RETAIL FOOTFALL ANALYTICS: 3 TIPS TO CONTROL SALES
Turn visitor counts into reliable action. Pair people counting sensor technology with POS data. Plan staffing, protect margins, and lift conversion without guesswork.
1) KNOW YOUR SALES SHARE
Not every visitor will buy. Performance varies by day, hour, and mission. Measure daily visitors, transactions, and conversion as your baseline.
Footfall alone shows how many. POS shows what sold. Together, they reveal productivity.
Whatever your current conversion, treat it as a relationship to improve daily.
Conversion rate: transactions ÷ visitors.
Sales per visitor: revenue ÷ visitors.
Average transaction value: revenue ÷ transactions.
Use privacy-safe sensors, not surveillance. Solutions like Xovis process anonymized depth points. No faces, no PII.
2) FIND WHEN YOU HAVE VISITORS
Traffic and intent follow rhythms. Some hours are busy with low intent. Others are moderate with high purchase intent.
Chart hourly traffic share and hourly conversion. The shapes repeat weekly. Staff to the shape, not the clock.
Schedule queue relief for the top 90-minute demand window.
Place your strongest sellers on peak conversion hours.
Align replenishment to low-intent windows, not peaks.
3) USE THE NUMBERS TO CHANGE OUTCOMES
Data should trigger action, not just reports. Tie analytics to simple workflows.
Entrance: test layout, count entering visitors, compare uplift.
Service: alert if occupancy crosses a queue threshold.
Fitting rooms: correlate usage with conversion and staff accordingly.
Campaigns: compare traffic, conversion, and sales per visitor to control days.
FOUR-WEEK PLAYBOOK
Instrument: calibrate sensors at entrances and key zones. Verify store hours.
Baseline: capture four weeks of footfall, conversion, and sales per visitor.
Pilot: add one associate during peak conversion hours. Monitor queue time.
Review: measure uplift; scale to similar stores; keep A/B discipline.
GDPR AND PRIVACY BY DESIGN
CountMatters uses sensor data designed for occupancy and counting. We store aggregated metrics only. No images, no identities—actionable insight without exposure.
IMPLEMENTATION: SENSORS, DASHBOARDS, WORKFLOWS
We connect sensors and POS, then surface KPIs in role-based dashboards. Triggers make insight operational: “if queue time > target, notify floor lead.”
ROI YOU CAN PROVE
Because hourly patterns repeat, small staffing shifts compound. You can track where conversion improved and which interventions deserve rollout.
ROI
A small uptick in conversion can have outsized impact. See how visitor data changes the math.
Your scenario
Your baseline. Typical retail: 8–12%.
Lift is measured in absolute percentage points (e.g., +2 pp from 10% → 12%).
Currency is auto-detected for display.
+0% % relative lift
What it means:
What it means
Projected revenue uplift (per month)
Additional orders (per month)
Validated in production; typical accuracy 94–98% with on-device anonymization.
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