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Case Study: Using Mobile Eyetracked VR for Retail Merchandising
Cognitive3D worked alongside Accenture, Qualcomm, Kelloggs, & InContext Solutions, to create a virtual reality experience based on the existing real-world business needs of Kellogg's. The experience set out to test planogram configuration, product placement, & pricing strategy for the launch of Kellogg's new product: Pop Tarts Bites.
The retail experience utilized the new Qualcomm 845 chip to enable eye tracking on mobile VR, meaning we could enable user eye tracking support within the Cognitive3D analytics package. The addition of precise eye tracking to the immersive VR experience enabled a new layer of insights not possible with any other method of research.
In an initial feasibility test, Accenture and Qualcomm ran two focus groups through the immersive VR testing process for merchandising the Kellogg’s Pop Tarts Bites, placing the new product and promotional signage on two different shelves — one higher and one lower. Kellogg’s had already run traditional in-home user tests and online attitudinal studies. The VR results showed a high degree of correlation with real-life results from Kellogg’s more traditional testing scenarios. Both showed that consumers expected to find new products higher up on a shelf.
What truly set the VR results apart were the additional insights available from the eye tracking analytics. These insights are not possible through traditional physical, in-home, online or survey merchandising methods. With the immersive VR Merchandising experience, Accenture, Qualcomm and Kellogg’s were able to see what consumers were looking at, when they were looking at them, and in relation to which action.
What truly set the VR results apart were the additional insights available from the eye-tracking analytics.
Eye-tracking stats available in the immersive experience included:
- Total gaze time for each scene, element, and product
- Sequence of products & elements by gaze time
- Product interaction relative to gaze
- Specific sequenced user gaze data
This level of behavioral data is unavailable when using traditional merchandising research.
When looking at the signage and the Kellogg’s Pop Tarts Bites, consumers’ eyes were also drawn to products that were physically nearby. On the higher up shelves – where consumers normally expect to find new products – the close proximity of non-Kellogg's products meant that these products were also gazed at more frequently.
When looking at the signage and Kellogg’s Pop Tarts Bites placed on the lower shelves, consumers also paid more attention to the other surrounding Pop Tarts products, stimulating additional sales of traditional Pop Tarts items with an overall 18 percent increase in purchase frequency. Our conclusion is that the VR headsets equipped with eye-tracking analytics delivered a different, more informed merchandising conclusion.
Applying VR Merchandising consumer testing at scale with an eye tracking enabled mobile VR headset is essential for retailers going forward. The benefits of deeper data and more informed conclusions lead to more optimal product placement, assortment, and pricing results. This also allows brands and retailers to test a larger, dispersed group of people while reducing time and cost when performing research at scale.
Based on these outcomes, we recommend that brands, retails, and consumer packaged goods companies alike should create and maintain virtual store experiences and use the rapid turnaround of virtual product sets to perform faster and more efficient consumer testing scenarios across more multiple geographies, ultimately contributing to higher revenue generation potential.
- User research in virtual reality mimics real life results
- Research using virtual reality has a much faster turn around time than traditional methods
- Eye tracking analytics is essential for retails performing user research in virtual reality.
What can we measure?
Track gaze on products, shelves, retail activations and signage with eye tracking enabled devices.
How did the user move through the retail experience, and was the customer drawn to the appropriate planograms?
Did users interact with relevant products? Did the customer react to product positioning or packaging? Did this lead to a purchase?
Measure and compare how physical and emotional state may have influenced a buyers behavior in SceneExplorer.