Two stores can post identical footfall numbers and be running two completely different businesses. One pulls a steady stream of 25–34-year-old women on weekday lunch breaks; the other lives on weekend family traffic skewing male and over 45. Same count, same trend line on the dashboard — and if you plan assortment, staffing, or campaigns off that count alone, you are guessing at the half of the picture that actually drives conversion. That gap between how many and who is exactly what the Quividi Vemco integration closes.
Quividi is an audience measurement platform: its sensors estimate age and gender composition of the people passing through a measured zone. Vemco Group, founded in 2005 in Denmark, runs a sensor-agnostic open data analytics platform that already processes more than 85 million counts per day for over 2,000 customers across 95+ countries. The integration imports Quividi's demographic data — age and gender — directly into the Vemco platform, where it sits alongside footfall, POS sales, and any other data source you have connected.
The operative word is alongside. If you already run Quividi, you have demographic data. If you already run footfall counting, you have volume data. What most organisations do not have is those two datasets in the same dashboard, on the same time axis, joined to sales — without an analyst exporting CSVs every Monday and stitching them together in a spreadsheet. That manual merge is where demographic programmes usually die. Someone goes on holiday, the export breaks, and three months later the data exists but nobody looks at it. The integration removes that failure point entirely: no manual data merging, one dashboard, one time axis.
If you have read the generic articles, you know the pitch: "understand your audience." Here is what that means when someone actually owns a budget.
For malls, demographic data joined to footfall has a commercial edge that single-brand retailers do not have: leasing. A prospective tenant asking "who walks past this unit?" usually gets an answer built from catchment studies and intuition. A leasing team that can show measured age and gender composition for a specific corridor, by daypart, across a full season, is negotiating from a different position. The same data feeds event programming — if your Saturday audience is measurably older than your Thursday-evening audience, your entertainment calendar should reflect that, and now you can prove whether it worked afterwards rather than debating it in a post-mortem.
A practitioner observation from real deployments: demographic sensors and footfall counters rarely cover identical zones. A Quividi sensor typically measures a specific field of view — an entrance approach, a screen zone, a corridor — while footfall counters measure entry lines. If you treat the demographic sample as a literal census of every counted visitor, you will over-interpret. The right mental model is demographic composition applied to counted volume: footfall gives you the reliable denominator, Quividi gives you the audience mix, and the Vemco platform keeps both honest by showing them side by side. Teams that understand this from day one place sensors deliberately and write their reporting definitions accordingly. Teams that don't spend their first quarterly review arguing about why the numbers "don't match" — when they were never measuring the same thing.
On accuracy: Vemco contracts on a minimum of 96% counting accuracy, and in practice accuracy typically reaches 98–99% when conditions — lighting, store layout, visitor behaviour — allow. That distinction matters more with demographics in the mix, because segment-level analysis amplifies noise. A stable, honestly-specified counting baseline is what makes the demographic overlay trustworthy enough to base budget decisions on.
Vemco's platform is sensor-agnostic by design, which is not a footnote — it is the reason this integration is practical for existing Quividi users. You do not replace your Quividi estate, and you do not lock your footfall counting to a single hardware vendor to get the combined view. The platform's job is to take counts, demographics, sales, and whatever else you feed it, and put them on one analytical surface. For teams that have been burned by closed ecosystems where every new data source means a new contract negotiation, that architecture is the difference between a six-week integration and a two-year procurement saga.
If you are already running both Quividi and Vemco, or considering the combination, the fastest route to value is narrow: pick one hypothesis your organisation actually argues about. "Our flagship attracts a younger audience than our high-street format." "The spring campaign brought in the segment we paid for." Connect the data, test that single claim over one full trading cycle, and put the answer in front of the people who made the assumption. One settled argument does more for adoption than any capability overview — and it builds the internal credibility to expand from there into staffing, assortment, and leasing use cases.
Footfall tells you how many. Demographics tell you who. Together, they turn visitor data into audience understanding — in the same dashboards you already use, with no spreadsheet stitching in between.
Want to know who your visitors are, not just how many? Connect Quividi with Vemco and add age and gender insight to your footfall analytics. Talk to our team at vemcogroup.com/contact-us and we'll walk you through the integration against your current sensor setup.