agent42labs.com

CV-Powered Insights From In-Store Footage

Elevating in-store experiences with vision-powered retail intelligence

The Challenge

A high-end retail chain wanted to understand in-store customer behavior but had no way to quantify what was happening on the floor. Heatmaps, footfall, engagement—everything was anecdotal. Existing CCTV footage was underutilized.

Our Approach

We built a CV Analytics Layer on top of their existing camera infrastructure:

  • Detected and tracked anonymized customer movement in real time
  • Identified zones with high engagement vs. cold zones
  • Measured dwell time, product pickup rates, and queue lengths
  • Triggered alerts when overcrowding or unattended children were detected

Privacy was maintained through on-device anonymization and no facial recognition.

Stats

Sales up 11% in optimized zones
Checkout wait times down 24%

Enabled weekly A/B layout experiments

The Outcome

With zero new hardware, the client turned passive surveillance into a strategic asset.
Our Expertise

Case Study

  • All Posts
  • AI Agents
  • AI Chat Bot
  • AI Kickstater
  • Computer Vision
  • Data Engineering
  • Gen AI
  • Machine Learning
Manufacturing QA Automation

June 8, 2025/

Home Compute Vision Manufacturing QA Automation Computer Vision for Zero-Defect Assembly Lines Enabling zero-defect manufacturing through edge based visual quality...

Multinational Retail Chain

June 8, 2025/

Home Data Engineering Multinational Retail Chain Modernizing Retail Intelligence with Scalable Data Infrastructure Unifying retail data pipelines to fuel real-time...