Case 4: AI Video Analytics for Fashion Retail Stores

About Customer

The customer is a major fashion retailer operating both exclusive brand outlets and multi-brand partner formats. Their business depends on consistent conversion performance, strong in-store service, and tight loss-prevention controls across varied store footprints.

Leadership needed a unified operating view that could compare performance across formats and guide staffing, layout, and risk interventions in near real time.

Problem

The fashion retailer did not have a unified, real-time view of how stores were performing across EBO and multi-brand formats. Decisions on staffing, service quality, and risk control were largely based on delayed reports and manual observations.

• Customer movement, dwell behavior, and queue pressure were not measured consistently.
• Staff-customer engagement signals were anecdotal rather than operationalized.
• Shrinkage-related behavior was detected late, limiting prevention effectiveness.
• Fragmented reporting made cross-format benchmarking and intervention difficult.

This created a reactive operating model: conversion opportunities were missed during peak windows, and loss-prevention teams acted after incidents instead of at-risk moments. The business needed one analytics layer to standardize decisions, improve service responsiveness, and reduce avoidable losses across all store types.

Solution

Solution Architecture

• Step 1 - Store onboarding: We configured all relevant in-store zones (entry, display, queue, and risk areas) for standardized measurement.
• Step 2 - Behavior analytics: CV models continuously measured footfall, dwell time, queue buildup, and staff-customer engagement events.
• Step 3 - Journey intelligence: Heatmaps and zone patterns highlighted missed conversion opportunities and layout bottlenecks.
• Step 4 - Risk controls: Rule-based detection generated real-time alerts for suspicious movement and shrinkage-linked behavior.
• Step 5 - Unified governance: A central dashboard compared stores and formats for faster, data-driven operational decisions.

Conclusion

The solution gave fashion retail teams a unified control tower for both growth and risk management. Store operations became faster, more consistent, and more measurable across all channels.