Site selection with footfall and trade area data

Why is site selection such an expensive decision?

Site selection is one of the most expensive decisions a multi-site operator makes. In retail site selection, opening a new location commits years of rent, fit-out and people to one bet: that enough of the right visitors pass this spot at the right times. Yet most major investment and leasing decisions are still made on assumptions or thin data, such as a drive past the site, a broker’s brochure or a hunch about the neighbourhood. The movement that decides the outcome can be measured before the lease is signed: who passes, where they set out from, and how flows shift by day and season.

How do you analyse a site’s catchment and trade area?

Mobile network data (4G/5G) answers the broad questions in site selection: where visitors travel from (origin and catchment), trade area analysis at district scale, total flows along a corridor or high street, travel patterns between areas, and peaks and trends at city scale. It measures movement across whole districts, streets and open outdoor areas using anonymised, aggregated data. This is location intelligence, or location analytics, based on real movement data rather than demographic models. Because the input is network data, there is no hardware to install at a site you do not yet occupy, and the method covers areas that Wi-Fi and sensors are not built to measure.

How do you compare candidate sites?

District-level flows put candidates side by side: which district carries traffic, when, and how movement runs between the areas in question. Peaks and trends by day and season count as much as volume, because they show whether a corridor that looks busy on a Saturday viewing is quiet on the weekdays your format depends on. For destination formats, catchment shows how far a location’s pull would need to reach. Retail destinations use the same measure to understand the trips people already make to them.

Your existing sites add a benchmark. Passers-by, capture rate and visit counts per building quantify the pull of locations you already know, and property companies measure the same metrics across the portfolio and across seasons. The candidate site itself is read on flow, catchment, peaks and trends from mobile network data.

How do you reduce the risk before you sign for a new location?

Three practical steps reduce that risk:

• Check the flows before the unit. Confirm at district level that the area carries the visitors you need before you debate frontages within it.
• Trial the location before you commit to a long lease. A time-boxed pop-up is a deliberate test. Its capture rate shows how the concept performed against the street it was given, which separates the pull of the location from the strength of the concept.
• Measure what you build. Where you develop a site, visitor pull can be measured before, during and after the project, so the investment case is checked against what actually happened.

However the analysis is run, the metrics arrive through the same dashboards and documented API as every other Bumbee Labs method, so a siting study sits alongside the rest of your footfall data.

How private is mobile network data at district scale?

Mobile network data is anonymised and aggregated before it is analysed. Movement is measured as flows across large areas, never as individuals, and there is no device-level tracking.

The metrics behind a location decision, from catchment to capture rate, are laid out on data deliverables.

Bumbee Labs is the company behind the only footfall method in Europe approved by a data protection authority.