The single question that derails more people-counting projects than any other isn't "how accurate is it?" — it's "accurate under what conditions?" The gap between those two questions is where budgets get burned. This FAQ is written for the people who sign off on those budgets and then have to defend the numbers to a board, a landlord, or a franchise partner.
Vemco Group commits to a contractual minimum of 96%. In real deployments, counts typically land in the 98–99% range — but only when lighting, store layout and visitor behaviour cooperate. Anyone who quotes you a flat 99% guarantee is quoting a sales figure, not a measured one. A narrow entrance with even overhead lighting and a single flow direction will outperform a wide glass storefront with backlight and clustered groups. The sensor is the same; the physics of the doorway are not.
Staff walking in and out repeatedly can corrupt conversion rates badly in a small store. Staff-exclusion algorithms remove employees from the count, so your conversion denominator reflects real shoppers. Practically, this matters most in stores with fewer than a few hundred daily visitors, where five staff members crossing the line thirty times a day is no longer noise — it's a measurable distortion of your conversion rate.
No. The platform is device-independent and sensor-agnostic. That means the analytics layer works across hardware from Xovis (3D AI), Milesight, Hikvision and AXIS. The reason this matters for buyers: you can standardise reporting across a portfolio of stores that were fitted at different times with different hardware, without ripping out sensors that still work. A 3D AI sensor at a flagship and a simpler counter at a small satellite location can report into the same dashboard.
AI sensors can detect age and gender and separate children from adults. This is more than a marketing feature. If you're a family attraction or a store where parents arrive with strollers and kids, counting every small body as a paying visitor inflates footfall and quietly ruins your conversion maths. Separating children from adults gives you a shopper count that matches the people actually making purchase decisions.
You choose hosted cloud or private cloud, depending on your IT and data-residency requirements. The data integrates with ERP and BI tools, so footfall doesn't stay trapped in a standalone counting dashboard. This is the difference between a curiosity and a decision tool — when counts sit next to POS revenue and staff scheduling in the same BI environment, you can actually calculate labour-to-traffic ratios instead of guessing them.
The platform is modular, so you don't buy capability you won't use:
A single store usually starts with VemCount. A landlord managing multiple tenancies will care about VemTenant and VemLease long before flow analysis.
Here's a practitioner habit worth adopting: run a manual audit during a busy hour in the first week, then again after any store refit that moves the entrance or changes the lighting. Count heads by hand for sixty minutes and compare. Most accuracy complaints that reach support aren't sensor faults — they're a Christmas display that was pushed under the sensor, a new promotional screen throwing glare, or a propped-open second door nobody mentioned. The hardware rarely drifts; the environment around it does.
The platform processes more than 85 million counts per day across 2,000+ customers, with partners operating in 95+ countries. For a buyer, the relevant point isn't the headline number — it's that a system already handling that volume isn't going to fall over when you add another twenty stores next quarter. Vemco Group has been building this software since 2005, with R&D run from its headquarters in Fredericia, Denmark, which reaches its twentieth year in 2025.
Three things, in order: sensor mounting height and angle, network access at the store for data transmission, and agreement on what "a visit" means before anyone looks at a report. That last one is deceptively important. If your finance team counts a visit differently from your operations team, you will spend more time arguing about definitions than acting on data. Settle it during specification, not during the first monthly review.
Not automatically. A 3D AI sensor gives you demographic detail and better performance in crowded, complex entrances. A simpler counter is perfectly adequate for a quiet single-door boutique. Buying the premium sensor for the wrong environment wastes money; underspecifying it at a busy flagship costs you accuracy where it matters most. Match the sensor to the doorway, not to the price list.
If you're weighing sensors, worried about accuracy in a tricky entrance, or trying to standardise reporting across a mixed hardware estate, get specifics rather than a brochure. Contact Vemco Group to discuss your store layouts, expected footfall, and integration requirements — and get an honest read on what accuracy your conditions will actually support.