulated factors (Brand, Product flavour, Label and brand Placement). The results showed significant main effects of Brand (χ2(1) = 22.58, p < .0001), and Product flavour (χ2(3) = 18.65, p < .0001). Chocolate flavour product was selected in 41% of the cases. The Brand Corny outperformed the Brand Sirius, being selected in 71% of the cases. The stronger brand was chosen more often, when being positioned on the right (than left) side of the shelf, as reflected in a significant interaction Brand by Placement, χ2(1) = 17.45, p < .0001. A slightly different look at this outcome shows that the probability to select the weaker brand was higher when positioned on the left side of the shelf (i.e. the side from which the consumers approached the shelf).

5. Discussion The current study faced an important gap in the literature - the need to reconcile ET results from lab and field studies. In particular, we investigated the effect of key parameters of an in-store setting, i.e. brand, product flavour, brand placement, and label

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Consumer attention and choice on consumer attention and choice. The results of two studies conducted in lab and in real store settings were compared, and thus, shedding much needed light on the environmental validity of lab studies employing ET. We explored gaze behaviour (in terms of number of fixations and fixation duration) and purchase decisions in the context of FMCG. The results showed that brand, product and placement are crucial determinants in consumers attention and choice. Placement interplayed with brand strength in the retail environment. Shopping goal and label formats also contributed to variation in the observed patterns, as discussed in details below.

From desktop to shelf Several lab studies employed eye-tracking measures to explore what drives consumers’ attention (e.g., Bialkova & van Trijp, 2011; Bigné et al., 2016; Van der Lans et al., 2008; Wedel & Pieters, 2008), choice (e.g., Chandon et al., 2009; Meißner & Decker,2010; Russo & Leclerc, 1994), and their interplay (e.g., Bialkova et al., 2014; Pieters & Warlop, 1999). However, only few ET studies have been carried out in a real store setting (e.g., Burke & Leykin, 2014; Clement et al., 2013), and thus calling further investigation. Yet, the question is what is the environmental validity of such studies from lab to in-store. While lab studies have shown that consumers’ attention is a crucial factor driving choice (e.g., Bialkova et al., 2014; Pieters & Warlop, 1999), based on an instore study it has been argued that consumers have fragmented visual attention, and that brand elements are not significant visual features influencing the later decision process (Clement et al., 2013). The authors further claimed that the shelf display might not influence but rather disturb attention (Clement et al., 2013). These in-store

22

Consumer attention and choice observations seriously questioned the findings reported in several lab studies, and thus called for additional exploration. The present study addressed this challenge by comparing results from a lab study with those of an in-store study. Our results show a similar pattern in both settings, and thus answering RQ1. Whether lab and in-store results streams come to the same conclusions and if so, whether this leads to increase of the validity and relevance of ET data? Table 3 presents a summary of the main outcomes and in the following, details on the observed patterns are provided while reflecting in accordance with the relevant theories.

-------------------------------Insert Table 3 about here --------------------------------

Determinants of consumer attention and choice In line with RQ2: Which parameters determine the assortment context saliency, and thus navigate attention and choice, and are these effects consistent in both settings (lab and in-store), the results are clear in showing that: Brand, product flavour and placement (on shelf) are crucial for attention and thus the purchase decision. Nutrition labels displayed front of pack and the shopping goal further modulated attention and choice, as described in detail below. The stronger brand outperformed the weaker brand, being the one receiving more attention and choice. The brand effect was significant in both, the lab (study 1) and the in-store (study 2) environment, and reflected the number of fixations, fixation duration and choice made. The chosen brand (compared to the non-chosen) received

