Most stores fly blind between the front door and the till. HyperDecode reads your existing CCTV to show real footfall, conversion, queue length and shrink patterns as they happen — so store teams act on the day, not on last month’s report.
Traffic and conversion are guessed from POS alone — you can’t see how many people entered, browsed, or left without buying.
Checkout queues trigger silent walkouts at exactly the busiest, highest-revenue moments.
Shrink is reviewed after the fact by scrubbing hours of footage, so organised theft and till fraud are caught late or never.
Labour is scheduled on rough templates instead of the real footfall curve of each individual store.
Merchandising and display decisions are made with no data on where shoppers actually look, stop, or ignore.
Each capability targets a specific problem, on the cameras you already run.
You know how much you sold, not how many chances to sell you had.
Line-crossing counts at every entrance are matched to POS transactions to give a true visit-to-purchase conversion rate — deduplicated and with staff excluded — by hour, day, zone and store.
Benchmark stores fairly, spot underperforming locations, and prove the impact of promotions and layout changes.
Long lines at peak send ready-to-buy customers back out the door.
Real-time queue-length and wait-time detection at every till triggers an alert to open another register before customers abandon their baskets.
Recover abandoned sales at peak and hold wait times to a defined service standard.
You don’t know which displays pull shoppers in and which are dead space.
Anonymous movement heatmaps and dwell-time analysis reveal hot zones, cold zones, and how long shoppers engage with each display or category.
Optimise planograms, promo placement and store layout with evidence instead of intuition.
Manual CCTV review only catches theft after the stock and margin are gone.
Detects scan-avoidance and sweethearting at the till, loitering in high-theft zones, and repeat-offender / organised-retail-crime patterns — with clips pushed to LP in real time and linked to EAS events.
Shift loss prevention from reactive footage-scrubbing to proactive, prioritised alerts.
Staffing templates don’t match how each store actually fills and empties.
Footfall curves per store and daypart feed scheduling so cover lands where and when customers are, not on a generic rota.
Cut over-staffing in quiet hours and under-service in peaks — protecting both cost and conversion.
Catch queue build-up and walkouts the moment they start, not in next week’s numbers.
Prioritised, evidence-backed alerts help LP teams focus on the incidents that actually matter.
Align labour to genuine footfall so cost and service improve together.
HyperDecode is software that runs on your existing CCTV — no rip-and-replace, no new hardware to buy or install. Point it at the feeds you already record and start turning them into intelligence.
No. HyperDecode runs on the IP and analog CCTV you already have. If a camera can see the entrance, aisle or till, it can be turned into an analytics sensor — no hardware refresh required.
People are counted on entrance line-crossings with de-duplication and staff exclusion, so a shopper who enters, leaves and re-enters isn’t double-counted. Counts are reconciled against POS to produce a defensible conversion rate.
No. Footfall, dwell and queue analytics are anonymous — they measure movement and counts, not identities. No facial recognition or personal data is required to deliver the core retail use cases.
Yes. Conversion analytics reconcile against POS data, and loss-prevention alerts can be correlated with EAS and till events so the right context reaches your LP team.
Book a demo and we’ll show HyperDecode running footfall, queue and shrink analytics on a retail floor.