Case Study: Implemented In-Store Smart Device Platform and Analytics Engine for Two Major Retailers

Divertica implemented in-store smart easels and mirror for two major retailers.

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We were engaged in deploying Digital Easels and Smart Mirrors in multiple stores and then measuring the impact to customer in-store behavior.  Because the devices were for direct end customer in-store interaction, there was a high degree of focus on creating a elegant design.

The smart devices were used to enhance the in-store experience,  provide product information to customers, and to be able to display marketing and promotional messaging.  For this project, we had to gather people analytics, facial analytics, and device analytics as well as measuring the impact of the devices.

This was a platform development project that required a broad range of technologies and hardware customization.  The following were the technologies used:

Running on Smart Devices:

  • Customized Version of Android – we created a custom version of Android to fit a Smart Mirror application. This required deep knowledge of the Android OS along with a close working relationship with Google.
  • Firebase and Heroku – these were used to develop the app running on the Smart Mirror

Management and Analytics Platform for Smart Devices:

  • js and REACT – this was used for the UI layer on the Smart Mirrors and Digital Easels
  • js – this was used for the logic layer managing the Smart Mirrors and Digital Easels
  • Ruby – this was used for DevOps scripting

Content Management Platform – we had to build a new content management platform that fit the unique use case of a Smart Mirror and Digital Easel In-Store platform.  This required the ability to make real time adjustments at the individual store level.

  • Google Data Studio – we used Google Data Studio for data visualization and allow users to easily generate their own queries and reports.
  • Google AutoML – we used machine learning algorithms to understand personas and environment driving particular customer reactions/facial expressions
  • Facial Expression – we used a facial expression library to categorize customer expressions


  • RFiD – integrated to automatically pull up product information
  • Barcode – integrated to automatically pull up product information

External Integrations

We integrated with an external companies as part of the overall design.  This included:

  • Legacy Systems
  • Strava – Influencer events
  • Salesforce
  • Magento
  • Shopify

In-Store Experience

The goal was to have a rich user experience that include:

  • Dynamic searching of the product catalog

  • Easy digital checkout

  • Ability to try on products virtually

  • Analytics and Content Management

  • In-Store Live Customer Data

The focus on the hardware was creating a design that was visually appealing for end customers and offered a number of different options.

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