23

Consumer attention and choice significantly more fixations and longer fixation durations, in line with previous findings that a high level of attention to a brand leads to additional brand purchases (Bigné et al., 2016). While prior studies reported that the brand effect appears irrespective of task motivation (Pieters & Warlop, 1998), current results demonstrate that the shopping goal modulates brand choice. When consumers had to select the healthiest option within the assortment, they dedicated equal attention (e.g., reflected in number of fixations) to both brands. By contrast, when consumers had to select a product based on their preference, the stronger brand totally outperformed its competitor. These interesting findings in line with RQ3, Whether and how shopping goal modulates attention and choice, could be well employed by marketers to enhance brand design towards desired attention-grabbing properties and thus brand choice. Concerning placement, when positioned on the right side of the shelf, the stronger brand received higher number of fixations and longer fixation duration. The probability of selecting the stronger brand was also higher when being positioned on the right side of the shelf. Although the role of placement has been addressed in previous ET studies, the findings have been controversial (Chandon et al., 2009; Van der Lans et al., 2008). Note that the prior studies were desktop studies and thus, the only way to explore the environmental validity of the placement effect is through instore observation. In our study 2, participants had the opportunity to behave as they normally do during their shopping (e.g., walking through the shelves, and to purchase the product they select). In this respect, our work makes a significant contribution to advance the understanding of visual marketing stimuli effect from desktop to shelf. In particular, we found that the stronger brand received more attention and was selected more often when being positioned on the right side of the shelf. Note however that participants in the current field study approached the shelf from the left side. Thus, it

24

Consumer attention and choice might be the case that they had the opportunity to longer observe the right side of the shelf (than the left side). Whether the this is the case, a follow up study could check, namely, probing how the direction from which the shelf is approached influences consumers attention and choice. The product flavour played a significant role in grabbing attention and driving choice. This effect was significant in both the lab (study 1) and in-store (study 2) settings, and reflected in the number of fixations, fixation duration and choice made. Note, however, that the product variety effect was modulated by the shopping goal. With a health goal in mind, the apple muesli bar was the product receiving highest number of fixations, longest fixation durations, and was chosen in the majority of the cases (study 1). With a preference goal in mind the picture was different, as reflected in the significant goal by product interaction. Chocolate and banana muesli bars (than other two products) got a higher number of fixations and longer fixation duration, and chocolate was the product selected at most (study 2). These findings are in line with previous studies showing that the goal of the viewer influences the visual inspection (Pieter & Wedel, 2007; Rayner et al., 2001). More precisely, decision makers attend preferentially to stimuli with higher goal relevance (Bialkova & van Trijp, 2011; Bialkova et al., 2014). The nutrition labels displayed FOP also modulated attention and choice. There was a tendency for better attention capture with colour-coded GDAs. Products carrying colour-coded (than monochromatic) labels were selected more often, but this effect was only pronounced with a health goal in mind (study 1). Taken that colour is a bottom-up stream feature (Bialkova et al., 2013), current results support previous findings demonstrating that attention is directed towards the most salient information,

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Consumer attention and choice especially when this information is meaningful in relation to the shopping goal (Bialkova & van Trijp, 2011). Labels explicitly communicate the benefits of a product (brand), and thus, provide appropriate knowledge concerning its value. In this respect, the current study 2 brings further understanding on the way visual marketing stimuli (e.g., labels featured FOP) interplay with other parameters (e.g., brand itself, product attributes). It seems that for the strong brand, label formatting did not matter. By contrast, for the weak brand, products carrying colour coded (rather than monochromatic) labels were preferred. The interaction Product by Label was also reliable. Chocolate and banana received higher number of fixations and longer fixation duration (in comparison to the other two products), and this effect was pronounced with colour-coded label formatting. Colours seem to provide additional information, lifting value and making a product/brand more attractive, which could be used as a persuasive tool. Finally, we have to note that we tried to keep the stimuli in both studies as similar as possible. The reason for this was the need to have comparable settings in order to properly address the main objective of the current study, namely, to reconcile lab and in-store ET data streams. The results are clear in showing that the effects of Brand, Product flavour and Label followed similar patterns across both studies (lab and in-store), and thus, supporting the notion for environmental validity of the ET lab studies. We have to point out here that Brand placement showed a significant effect in the real shelf positioning, especially the interplay between placement and brand strength. However, lab studies (previous observations, including also studies from our lab) have not been able to capture such an effect, as discussed in section brand placement in details.

