Walking and cycling areas: the real catchment of a city shop

For a shop in a dense city, the area that matters is the one people can walk or cycle to in a few minutes, not the one they could drive to. Draw a 10 or 15-minute walking area around the shop, and a cycling area for the wider ring, then count the residents, the rivals and the places that bring people past the door inside each. That tells you who the shop can realistically serve, and which rivals actually compete for the same customers.

This article is for owners and expansion leads of neighbourhood shops: bakeries, florists, pharmacies, bike shops, cafes, dry cleaners, convenience stores and small grocers. It explains why driving areas mislead in city centres, how walking and cycling areas are drawn, what to count in them, a worked example in Montreal, and an AI employee that keeps an eye on each shop's walking area.

Why a driving area is the wrong picture

Driving areas are made for suburbs and retail parks. In the centre of Amsterdam, Kyoto or Montreal, a 10-minute drive covers neighbourhoods whose residents would never cross the city for a loaf of bread. A shop that counts them overstates its market, and counts as rivals shops its customers never see.

Walking and cycling areas are tighter and follow the street grid. A river with few footbridges, a railway line, a motorway or a large park can cut them sharply, while a long straight avenue stretches them. Those shapes match how people actually move around a neighbourhood.

How the areas are drawn

The Travel area block draws the area reachable within a travel time on foot, by bike or by car, following the roads and paths, or within a distance along them. As a rough guide from the block's own description, a 15-minute walk reaches about a kilometre in a town. Areas go up to 15 minutes for now. Travel area passes on no items of its own: it hands the blocks after it an area to search, so everything they find inside comes back named after the shop and the area, such as "10 minutes walking of Plateau shop".

What to count inside a walking area

• Residents. Demographics gives how many people live inside the area, with age groups, in countries its population grid covers (Canada, France, India, Australia, Thailand and Egypt among them; not the United Kingdom or the United States).
• Direct rivals. Nearby places inside the area: the other bakeries, florists or bike shops a customer could walk to instead, with their ratings and whether they belong to a chain.
• Places that send people past. Stations, schools, offices, gyms and supermarkets inside the area. A florist near a station and a hospital sees different trade from one on a quiet street.
• New openings. Places in the area that opened in the last 12 months, which tell you whether the neighbourhood is gaining shops or losing them.

A worked example: a bakery in Montreal

This example is made up. A bakery owner in Montreal is choosing between two units for a second shop: one on a busy commercial street in a dense neighbourhood, one on a quieter residential street near a metro station.

For each unit she draws a 10-minute walking area and a 10-minute cycling area. Inside each walking area she counts residents, other bakeries and cafes, and the metro stations and schools. The commercial street's walking area has more residents but six bakeries already; the quieter street's area has fewer residents, one bakery, a metro entrance and two primary schools. The cycling areas overlap with her first shop for the commercial unit but not for the quieter one. She chooses the quieter street, because it brings new customers instead of sharing them with her own first shop and six rivals.

Common mistakes

• One size for every street. A 10-minute walk in a hilly old town covers less than on a flat grid. Let the area follow the streets rather than drawing the same circle everywhere.
• Counting rivals across a barrier. A shop on the other side of a railway may be close as the crow flies and far on foot. The walking area handles this; a circle does not.
• Ignoring the cycling ring. For bike shops, specialist food and anything people carry home, the cycling area is where many regulars come from.
• Expecting footfall from residents. Residents are people who live there, not people who walk past. For how busy the street is, footfall data is a separate measure, counted as people-hours and arriving about 10 days late.
• Population where it is not covered. In the United States or the United Kingdom, do not assume a resident count; rely on places and your own customer addresses.

An AI employee for each shop's walking area

1. Schedule: every Monday morning.
2. My data: your shops, each with its position.
3. Travel area: 10 minutes walking from each shop.
4. Nearby places: your kind of shop inside each area.
5. Only new: only rivals that were not there last week.
6. Email to the shop's manager, with a map link for each new rival.

Most weeks the email is empty or holds one name; when a rival opens within a short walk, the manager hears about it in the first week. Templates that work the same way: Who and what is within a 15-minute walk of a planned station, Offices with no bike share station nearby and Rivals within 10 minutes' drive of each store, which can be switched from driving to walking.