The most expensive shelf in your store is often the one nobody walks past. Merchandising teams spend weeks negotiating supplier placement fees and building planograms, then position those products in aisles that receive a fraction of the foot traffic they assume. Movement data exposes this gap immediately, and the numbers are usually uncomfortable. A high-margin category parked in a low-circulation corner can underperform an identical assortment placed on a primary path by a wide margin — not because of the product, but because of the floor tile it sits on.
Entrance counting has been standard practice for years, and it answers one question: how many people came in. That is necessary but shallow. The gap between a visitor entering and a visitor reaching your featured end-cap is where merchandising decisions actually live. Vemco has been counting shoppers since 2005 and now processes more than 85 million counts a day across 2,000-plus customers, but the shift that matters for placement is from counting people to tracing routes. VemTrack adds customer-journey and movement analytics on top of the count, including AI Re-Identification that follows an anonymous shopper's path through the space without tying it to an individual.
Once you can see paths, three patterns emerge in almost every store:
The instinct is to fix cold zones by adding signage or lighting. Sometimes that helps. More often the smarter move is to stop fighting the natural flow and reassign the space. If a zone consistently gets traffic but no dwell, it is a poor home for considered purchases that need browsing time — but an excellent home for grab-and-go items, seasonal impulse buys, or a rotating clearance table that benefits from volume passing rather than lingering.
Pair that with dwell time and you can separate two things that look identical in a sales report. A category with high traffic and low conversion has a placement or presentation problem. A category with low traffic and high conversion — meaning the few people who find it buy it — is a candidate for relocation to a busier path, where the same conversion rate applied to more visitors produces real revenue. Luksusbaby used VemCount to watch hit and conversion rates in real time alongside visitor demographics, which is exactly the combination that lets you act on this distinction within a trading week rather than after a quarterly review.
Movement data becomes sharper when you know who is moving. Demographic targeting matches assortment and adjacency to the actual age and gender profile of visitors, not the profile in the brand deck. If your morning traffic skews differently from your weekend crowd, a fixed planogram is serving one of them badly. Store directors who track this find that the "best" placement is often time-dependent — a display that earns its keep on Saturday afternoon is idle on Tuesday morning, and a movable fixture solves what a fixed one cannot.
Placement decisions rarely fail because of one store. They fail because a change works in one location and gets rolled out blindly to twenty others with different footprints and traffic patterns. Daells Bolighus, during a turnaround, integrated in-store and online sales and visitor data across locations rather than treating each shop as an island. That comparison view is what stops a good local decision from becoming a bad chain-wide one. When you can see that a repositioning lifted a category in the flagship but flatlined in the smaller-format stores, you keep the win and skip the mistake.
If you are going to reallocate square metres and supplier fees based on movement data, the counting underneath it has to hold up. Vemco's contractual minimum is 96% accuracy, and under good conditions — decent lighting, a layout that doesn't force sensors into blind angles, normal visitor behaviour — it typically runs 98–99%. The practitioner detail that gets missed: reflective flooring and glass near the entrance will quietly degrade accuracy in exactly the high-traffic zone you care about most. Fix the mounting and sightlines during installation, not after three months of questionable data. It is far cheaper to get the sensor position right on day one than to explain a merchandising decision built on numbers you later distrust.
You don't need a chain-wide rollout to test the idea. Pick one store, map the paths and dwell for two weeks, then move a single underperforming high-margin category from a cold zone to a mapped hot path. Hold everything else — price, staffing, promotion — constant. Measure conversion and sales for that category against the prior period. If the lift is real, you have a repeatable playbook and internal proof that beats any vendor slide. If it isn't, you learned something about your store that a sales report would never have shown you, and you spent almost nothing to learn it.
If you want to see how shopper movement data maps to your own floor plans and turn it into placement decisions your finance team will accept, talk to the Vemco team about a movement-analytics setup for your store or chain.