26

Consumer attention and choice These are interesting outcomes, highlighting the contribution of the current research. Our study is just the first step in a new avenue to investigate the environmental validity of results coming from two different streams, namely lab and supermarket. Further research could look at pack size (e.g., shelf ready impulse, economy, family), advertisements, (price) promotions, profit generation, image builders, cashier zone itself, etc. Current outcomes could be taken as a corner stone to build around exploration, and thus, to provide further insight on the influence of Marketing communication mix at the POP when employing ET.

6. Conclusion While lab eye-tracking studies investigating consumer attention and choice when selecting FMCG have been plenty, the number of studies conducted in a real store setting has been much more limited. The current paper addresses this limitation and in particular we focus at the environmental validity of ET research by conducting two studies on consumer attention and choice, one in the lab and one in the store, with the same stimulus material. We found largely converging results of the two studies: 1) The strength of the brand and the product variety determined where the attention goes and thus the purchase decision. This was reflected in higher number of fixations and longer fixation duration. The more attention a product/brand received, the higher was the probability to be selected. These effects were similar for both, desktop and shelf studies. 2) Explicitly communicating specific product benefits through elements featured FOP (here, nutrition labels) increased attention and influenced purchase outcome, but these effects were contingent on the purchase goals. 3) Bottom-up stream of information (here colour-coded labels and placement) further lifted attention and purchases, but

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Consumer attention and choice these effects were modulated by the strength of the brand. 4) Top-down processing (shopping goal and prior knowledge) also played a role in determining which product gets most attention and is chosen most often. 5) Consumers followed similar patterns, in both lab and in-store studies concerning brand, product variety and label effects. 6) Placement emerged as significant determinant in the in-store environment. 7) Its effect should be further explored in combination of other marketing commination tools at the POP, like advertisements, (price) promotions, cashier zone itself. In sum, ET is a powerful tool to align observations and to provide in-depth explorations on the mechanism underlying consumers’ attention and subsequent choice. Current work showed that both streams of results (lab and in-store when using same stimuli material) lead to similar conclusion. Thus, we could say that ET studies that are concurrently done in the lab and in the store could further strengthen our confidence in the validity and usefulness of the results obtained.

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Consumer attention and choice Acknowledgement The data collection was supported by the 7th EU Framework Programme Small Collaborative Project FLABEL (Contract n° 211905). The content of the paper reflects only the views of the authors; the European Commission is not liable for any use that may be made of the information contained in this paper. We thank Rebecca Mascioni, Julia Math, Sabrina Trautmann and Viktoria Dehnhard for the assistance with collecting the data.

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Consumer attention and choice References Aleksejeva, S., Siksna, I., and Rinkule, S. (2017). Composition of Cereal Bars. Journal of Health Science, 5, 139-145. Bialkova, S., Grunert, K.G., Juhl, H.J., Wasowicz-Kirylo, G., Stysko-Kunkowska, M., and van Trijp, H. (2014). Attention mediates the effect of nutrition label information on consumer’s choice: Evidence from a choice experiment involving eye-tracking. Appetite, 76, 66-75. Bialkova, S., K.G. Grunert, and van Trijp, H. (2013). Standing out in the crowd: the effect of information clutter on consumer attention for front-of-pack nutrition labels. Food Policy, 41, 65-74. Bialkova, S., and van Trijp, H. (2011). An efficient methodology for assessing attention to and effect of nutrition information front of pack. Food Quality and Preference, 22, 592-601. Bigné, E., Llinares, C., and Torrecilla, C. (2016). Elapsed time on first buying triggers brand choices within a category: A virtual reality-based study. Journal of Business Research, 69, 1423–1427. Burke, R.R., and Leykin, A. (2014). Identifying the drivers of shopper attention, engagement, and purchase. In Grewal, D., Roggeveen, L.A., NordfÄlt, J. (eds.). Shopper Marketing and the Role of In-Store Marketing (Review of Marketing Research, Volume 11) Emerald Group Publishing Limited, pp. 147–187. Chandon, P., Hutchinson, J.W., Bradlow, E.T., and Young, S.H. (2009). Does in-store marketing work? Effects of the number and position of shelf facings on brand attention and evaluation at the point of purchase. Journal of Marketing, 73(4), 1– 17. Clement, J., Kristensen, T., and Grønhaug, K. (2013). Understanding consumers’ instore visual perception: The influence of package design features on visual attention. Journal of Retailing and Consumer Services, 20, 234–239 Engel, J. F., Blackwell, R. D., and Miniard, P. W. (1995). Consumer Behavior (8th ed.). Orlando, FL: The Dryden Press. Hawkins, S. A., Best, R., and Coney, K. A. (1992). Consumer Behavior: Implications for Marketing Strategy (5th ed.). New York: McGraw-Hill/Irwin.

