Entrance Counting for Retail
Door Counter
Accurate door counter systems for retail stores. Count every visitor entering and exiting with 98%+ accuracy using AI-powered overhead sensors. Know your true footfall. From £720 per store per year.
Trusted by leading brands
The problem
Why Upgrade Your Door Counter
Traditional infrared door counters miscount groups walking side-by-side, giving you 70-80% accuracy at best. That 20% error makes conversion rates meaningless.
Without an accurate door counter, you cannot identify when your busiest and quietest periods really are. Staffing schedules are based on assumptions, not data.
Simple beam door counters cannot distinguish between people entering and leaving. Without bidirectional counting, you cannot calculate real-time occupancy or dwell time.
Simple setup
How Door Counting Works
Mount Above the Door
Install the Hoxton AI door counter above your entrance in 15 minutes. Compact overhead sensor — no door frame modifications needed.
Count Every Entry & Exit
The door counter uses AI vision to count people entering and exiting separately, with 98%+ accuracy — even groups and children.
Connect Your POS
Link your POS system to pair door counter data with transactions. Calculate store conversion rates automatically.
Optimise Your Store
View real-time door counting dashboards showing peak hours, conversion rates, and traffic trends by day and week.
Door Counter Specifications
98%+
Door counting accuracy
15 min
Installation time
Bi-directional
Entry & exit counting
Real-time
Live dashboard data
Everything You Need in One Package
Compact overhead S1 sensor mounts above any door in 15 minutes. Bidirectional counting with 98%+ accuracy.
Entry counts, exit counts, peak hours, and conversion rates — all updated in real time and accessible from any device.
Out-of-the-box integration with Shopify, Square, and enterprise POS. Plus a full API for custom workflows.
Why 98%+ accuracy
Counting based on journey prediction, not simple line crossings
Most people counters fire a +1 the instant something crosses a beam or line. That's fast — but it's also why they overcount. Hoxton works differently: it uses an overhead view to recognise a complete in-view journey and only counts when the journey matches a real entry or exit.
Traditional counters
A single trigger = a count, every time the line is crossed.
- ●Security guard pacing near the doorway? Counted repeatedly.
- ●Customer steps in, hesitates, turns back out? Often counted twice.
- ●Staff working near the entrance? Every pass inflates the number.
Result: counts drift upward anytime there's “doorway noise”.
Hoxton AI directional event counting
A count is only created when the system confirms a genuine entry/exit event.
- ●Understands a person's in-view journey from arrival to departure.
- ●Someone loops, pauses, or changes their mind? No false extra counts.
- ●A count only registers when they arrive on one side and leave on the other — a real entry or exit.
Result: accurate footfall that matches what actually happened, not how many times a line was crossed.
How directional event and journey prediction works
Detect
Person enters the field of view
A person is detected as they arrive in the overhead zone.
Interpret
Movement is understood in context
The system evaluates whether the movement indicates entering, exiting, or lingering/turning back (including loops and hesitation).
Confirm
Count only when the journey is complete
A count is recorded only when the person leaves the zone in the opposite direction — confirming a true entry/exit event, once.
Trusted by Leading Retailers
“Switching from infrared to Hoxton's AI door counter was a revelation. Our conversion rate calculations finally reflect reality — the data is accurate enough to act on.”
Lisa Angel
Jewellery and gifting retailer
“The bidirectional counting means we know exactly how many people are in the store at any time. It transformed our staffing decisions.”
Ribble Cycles
Multi-location cycling retailer
Door Counter FAQ
See It in Action
Book a demo and we'll show you real dashboards from spaces like yours.