A multibillion dollar footwear retailer wanted to improve performance of entryway display tables by testing placement.
With video and advanced ML, DisplayBrick tracked how shoppers navigated the feature area and what they interacted with.
Customers flowed around the exterior display tables, rarely interacting with featured products.
Shifting a key display forward towards customer flow resulted in a near 400% increase in product interactions.
Digital Mortar’s DisplayBrick puts advanced Machine Learning (ML) on the edge to create highly customized solutions for tracking your key merchandising, display and experience elements. Endcap, table, wall, kiosk or complex experience. The DisplayBrick breaks down performance and drives real optimization.
The DisplayBrick Measures:
It’s the data you need to figure what’s working, what isn’t and what could be better. From product placement to full display testing to experience optimization. Because you can’t improve what you can’t measure.
A year or two ago, the DisplayBrick couldn’t have existed. Because the underlying technologies didn’t exist. But thanks to an explosion in edge-based, purpose-built ML compute engines, it’s now possible to do advanced machine learning on the edge. These tiny IoT compute engines are inexpensive, super-powerful and highly tuned for advanced processing.
We use compute engines from legendary GPU maker Nvidia to deliver analytics that no one, quite literally, has seen before.
Powerful video processing that can be quickly customized to your lighting and interaction needs
No video to the cloud. No requirement for massive bandwidth. Easy single camera installation. Little or no impact on store infrastructure.
No face recognition. No PII captured or sent. No video capture off device at all. GDPR compliant with NO personal data added to your privacy burden.
Modern edge-based ML is remarkably inexpensive for the power it brings. Meaning measurement IS affordable.
The hardest part of most store measurement? Getting equipment in the store. But if you have relatively modern LP cameras reasonably positioned on the merchandising you care about, chances are we can use them for advanced display analytics.
For ongoing projects, you’re better off putting ML at the edge. But if you want to test display analytics or conduct a one-off project, using existing LP cameras can often be the right solution. You get the same advanced capabilities of the edge-based Display Brick. Measure pass-by traffic to understand opportunity. Count real eyeballs and exact foot-traffic patterns. Determine capture rates. And measure detailed interaction rates and types.