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Consumer attention and choice Koenigstorfer, J., Groeppel-Klein, A., and Kamm, F. (2014), Healthful Food Decision Making in Response to Traffic Light Color-Coded Nutrition Labeling, Journal of Public Policy & Marketing, 33 (1), 65-77. Krajbich, I., Armel, C., and Rangel, A. (2010). Visual fixations and the computation and comparison of value in simple choice. Nature Neuroscience, 13(10), 1292– 1298. Meißner, M., and Decker, R. (2010). Eye-tracking information processing in choice based conjoint analysis. International Journal of Market Research, 52(5), 591– 610. Norman, D. A., and Shallice, T. (1986). Attention to action: Willed and automatic control of behavior. In R. J. Davidson, G. E. Schwartz, & D. Shapiro (eds.). Consciousness and Self-regulation (Vol. 4, pp. 1–18). New York: Plenum. Norman, D. A., and Shallice, T. (2000). Attention to action: Willed and automatic control of behavior. In M. S. Gazzaniga (ed.), Cognitive Neuroscience. A Reader (pp. 325–402). Malden, MA: Blackwell. Peter, J. P., and Olson, J. C. (1998). Consumer Behavior and Marketing Strategy. Boston, MA: McGraw-Hill. Pieters, R., and Warlop, L. (1999). Visual attention during brand choice: The impact of time pressure and task motivation. International Journal of Research in Marketing, 16, 1–16. Pieters, R., and Wedel, M.(2004). Attention capture and transfer in advertising: Brand, pictorial, and text size effects. Journal of Marketing, 68(2), 36–50. Pieters, R., and Wedel, M. (2007). Goal control of attention to advertising: The Yarbus implication. Journal of Consumer Research, 34(2), 224–233. Rayner, K., Rotello, C., Stewart, A., Keir, J., and Duffy, S. (2001). Integrating text and pictorial information: Eye movements when looking at print advertisements. Journal of Experimental Psychology: Applied, 7, 219–226. Russo, J. E., and Leclerc, F. (1994). An eye-fixation analysis of choice processes for consumer nondurables, Journal of Consumer Research, 21, 274–290. Schiffman, L., and Kanuk, L. L. (2004). Consumer Behavior (8th ed.). Pearson Prentice Hall, NJ. Schneider, W., and Shiffrin, R. M. (1977). Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review, 84(1), 1–66. 31

Consumer attention and choice Shiffrin, R. M., and Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending, and a general theory. Psychological Review, 84(2), 127–190. Shimojo, S., Simion, C., Shimojo, E., and Scheier, C. (2003). Gaze bias both reflects and influences preference. Nature Neuroscience, 6(12), 1317–1322. Solomon, M., Bamossy, G., and Askegaard, S. (2002). Consumer Behaviour: A European Perspective. Pearson Prentice Hall, NJ. Van der Lans, R., Pieters, R., and Wedel, M. (2008). Competitive brand salience. Marketing Science, 27(5), 922–31. Van Trijp, H. C., Hoyer, W. D., & Inman, J. J. (1996). Why switch? Product category: Level explanations for true variety-seeking behavior. Journal of Marketing Research, 33(3), 281–292. Wedel, M., and Pieters, R. (eds.) (2008). Visual Marketing. From Attention to Action. New York: Taylor & Francis.

