Customer Traffic & Behavior Analytics

The Problem

Retailers make layout, staffing, and merchandising decisions based on sales data alone — which only captures what customers bought, not how they moved through the store, where they lingered, or what they considered and passed on. Without behavioral data, optimization is guesswork.

How Computer Vision Solves It

Computer vision counts and tracks customer movements through the store from overhead cameras, generating heatmaps, dwell time analysis, path flows, and zone conversion rates. This data reveals which displays attract attention, which aisles are bypassed, and how traffic patterns change by time of day.

The Challenge with Current Solutions

Tracking individuals across multiple camera views without facial recognition is technically complex. Crowded environments cause tracking loss and merge errors. Privacy regulations require anonymized analytics. Different store formats need different camera configurations.

What vfrog Brings That's Different

vfrog uses anonymous person detection — no facial recognition. Models train on your store's specific layout and camera angles. Edge processing keeps all video data on-premise for privacy compliance. Analytics dashboards integrate with your existing retail intelligence tools.

Key Benefits

• Data-driven store layout optimization
• Staffing aligned to actual customer traffic patterns
• Promotional placement based on dwell time data
• Fully anonymous — no facial recognition required
• On-premise processing for privacy compliance
• Cross-location benchmarking and comparison