Reading footfall around a shopping centre: what it shows and how to use it

Footfall around a shopping centre tells you how much human presence there is in and around the building, measured in people-hours: one person staying two hours counts as two. It is a good guide to how busy a centre is, when it peaks and whether that is changing week to week. It is not a count of shoppers. It includes staff on long shifts, people using a station under the centre and anyone sitting in its cafes, so it is best used to compare centres measured the same way, and to watch one centre over time.

This is for retailers deciding which centre to take a unit in, landlords and asset managers tracking their own centres, brands planning pop-ups and kiosks, and agencies selling advertising space inside malls. It covers choosing the area to measure, reading the figures, a worked example in Sao Paulo, and an AI employee that reports on a set of centres every month.

Choosing the area to measure

A shopping centre is a large building, often with car parks, a bus station or a metro stop attached. The area you add footfall up over decides what you are measuring.

• Up to 200 m: the block of the map the centre's entrance sits in, an area of about 0.1 km². For a compact centre this is mostly the building itself.
• 300 to 500 m: the whole of a large mall and its car parks, but also the streets and anything else around it.
• Wider: the district. Useful for a centre's surroundings, not for the centre.

Choose the smallest area that covers the building, and use the same one for every centre you compare. Put the point at the middle of the building, not at its postal address, which may be a side entrance.

How to read the figures

Footfall per day

The average day's people-hours around the centre. It is the headline for comparing centres, as long as they were measured with the same radius over the same days.

The busiest hour and how the day splits

The block gives the busiest hour and how presence splits between morning (6:00 to 12:00), midday (12:00 to 16:00), evening (16:00 to 21:00) and late night (21:00 to 6:00), in the centre's own time. A centre whose share peaks in the evening is used after work and for dining; one that peaks at midday is a lunchtime and errands centre. The parts are of different lengths, so compare each part between centres rather than parts within one centre.

Busiest and quietest day

Most centres peak at the weekend. One that peaks on a weekday is often built around offices or a station, and a brand that needs weekend family traffic should notice that.

The trend

The last 7 days against the 7 before. A single week means little; a trend that points down month after month, while nearby centres hold steady, is worth a conversation with the landlord.

A worked example in Sao Paulo

The figures below are made up. A sportswear brand is choosing between two shopping centres in Sao Paulo for a store, and measures 300 m around each over the last 30 days.

Invented figures, for illustration only.

Centre B is busier, but its Friday peak at 18:00 and visitors spread across the city suggest a good part of the presence is commuters changing trains. Centre A is less busy, with a Saturday peak and visitors from the residential districts around it: families on a shopping trip, which is the brand's customer. The brand shortlists A, and asks B's landlord for its own door counts before ruling it out.

Sao Paulo is the one city where the block can say where visitors come from and how they travel, so far. In other cities the same comparison rests on the busy hours and days alone.

Mistakes to avoid

• Comparing a mall's footfall with its own door counts. The landlord's counters count entries; footfall counts presence over time. They answer different questions and will not match.
• Comparing centres measured at different radii. A 500 m circle around a small centre takes in its streets; a 200 m circle around a big one misses half the building.
• Reading staff as shoppers. A large centre's staff spend eight hours a day there. Their presence is in the figure, so a big centre with quiet shops can still look busy.
• Judging a trend from one week. A holiday, a sale or bad weather can swing one week. Wait for several.

A monthly report on your centres

An AI employee can measure the same centres each month and write you a short report.

1. Schedule, on the first day of each month.
2. My data with the centres you care about, each as a point at the middle of its building.
3. Mobility Footfall with Around each place set to 200 or 300 m, Time window Last 30 days, and Footfall, Busy hours, Busiest days and Trend chosen under Return.
4. Nearby places, Each incoming place with counts, for the shops of your sector within the same distance, so each centre also shows how many rivals are inside or next to it.
5. xMap LLM on the whole list, told to compare the centres and point out any whose trend is falling, using only the figures given.
6. Make a report, sent by email to the property team.

What lands in the inbox each month is a PDF with each centre's footfall per day, its busy hour and day, its trend and its rival count, and a short written comparison. Because the figures arrive about 10 days late, the report covers the 30 days that ended about 10 days before it was sent, which is fine for a decision about a lease.