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Consumer attention and choice Table 1. Summary of the statistics for Study 1 (only significant interactions reported) Number of fixations

Fixation duration

F(1, 28) = 9.43 p < .005

F(1, 28) = 6.84, p < .01

χ2(1) = 15.

F(3, 84) = 14.71, p < .0001

F(3, 84) = 16.01, p < .0001

χ2(3) = 26.

Label

F(1, 28) = 8.54, p < .01

p > .1

χ2(1) = 3.

Goal x Brand

F(1, 28) = 4.28, p = .048

p > .1

p

Goal x Product

F(3, 84) = 6.56, p < .0001

F(3, 84) = 5.79, p < .001

χ2(3) = 18.

p > .2

p > .1

χ2(1) = 9.

Brand Product

Goal x Label

Choi

33

Consumer attention and choice

Table 2. Summary of the statistics for Study 2 (only significant interactions reported) Number of fixations

Fixation duration

Choice made

F(1, 115) = 37.60, p < .0001

F(1, 115) = 20.66, p < .0001

χ2(1) = 22.58, p < .0001

F(3, 345) = 5.23, p < .005

F(3, 345) = 6.59, p < .0001

χ2(3) = 18.65, p < .0001

p > .3

p > .1

p > .3

F(1, 115) = 4.31, p =.040

p > .1

Brand x Placement

F(1, 115) = 12.78, p < .001

F(1, 115) = 18.55, p < .0001

χ2(1) = 17.45, p < .0001

Product x Label

F(3, 345) = 7.03, p < .001

F(3, 345) = 5.72, p < .001

p > .1

Brand Product Label Brand x Label

χ2(1) = 3.54, p = .060

34

Consumer attention and choice

Table 3. Summary of the main outcomes Manipulated parameters Study1 Lab Brand (strong vs. weak) Sig.

Study 2 In-store Sig.

Product (4 flavors)

Sig.

Sig.

Label (2 types)

Sig.

ns.

Brand Placement (left vs. right) Shopping goal (health vs. preference)

na

ns.

ns.

na

Brand x Placement

na

Sig.

Goal x Product

Sig.

na

Attention

Choice

Effects

The stronger brand attracts more attention Best selected product attracts attention at most Products carrying colourcoded GDAs and health mark (study1) got more attention

The stronger brand was selected more often Product attracting attention at most was the selected one Products carrying colourcoded GDAs and health mark were preferred (tendency)

Consistent Consistent *Consistent result for preference goal (ns. effect) See comment for Brand x Placement

Tendency for longer fixation with health than preference goal The stronger brand received more attention when positioned on the right side of the shelf Apple flavour product received highest attention (with health goal) Chocolate flavour product received highest attention (with preference goal)

The stronger brand was selected more often when positioned on the right side of the shelf Apple flavour product was selected at most (with health goal) Chocolate flavour product was selected at most (with preference goal)

New outcome

*Consistent result for preference goal in both studies

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Consumer attention and choice Figure captions Figure 1. Example of the assortment context as displayed in Study 1 (placement Corny-Sirius) Figure 2. Mean number of fixations per product (Top panel); Mean fixation duration per product (Middle panel); and Choice made (Bottom panel) in Study1, as a function of Brand (A vs. B) and the nutrition Labelling format (monochrome GDA vs. colour coded GDA), respectively for Health shopping goal (Left panel), and Preference shopping goal (Right panel) Figure 3. Example of the assortment context as shown in Study 2 (placement CornySirius) Figure 4. Mean number of fixations per product (Top panel); Mean fixation duration per product (Middle panel); and Choice made (Bottom panel) in Study 2, as a function of Brand (A vs. B) and the nutrition Labelling format (monochrome GDA vs. colour coded GDA), for Preference shopping goal

