Interest in shopper research has significantly risen since it first appeared, especially in the realm of online shopping and e-commerce during the COVID-19 pandemic.
Shopper research is fundamentally based on gaining shopper insights, i.e., learning about their attitudes and behavior.
In particular, shopper research is path-to-purchase research which takes an in-depth look into how customers behave in-store and near-store, helping retailers understand better how the shopping environment affects shoppers’ perception, experience, and purchase decisions.
Aside from behavioral measures, such as queries, observations, and polls, eye tracking measures have also gained popularity in researching shoppers for several reasons:
1. Retailers and manufacturers can better understand what shoppers’ attention is being drawn to.
2. They can use this information to tailor the shopping environment to their customers’ preferences.
3. Furthermore, they can test and improve on their new products before releasing them.
Eye tracking can provide retailers with a knowledge base of the most valuable resource in today’s world — consumers’ attention.
What shopper insights can you gain with eye tracking?
Utilizing insights from store research in order to understand consumer behavior has been around for more than 75 years, and it has become increasingly important as the tools to gain shopper insights have improved.
As one of these helpful tools, eye tracking has one specific benefit compared to behavioral methods, as it can provide a view of the consumers’ subconscious.
Essentially, as Gerald Zaltman, a Harvard Business School professor, would state, about 95% of purchasing decisions are made in the subconscious.
Behavioral methods of research are not easily capable of addressing this subconscious decision-making process effectively. Moreover, it has been shown that buyers don’t always end up purchasing the products that they report preferring.
On the other hand, eye tracking research enables retailers to understand what consumers might wish to purchase before they even do so. By analyzing visual pathways, fixations, and particular areas of interest, eye tracking data provides insight into consumers’ preferences. Studies have shown we tend to prefer objects that we look at longer and often return our gaze to.
This type of insight can be valuable in shelf organization, product packaging, advertisement placement, and more. With research showing that up to 70% of purchase decisions are made inside the store, both marketers and retailers have found eye tracking to be a much-needed source of in-store shopper insights.
How can eye tracking be used in shopper research?
Eye tracking can be used to assess several questions to gain insights about shoppers:
- Where people are most commonly looking within a specific display of products on shelves, parts of packaging, signs, etc.
- What objects are they looking at and
- For how long they are looking at these objects, as well as
- How often they change their gazing point or
- How often they blink and even
- In what order they look at different objects.
All of this information can be useful to analyze further what aspects of, e.g., a product display, packaging, or signage, can be designed differently to attract consumers’ attention and “capture” it for as long as possible.
In practice, the most commonly used eye tracking tool for shopper research are wearable eye tracking glasses. Wearables are the most convenient and natural way to conduct eye tracking research in an everyday environment, allowing for this type of research to have strong ecological validity.
However, there are other methods regarded as simulations but can lead to important conclusions within less time. Research can be conducted with a VR headset (eye tracker included), which allows for an immersive shopping experience that truthfully mimics natural settings.
Another, more affordable option can be using a screen-based visible light or near-infrared eye tracker, which is the most precise but requires participants to be still while the objects of interest are being presented on a screen.
Moreover, there’s an option that requires no research with new participants to be conducted while still providing valuable insights based on AI technology. Predictive eye tracking uses a data-driven approach to very accurately guess which areas and objects people are most likely to view in a new surrounding.
Eye tracking use cases in shopper research
There is more than one way to gain novel insight into shoppers using eye tracking, and many companies have shared their research on what particular insights one can gain.
One such example is the case of Pringles, where they used eye tracking to analyze how customers react to their new eco-friendly packaging.
This type of research can be especially helpful for companies with legacy packaging that rarely changes, so understanding how shoppers react to this change can be very insightful. Other companies have benefited from eye tracking when piloting a new package or product to understand whether new designs are eye-catching and how consumers see them.
Eye tracking can also be useful to gain insights on what parts of the shelf customers focus on when found in-store in order to better organize certain products on shelves.
An example of such a case study was done by Unilever’s Customer Insight and Innovation Centre. The purpose of the study was to analyze what shoppers see when they engage with Unilever products on shelves. Conclusions drawn from this study helped Unilever discover which features of their products and product placement are important attention hubs and how this attention can be further used to optimize brand awareness.
Some companies opt for doing research with eye tracking in a simulated store environment.
Kellogg is an example of such a company, which partnered with Qualcomm Technologies on a VR project. When combining eye tracking with VR, companies can extend their research to demographical areas where they don’t yet have an option to do in-store research, making it possible to better fit their products to a novel consumer niche.
Moreover, eye tracking can be insightful in competitor analysis. By comparing which part of the product shoppers focus on, how their visual attention spreads, and how this relates to which product they end up purchasing, companies can better understand how to top their competitors.
Shelf placement analysis with Attention Insight
Attention Insight provides predictive eye tracking that can be comparable to real-life eye tracking results. MIT studies have shown that AI eye tracking algorithms from Attention Insight have up to 94% accuracy in predicting how the consumers will engage with visual content.
The way this algorithm works is by predicting the first 3-5 seconds of visual engagement. It has been shown that it can take no more than 2 seconds for consumers to create the first impression of a product, which is why this time window is of interest for most marketers. If it takes seconds for a person to decide which product on a shelf he or she will go for, then it’s only reasonable for companies to make their products stand out positively.
Eye tracking with predictive algorithms can provide this valuable insight without conducting eye tracking research in the real world. All that is needed is an image of a shelf with a product (or products) of interest, which can be uploaded to the system. The algorithm returns a heatmap of areas most likely to be viewed in the first 3-5 seconds.
In the example image below used in the study from Tonkin et al. (2011), the AI eye tracking algorithm predicts within specific areas of interest where the consumers are likely to look at the most, darker red areas being the spots where most visual attention is focused.
Shelf analysis conducted with Attention Insight tool
Judging by analysis results, the area that attracts the most visual attention is the eye-level part of the shelf (17% in total). The bottom two shelves attract some attention as well, while the top shelves are almost completely ignored.
By changing the areas of interest, one can make different predictions and focus on different products and/or parts of the product to better understand how positioning, branding, colorways, and other features may affect consumers’ visual attention.
Conclusion
We have covered several ways in which eye tracking and predictive eye tracking can be used to enhance shopper research and help companies attain novel shopper insights.
However, it’s important to understand the limits of this technology in order to utilize it and properly understand the outcomes of this type of research.
What eye tracking can help you with in terms of understanding shoppers better is to provide precise, detailed information on the visual behavior of shoppers. With this information, it’s possible to understand which features of the targeted products are not receiving enough attention.
Finally, these insights make data-driven decisions possible and rethinking the design of packaging, product placement, advertisement, etc., in a more meaningful way.
FAQ
What is shopper research?
The term “shopper research” refers to a group of methods that helps marketers understand the behavior and attitudes of shoppers. The goal is to provide insight into consumers, which can help optimize products and services to maintain customer satisfaction.
What are shopper insights?
“Shopper insights” is a term often used to refer to shopper research. However, some prefer the term “shopper research” as it is more precise and inclusive. Shopper insights most commonly refer to knowledge about shoppers’ opinions and preferences.
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