Display and Experience Measurement

MEASURE OPPORTUNITY, ENGAGEMENT AND INTERACTIONS DOWN TO THE PRODUCT LEVEL

Case Study

BACKGROUND
A multibillion dollar footwear retailer wanted to improve performance of entryway display tables by testing placement.

EXECUTION
With video and advanced ML, DisplayBrick tracked how shoppers navigated the feature area and what they interacted with.

LEARNING
Customers flowed around the exterior display tables, rarely interacting with featured products.

IMPACT
Shifting a key display forward towards customer flow resulted in a near 400% increase in product interactions.

What it Does

Digital Mortar’s Display 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. DM Display breaks down performance and drives real optimization.

DM Display Measures:

  • Opportunity. Pass-by traffic (in detail – by edge and exact location to optimize product placement)
  • Attention. Detailed measurement of stops and dwell times down to specific product frontages
  • Interaction. Product touches, pick-ups and interactions measured in detail by area and product type

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.

Take Real-time video and analyze shopper tracking with dedicated or existing LP cameras
Extract, Trasnform and Load into DM1 to deliver advanced people tracking
Tune for Display and Product Interactions with customized reporting

The New State of the Art in
Experience Measurement

A year or two ago, the DM Display 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.

  • Edge-Based ML Means It works.

    Powerful video processing that can be quickly customized to your lighting and interaction needs

  • It’s practical.

    No video to the cloud. No requirement for massive bandwidth. Easy single camera installation. Little or no impact on store infrastructure.

  • It’s privacy sensitive.

    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.

  • It’s inexpensive.

    Modern edge-based ML is remarkably inexpensive for the power it brings. Meaning measurement IS affordable.

 

Existing Infrastructure Can Sometimes Do the Job

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.

Request a Demo

The best way to evaluate ANY enterprise software? See it in action.
Drop us a line and we’ll set up a time to walk you through DM1 and answer any questions you have.

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