Support FAQ for Tenant Revenue Analytics

Most support tickets about tenant revenue analytics do not come from people who misunderstand the dashboards. They come from finance teams who spot a €4,000 gap between a tenant's declared turnover and what the footfall-to-conversion model predicted, and want to know which number to trust. That single scenario drives more questions than any onboarding session, so this FAQ starts there and works outward.

What does tenant revenue analytics actually measure?

It ties visitor counts to reported or point-of-sale revenue per tenant, then benchmarks each unit against its peers in the same centre. With VemTenant connected to VemCount, the system pulls footfall automatically and pairs it with declared turnover, so a landlord can see spend-per-visitor, conversion, and revenue density per square metre without asking tenants for spreadsheets every month. Vemco has run this kind of setup across 95+ countries since 2005, so the FAQ below reflects patterns that repeat regardless of region.

Why doesn't the counted footfall match my tenant's sales figures?

This is the number one question, and the answer is usually not a counting fault. A mismatch normally comes from one of three sources:

• Reporting lag — tenant turnover is submitted weekly or monthly while footfall is live, so short windows look wrong until both align.
• Staff and delivery traffic counted as visitors when entrances aren't zoned correctly.
• Under-declared turnover — which is exactly what the analytics is designed to surface.

On counting itself, the contractual minimum is 96% accuracy, and in practice it reaches 98–99% when lighting, store layout, and visitor behaviour allow. If a wide entrance has direct sunlight hitting the sensor at 5pm, expect the lower end of that range until the mounting is adjusted.

How is a suspiciously high spend-per-visitor flagged?

The system compares each tenant against category benchmarks. A jewellery unit will always show high spend-per-visitor and that's expected; a fast-fashion store showing the same pattern is not. When a tenant's declared revenue divided by counted visitors sits far outside its category band for several periods, it gets flagged for review. This is not an accusation — it's a prompt to check whether an entrance is miscounting or a POS feed dropped for part of the month.

Do tenants have to share their POS data?

Not always. Many centres run entirely on declared turnover figures that tenants already submit for turnover-rent calculations. The analytics adds independent footfall as a cross-check. Where tenants do connect POS or provide finer sales data, the benchmarking gets sharper — but the core value works with the data landlords already collect under existing lease terms. That distinction matters during procurement, because it removes the "we can't get tenants to integrate anything" objection before it starts.

How does this connect to leasing decisions?

VemLease extends the revenue analytics into leasing, so the same footfall and turnover data feeds renewal negotiations and space allocation. Instead of arguing rent per square metre in the abstract, a leasing manager can point to actual revenue density and conversion for that unit and its neighbours. A tenant paying below-market rent but generating strong spend-per-visitor becomes a retention priority; a high-rent unit under-performing its category signals a re-mix conversation.

We replaced an old system — will migration break our history?

This is a fair worry. Magasin faced exactly this when it moved off an outdated system to a hosted Vemco solution and cut operational costs in the process. Historical footfall can typically be imported so trend lines don't reset to zero on day one. The practitioner detail worth knowing: turnover history is easier to migrate than footfall history, because old counters often stored aggregated daily totals rather than hourly data. If you want hour-of-day benchmarking to work from the start, ask whether your legacy granularity survives the import — this saves an awkward three-month gap in reporting.

How long before the numbers are trustworthy?

Live footfall is reliable within days of correct installation. Benchmarking needs longer — usually a full seasonal cycle — because a February comparison tells you little about December performance. Outlet Village Sofia became Bulgaria's first fully data-driven outlet village on Vemco precisely because it treated the first months as a calibration period rather than expecting perfect verdicts immediately. Give the data a quarter before making rent or re-mix decisions on it.

Who in our team owns this day to day?

Most successful rollouts split ownership:

• Centre management watches footfall and flags sensor faults early.
• Finance reconciles declared turnover against the model.
• Leasing uses the benchmarks in negotiations.

When one person tries to own all three, questions pile up and the tool gets blamed for slow answers that are really an ownership gap.

What triggers a support ticket versus a training question?

A sensor showing zero counts for a whole day is a support ticket. A manager unsure why spend-per-visitor dipped is a training question — the data is right, the interpretation needs context. Separating these two speeds up resolution, because hardware issues and analytics coaching go to different people. Sending an interpretation question to hardware support is the most common reason tickets sit unresolved.

If you're evaluating tenant revenue analytics, or your current setup is generating more questions than answers, talk to the team who has done this across 95+ countries. Contact Vemco to walk through your centre's data sources, migration risks, and how VemTenant and VemLease fit your existing lease terms.