Store Traffic Analytics

Compare store traffic before and after a change.

Compare visits, dwell, zone movement, and journeys before and after a layout or operating change. First, we check the zones, camera coverage, and metrics that matter to the decision.

Request a store analytics demo

Start with one store decision to see the relevant zones, analysis views, and camera coverage.

Concept illustration of zones in a multi-level retail store — Concept illustration. We configure traffic, zones, and journeys around the decisions each store team needs to make.

Visits & entries
Dwell
Movement & journeys
Heatmaps

Compare what changed—not only how many entered

Compare time periods, zones, or stores against one baseline. P2ACH AI shows observed patterns, so your team can choose and test the next change.

Traffic

Understand when and where visits change

Compare entrances, pass-by traffic, dwell, and zone patterns by time and location.

Journey

See movement beyond a single counter

Use zone transitions, journey views, and heatmaps to inspect how customers move through the measured space.

Operations

Create a baseline for layout and operating tests

Define a before-and-after comparison for space, media, or operating changes instead of assuming impact.

Design the analysis around a real store decision

Align zones, metrics, and comparison periods with the store decision so traffic data supports action.

01
Define zones and the operating question
Map entrances, key areas, traffic patterns, and the layout or operating change the team wants to evaluate.
02
Assess coverage and metric feasibility
Review camera views, occlusion, staff traffic, cross-camera requirements, edge capacity, and privacy controls.
03
Establish a baseline and compare
Use traffic and journey outputs to build a before-and-after or store-to-store comparison plan.

On-device Vision AI for store traffic

Task-specific Vision AI can infer visits, entries, dwell, and zone movement on a device in the store, then turn those signals into time, zone, and location comparisons. Cross-camera journeys, de-identification, transmission, retention, and access are defined for the selected analytics design.

Detection and tracking are validated against field of view, occlusion, staff traffic, and zone definitions.
Analytics metrics are separated from any images or events retained under the agreed design.
Where video export requires masking, it follows a separate review and approval workflow from store analytics.

See the views behind each store decision

The demo connects traffic, journey, and heatmap views to the zones and comparison periods they represent.

Hourly and daily traffic, entry, and dwell trends
Zone transitions, Sankey flow diagrams, and zone IN/OUT (entries/exits) views where configured
Heatmap and multi-location comparison views
Coverage, occlusion, and staff-exclusion considerations

AI AGENT Connection review

Continue store analysis with AI Agent questions

When visit metrics are connected to Analytics Measurement, a supported AI Agent environment approved by your organization can compare entry, exit, traffic, and dwell data by store and period. Availability is confirmed during the demo.

Questions for a connected configuration

Find the stores and time bands with the largest change in entries over the last four weeks.
Compare traffic and dwell before and after the selected operating period.
Prepare a table using the same store, period, filters, and metrics.

Availability depends on whether the selected store metrics are connected to Analytics Measurement and on workspace permissions. Answers retain the comparison conditions; layout or staffing decisions remain with the operating team.

Concept illustration showing authorized data flowing through an access boundary to an AI reasoning layer and evidence-backed answers — Concept illustration of permission-scoped data and evidence-backed answers

Questions store teams should ask

How is this different from a door counter?

A door counter focuses on entries. A configured store analytics installation can add zone dwell, movement, heatmaps, and journey comparisons when the environment and camera coverage support them.

Can employees be excluded?

Staff exclusion can be included where needed. We test uniforms, zones, camera views, and operating conditions before using it in reporting.

Can you track the same person across every camera?

Cross-camera journeys can be included where overlap, image quality, timing, and privacy requirements support them. They are not part of the default analysis scope.

Start with one store decision

The demo maps the relevant zones, current counters or cameras, analysis views, and comparison plan.