36

Consumer attention and choice Figure 1. The assortment context as displayed in Study 1(placement Corny-Sirius)

37

Consumer attention and choice Figure 2. Mean number of fixations per product (Top panel); Mean fixation duration per product (Middle panel); and Choice made (Bottom panel) in Study1, as a function of Brand (A vs. B) and the nutrition Labelling format (monochrome GDA vs. colour coded GDA), respectively for Health shopping goal (Left panel), and Preference shopping goal (Right panel)

10

Preference Goal Monochrome ColourCoded

8 6 4

2

Number Fixations

Number Fixations

Health Goal

0

10 8 6 4

2 0

Brand A

Brand B

Brand A

3000

Monochrome ColourCoded

2500 2000 1500 1000 500 0 Brand A

3000

2000 1500 1000 500 0

Brand B

Brand A

Brand B

Preference Goal 100

Monochrome ColourCoded

Choice made (%)

80

Monochrome ColourCoded

2500

Health Goal 100

Brand B

Preference Goal

Fixation Duration (ms)

Fixation Duration (ms)

Health Goal

Choice made (%)

Monochrome ColourCoded

60 40 20 0

Monochrome ColourCoded

80 60 40 20 0

Brand A

Brand B

Brand A

Brand B

38

Consumer attention and choice Figure 3. The assortment context as shown in Study 2 (placement Corny-Sirius)

39

Consumer attention and choice Figure 4. Mean number of fixations per product (Top panel); Mean fixation duration per product (Middle panel); and Choice made (Bottom panel) in Study 2, as a function of Brand (A vs. B) and the nutrition Labelling format (monochrome GDA vs. colour coded GDA), for Preference shopping goal

Number Fixations

Preference Goal 10

Monochrome ColourCoded

8 6 4 2 0 Brand A

Brand B

Fixation Duration (ms)

Preference Goal 3000

Monochrome ColourCoded

2500 2000 1500 1000 500 0 Brand A

Brand B

Preference Goal

Choice made (%)

100

Monochrome ColourCoded

80 60 40 20 0 Brand A

Brand B

40

Consumer attention and choice Appendix A. Total number of fixations per product (means) and Total fixation duration per product (means), as a function of Brand (A vs. B) and the nutrition Labelling format (monochrome GDA vs. colour coded GDA), respectively for Health and Preference shopping goal (Study 1). Study 1

Number of fixations per product

Fixation duration per product (ms)

Means (SE)

Means (SE) HEALTH goal

LABEL

Monochrome

Colour-coded

Monochrome

Colour-coded

Brand A

5.44 (.87)

8.65 (1.24)

1611 (.29)

2402 (.37)

Brand B

6.44 (1.19)

6.71 (.89)

1828 (.36)

1800 (.26)

PREFERENCE goal Brand A

5.66 (.81)

6.72 (1.16)

1512 (.27)

1612 (.35)

Brand B

3.35 (1.12)

3.81 (.83)

949 (.34)

849 (.24)

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Consumer attention and choice Appendix B Total number of fixations per product (means) and Total fixation duration per product (means), as a function of Brand (A vs. B) and the nutrition Labelling format (monochrome GDA vs. colour coded GDA), for Preference shopping goal (Study2).

Study 2

Number of fixations per product

Fixation duration per product (ms)

Means (SE)

Means (SE)

PREFERENCE goal LABEL

Monochrome

Colour-coded

Monochrome

Colour-coded

Brand A

6.26 (.49)

6.22 (.49)

1373 (.14)

1537 (.14)

Brand B

4.11 (.40)

5.16 (.38)

987 (.12)

1322 (.12)

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Consumer attention and choice 

Two eye-tracking studies (desktop and supermarket shelf) are conducted



Fixation duration, number of fixations, and the consumer's choice were recorded



Results show that brand and product are leading criteria driving attention and choice



Shopping goal, labels, brand placement contributed to variation in observed patterns

43