Checking footfall before you sign a lease
A landlord says the street is busy. How to check it with footfall data in an afternoon, what to compare it with, and which questions footfall cannot answer for you.
Before you sign a lease, check how busy the street really is, at the hours your business needs, against two or three other streets you could choose instead. Footfall figures from Mobility Footfall give you the average day’s people-hours around the unit, the busiest hour and day, and the trend on the week before, so you can test what the agent or landlord tells you instead of taking it on trust.
This is a checklist for founders and expansion teams who are about to commit to a unit for several years. It covers what to measure, what to compare it with, a worked example in Toronto, and the questions footfall leaves open.
Why a lease needs its own check
A lease is usually the biggest fixed cost a small business signs, and the hardest to undo. Agents show units at the hour they look best. A Saturday afternoon viewing tells you little about a Tuesday morning, and the Tuesday mornings are most of the year.
Footfall data replaces the one visit with an average over weeks. It is still a measure of presence, in people-hours, not a count of people who would walk in. Treat it as one piece of evidence beside rent, visibility and who your rivals are.
The five checks
- The level. Run the unit and two alternatives with the same circle (200 metres keeps it to the street itself) and the same window, the last 30 days. Compare footfall_daily between them; the figure means most when it sits next to others measured the same way.
- Your hours. Tick Busy hours. If you sell lunch, the midday share matters more than the daily total. A unit with a lower total but a stronger midday can beat a busier street that only fills at night.
- Your days. Tick Busiest days. A business that relies on weekends should look at the weekend on its own: run the block again with Days set to Weekends only.
- The direction. Tick Trend. It compares the last 7 days with the 7 before, so it needs at least two weeks of data. A street that is falling week after week deserves a question to the landlord.
- The competition. Add Nearby places around the unit, counting the businesses of your kind within a few hundred metres. A busy street with five rivals is not the same as a busy street with none.
An example in Toronto
Say a founder is choosing between three units for an independent cafe in Toronto. The city is not short of cafes: xMap’s places database lists 622 cafes within 10 km of the centre of Toronto in November 2026. Of the 312 nearest the centre, 47 belong to a chain and 265 are independent, they are rated 4.4 on average, and 31 of the 309 with an opening date opened in the last year.
With that much competition, the street matters. The made-up results for the three units might read like this:
| Unit | Footfall a day | Peak hour | Morning share | Cafes within 300 m |
|---|---|---|---|---|
| A, by an office tower | 38,000 | 08:00 | 44% | 6 |
| B, near a park | 21,000 | 14:00 | 27% | 1 |
| C, on a high street | 45,000 | 19:00 | 18% | 4 |
Made-up figures, to show how the checks fit together.
Unit C has the most footfall, but its crowd arrives in the evening, when a cafe that closes at 17:00 is shut. Unit A has a strong morning, which suits coffee, but six rivals already serve it. Unit B is quieter overall, yet it has one rival and an afternoon crowd that a cafe with good seating could own. The highest number is not the answer; the right shape of day with room to compete is.
What footfall cannot tell you
- Whether the people present would buy from you. Office workers on a lunch break and tourists on a walking tour both count.
- Who they are. For residents around a unit, add Demographics, which covers some countries (among them France, Canada, India, Thailand, Egypt and Australia) but not the United Kingdom or the United States.
- Where they come from. Trips that end near a place are measured only in Sao Paulo so far.
- What happens next year. A new station or a closing anchor store will change the street, and footfall only shows the past few weeks.
Doing it with an AI employee
If you look at units often, let a flow do the checks each time a new one comes in. A New rows trigger watches the sheet where you paste candidate addresses. Mobility Footfall adds the level, hours, days and trend; Nearby places counts the rivals within 300 metres; xMap LLM writes a short verdict for each unit from those figures alone; an Email sends it to you.
The result is a note per unit within minutes of adding it: its footfall against the others you have checked, when its street is busy, how many rivals it has, and the questions to put to the landlord before the second viewing.
Questions
Can I check footfall for a unit I have not leased yet?
Yes. The block works on any address or position, so you can check a unit before you sign, or before you even view it.
Is a higher footfall always better?
No. A higher figure at hours when you are closed, or with many rivals nearby, can be worth less than a quieter street whose busy hours match yours.
Can footfall data replace a site visit?
It replaces guessing from one visit, not the visit itself. Go and stand there at the busiest hour the data shows, and again at the quietest.
Does it work for a unit inside a shopping centre?
It measures presence in a small area of the map around the position you give, so a unit inside a centre gets the figures for that part of the centre, not for its corridor alone.