Store Traffic Analytics
Prove the value of every in-store step—and turn movement into revenue.
POS data cannot explain the behavior of shoppers who leave without buying. Vision AI goes beyond headcounts to show which zones keep customers engaged and help drive purchase.
- Entries & exits
- Dwell
- Movement & journeys
- Heatmaps
The purchase-driving patterns a counter total cannot reveal
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
Find retail hotspots and peak trading hours
Analyze traffic by time band and zone to place promotions where shopper demand is highest and optimize staffing.
Journey
Eliminate dead space and optimize the store layout
Use actual customer paths to reduce overlooked areas and design fixture placement that supports conversion.
Operations
Prove the ROI of pop-ups and visual-merchandising refreshes
Use reliable before-and-after data to show the impact of a new store concept or operating approach on dwell and traffic.
Tailored space analysis for your brand goals
Align zones, metrics, and comparison periods with the store decision so traffic data supports action.
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01
Define the business question
Set the retail challenge together, whether that is increasing dwell or measuring performance in a specific pop-up zone.
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02
Optimize the environment
Use existing cameras wherever possible to build an efficient Vision AI environment that respects privacy.
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03
Turn data into insight
Compare store performance and establish a practical baseline for the next operating action.
Proprietary Vision AI turns in-store entry, exit, dwell, and zone activity into insight
Turn every in-store journey—from entry and dwell through movement—into valuable data. P2ACH AI handles the complexity and provides analysis aligned to your brand policy.
An on-site assessment identifies the camera view best suited to the analysis.
Report measurement metrics alongside decision-ready statistical indicators.
Where video export requires masking, it follows a separate review and approval workflow from store analytics.
When data becomes strategy, see it in an intuitive dashboard
Visualize customer journeys with clear metrics, heatmaps, and comparison views.
Hourly and daily traffic, entry, and dwell trends
Customer-path flow diagrams
Store heatmaps and cross-store KPI comparisons
Re-ID for reliable customer-only data
Ask in plain language. Get an immediate answer from your store data.
No team needs to hunt through rows of data. When store metrics are connected to Analytics Measurement, ask P2ACH AI Agent in everyday language and receive evidence-based clues for the next operating decision.
Questions for a connected configuration
Find the stores and time bands with the largest change in entries over the last four weeks.
Which store had the longest customer dwell during weekend peak hours over the past month?
Create a table that compares Zone A entries with the same weekday last week.
The AI operates only in an authorized environment and provides objective, data-based indicators for faster, more confident decisions.
Frequently asked questions
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?
Yes. Training for uniforms and zone-specific filters can distinguish staff from customers in a way that supports more reliable analysis.
Can you track the same person across every camera?
Yes, where camera specifications and the physical environment support matching the same person across views. This is not included in the standard analysis scope.
Start with one store decision
The demo maps the relevant zones, current counters or cameras, analysis views, and comparison plan.
After the demo, we summarize the suitable analysis and next site-review step.