Consumer Research

Traditional consumer research is costly and time consuming because it involves mocking up physical stores, shelves, and products. With eye-tracked VR headsets however, there is significantly less overhead, a flexibility to try many variations, and the convenience of having analytics results calculated instantly from within the VR application.

Understanding the attention and decision-making processes of customers is invaluable for a business, and eye tracking analysis brings this to the table. Using eye and attention data, companies can make well-informed decisions to increase sales. You can read more about using eye tracking for marketing and user research.

You can also take a look at our Commercial Analytics Prototype.

Branding and Package Design

Traditional marketing research methods like surveys and focus groups don’t always paint the full picture when it comes to consumer behavior and what influences purchase decisions. Eye tracking can help better understand consumers by analyzing the gaze behavior of the consumers.

Unilever is an FMCG company which produces food and household items and owns more than one thousand brands. They use eye tracking to understand what attracts consumer attention in-store, and by seeing where shoppers look and understanding what package design elements are most effective, the company can influence purchase decisions at the shelf, achieving a competitive advantage and improving ROI.

Jeroen van der Kallen, Customer Insight and Innovation Manager Europe, Unilever:

“Using eye tracking gives you the opportunity to look through the consumer’s eyes, so instead of only listening to an opinion we now see the analysis…and when we need a specific answer to a question, we use a lot of eye tracking because eyes don’t lie."

Read more about how Unilever improves their products with eye tracking.

Other examples include a study that explored how much attention teenagers pay to health warnings in cigarette advertisements. Results showed the new health warnings attracted more readers and were noticed faster than the others, as well as revealing a significant relationship between eye-tracking measures, like how fast warnings were noticed and how long the participants paid attention to them, and masked recall of the warning content.1

Eye tracking has also been used to investigate optimal branding in TV commercials. In a study on over 2000 participants, eye tracking was used to predict attention and attention dispersion of various commercials and brand positions within commercials.2

Wayfinding and Store Layout

Munich Airport, awarded the coveted title of “Europe’s Best Airport” 12 times, has been using eye tracking to better understand their travelers and to improve wayfinding in the airport. Some of the elements studied with eye tracking is visibility - whether signs were positioned in a way that they could be seen properly; attention - if travelers did visually engage with signs and if so, for how long and with what parts; and understanding - whether travelers correctly understood the information the sign was designed to communicate.

A study revealed that passengers largely ignored information on navigation signage that wasn’t relevant to their journey and as a result the airport adjusted instructional floor signage. Furthermore, the effectiveness of dynamic digital displays was validated by the study results.

Read more about the Munich Airport wayfinding study.

Similarly, eye tracking has been used to understand if attention is paid to situated displays in public spaces. Studies has shown that situated displays are mostly just glanced at and often from quite far away, indicating design implications when designing these.3

Moreover, since the human brain has a limited capacity for perceptual stimuli, studies have explored the relationship between abundant in-store stimuli and limited perceptual capacity. Findings show that consumers have fragmented visual attention during grocery shopping, and that their visual attention is simultaneously influenced and disrupted by the shelf display. Physical design features such as shape and contrast dominate the initial phase of searching.4

Customer Informational Processing

Eye tracking data over the course of a shopping experience can be collected and then used to improve the customer experience.

One example of this is collecting eye tracking data during web navigation, using this implicit data to capture user interest and then recommend and suggest other web documents to the user. This method was found to enhance the navigation experience for users in about 73% of the cases.5

Another example is using eye tracking to determine how different designs of E-commerce product listings, where information on multiple products are displayed, is being perceived by consumers. In this comparison study between matrix versus list presentation, list presentation was associated with lower cognitive load and more economic product selections. Furthermore, eye tracking data suggests that list presentation triggers comparison processes which could account for the differences found.6

  1. Krugman, Dean M.. “Do adolescents attend to warnings in cigarette advertising? An eye-tracking approach.” (1994). ↩︎

  2. Teixeira, Thales & Wedel, Michel & Pieters, Rik. (2010). Moment-to-Moment Optimal Branding in TV Commercials: Preventing Avoidance by Pulsing. Marketing Science. 29. 783-804. 10.1287/mksc.1100.0567. ↩︎

  3. Dalton, Nick & Collins, Emily & Marshall, Paul. (2015). Display Blindness? Looking Again at the Visibility of Situated Displays using Eye Tracking. 10.1145/2702123.2702150. ↩︎

  4. Clement, Jesper & Kristensen, Tore & Grønhaug, Kjell. (2013). Understanding consumers’ in-store visual perception: The influence of package design features on visual attention. Journal of Retailing and Consumer Services. 20. 234–239. 10.1016/j.jretconser.2013.01.003. ↩︎

  5. Giordano, D. & Kavasidis, Isaak & Pino, Carmelo & Spampinato, Concetto. (2012). Content based recommender system by using eye gaze data. 10.1145/2168556.2168639. ↩︎

  6. Schmutz, Peter & Roth, Sandra & Seckler, Mirjam & Opwis, Klaus. (2010). Designing product listing pages—Effects on sales and users’ cognitive workload. Int. J. Hum.-Comput. Stud.. 68. 423-431. 10.1016/j.ijhcs.2010.02.001. ↩︎