What a footfall benchmark is actually worth
A footfall benchmark is worth something only when the numbers being compared were counted the same way, with the same method, definitions and calibration; otherwise the comparison misleads. When sites differ a lot in size, indexing each one against its own baseline keeps the comparison fair.
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Suppose, to take a made-up case, that a flagship’s footfall is up twelve per cent year-on-year while the nearest competitor’s location is down eight per cent over the same period, and both figures end up on one slide for the board. Before that slide goes in, check whether the two numbers measure the same thing, because often they do not.
The short version
- Two footfall numbers can be compared only when they share the counting method, the definitions and the calibration.
- An index sets each site to a baseline of 100, which takes the difference in size out of the comparison but still needs consistent counts underneath.
- A benchmark needs the counting technology, calibration history, definitions and error range written down, along with any change over the period.
- A published index shows which way the market is moving. It cannot reliably show that your site beats a particular competitor.
- Consistent, documented footfall data gives a tenant or a landlord a concrete basis in lease negotiations.
When is my own footfall data enough, and when do I need a benchmark?
Your own data is enough for operational questions. You need to know how many people come through on a Tuesday morning because you are staffing for it, and the hourly pattern shows when the queue at the fitting rooms becomes a problem. Set against the till, the same count gives the conversion rate behind footfall and sales telling different stories. None of this needs more than your own data, as long as it is collected consistently.
A benchmark comes in when you compare your number with something external: a competitor, an industry index or your own portfolio across different counting systems. From then on the comparison has value only if both sides were measured the same way, under the same rules and definitions. In practice, retail footfall data rarely meets that standard, and the gaps are not trivial.
Why can’t I compare footfall counts from different counting systems?
Because the systems count slightly different things. Take two sites that both use electronic visitor counting and both report daily totals. The first uses a camera-based system calibrated against manual control counts twice a year; it counts inbound visitors only, and staff are excluded because they use a separate entrance. The second uses a bi-directional door sensor; staff use the same entrance as customers, and the counter has not been recalibrated since installation. (A Wi-Fi system counts devices and relies on exactly that calibration step to turn the device count into a count of people.)
Those two numbers cannot be compared, even if they sit in the same spreadsheet or are averaged together in a chain-wide report. They have different error rates and definitional assumptions, and any benchmark built from them carries those errors into every decision it informs.
A 2021 study of footfall sensors across Great Britain (Philp et al., Applied Spatial Analysis and Policy) found distinct daily and weekly footfall patterns across types of retail location, and checked its sensor counts against manual counts before any analysis. A 2025 review by the West Midlands Combined Authority put the cross-site problem bluntly: incompatible counting methods produce incomparable results.
Does an index make a big site and a small one comparable?
As far as size goes, it does. An index sets each site (or each period, or each location type) to a baseline of 100 and expresses later performance relative to that point. A large regional shopping centre and a small high-street unit can each be measured against their own baseline, so the comparison is not distorted by one receiving ten times the visitors of the other.
Published national footfall indices work on this principle: they follow relative movement across location types without claiming a single absolute count for “retail”. Their value comes from normalising the data before anything is compared.
The limit is that an index still needs consistent underlying counts. If a site’s data shifts from year to year because a sensor was replaced, a counting rule changed or a new staff entrance opened, the index will record a movement that did not really happen.
What must be documented before a benchmark can be trusted?
A benchmark can be trusted only when the data behind it is documented as thoroughly as the count itself, which means knowing the counting technology and its calibration history, the definitional rules (inbound only or net, staff excluded or not, children counted or not), the known error range and any change to these over the period being compared.
Without that documentation, two numbers can look alike and still mean different things. A chain that has deployed four different counting technologies across its estate of retail locations over the past decade cannot produce a meaningful ten-year trend unless it has recorded the impact of each transition.
Mall operators and property owners face the same problem at a larger scale: multiple tenants and counting systems, and a footfall figure for the whole centre that often rests on methodological choices no two tenants made the same way.
Can a published index show whether we beat a competitor?
Not reliably, and benchmarking against a competitor is where the problem most readily goes wrong. Published footfall indices aggregate data from multiple operators and technologies, which is useful for macro trends such as whether retail footfall overall is rising or falling against the prior year. They cannot reliably tell you whether your specific site is outperforming or underperforming a specific competitor in the same retail format, because the underlying data came from different counting systems with different calibration standards.
A published index works best as a directional signal that shows whether the market is moving with you or against you. Using it as proof that your own locations are beating the competition goes further than the data methodology can typically support.
Can consistent footfall data strengthen a rent review?
It can, provided the data is internally consistent, and then it has clear, defensible value in lease negotiations. A tenant with validated footfall records for their unit (measured consistently, documented properly and produced by a system that distinguishes customers from staff) has a concrete basis for a rent review, which anecdote alone cannot provide.
A landlord with the same kind of records can show prospective tenants that the centre’s footfall is real, consistent and independently verifiable, and sophisticated tenants give that more weight than a bare total from an unknown system at an unknown calibration standard.
Can I trust a footfall trend across years and sites?
Only if the count stays consistent. Comparing performance over time, across a portfolio and against market indices shows whether a location is improving or declining, but it assumes that what you counted this year was counted the same way as last year, and the same way as at the site two hundred miles away. Every footfall benchmark rests on four things in the measurement behind it: a consistent method, documented definitions, calibrated hardware and a data trail that survives staff turnover and system upgrades. The analytics platform and the data deliverables it produces have to rest on a documented method.
Sources
- West Midlands Combined Authority (2025). Revitalising West Midlands Town Centres and High Streets: A Comprehensive Assessment of Footfall Data Collection. https://www.wmca.org.uk/what-we-do/research-and-insights/reports/research/revitalising-west-midlands-town-centres-and-high-streets-a-comprehensive-assessment-of-footfall-data-collection/
- Philp, S., Dolega, L., Singleton, A., & Green, M. (2022). Archetypes of footfall context: Quantifying temporal variations in retail footfall in relation to micro-location characteristics. Applied Spatial Analysis and Policy, 15(1), 161–187. https://doi.org/10.1007/s12061-021-09396-1
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Frequently asked questions
What is footfall benchmarking?
Footfall benchmarking compares visitor counts across locations, time periods or competitors to give performance a reference point. A site that attracts more visitors than comparable sites, or more than it did the previous year, is said to outperform the benchmark. For the comparison to mean anything, it needs the same counting method, the same definition of what counts as a visit and the same handling of staff, service entrances and multiple-entry visitors.
Should footfall benchmarks use absolute counts or indices?
Both have a place. Across sites and operators an index is often more useful than an absolute count, because it expresses each site's performance relative to a baseline, typically 100, so sites with very different absolute volumes can be compared fairly. Absolute counts suit internal planning, staffing and revenue correlation, where the actual number of visitors matters.
What makes a footfall benchmark misleading?
The most common problem is comparing counts produced by different measurement methods: a camera system that has not been calibrated against a manual control count, a sensor that does not distinguish staff from customers or a Wi-Fi-based system that counts devices rather than people. Even within one method, definitional differences add up, for example whether the count includes visitors who only enter the lobby, whether children are counted and what a bi-directional door sensor records when two people pass at once.
How does a footfall benchmark help in lease negotiations?
Consistently measured footfall data gives an objective basis for negotiating rent and service charges. A tenant who can show with validated data that their location draws significantly lower traffic than comparable units in the centre has a concrete argument. A landlord who can show that footfall at their property outperforms the broader market has equally strong grounds.