The short version
  • Measure task outcomes, not model accuracy in isolation.
  • Test lighting, occlusion, layout, and seasonal variation.
  • Design privacy and human review into the operating model.

01

Common retail vision use cases

Applications include shelf availability, planogram compliance, queue measurement, self-checkout assistance, loss prevention, safety monitoring, and store traffic analysis.

02

Technical evaluation

Test representative cameras, angles, lighting, product density, occlusion, and network conditions. Track precision, recall, latency, alert volume, and failure patterns by store type.

03

Operational and privacy review

Define data retention, access, signage, escalation, and staff responsibilities. Confirm that the system supports the workflow without creating unmanageable review queues.

Common questions

Questions worth asking

What metric matters most for retail computer vision?

There is no single metric. The useful measure is the operational outcome, supported by precision, recall, latency, coverage, and alert workload.