The job. Deciding which operator to chase, before you spend a year chasing them.
Most tenant targeting starts from a wish list: the brands everyone wants, ordered by how much everyone wants them. That list is the same in every scheme in the country, which is a good sign that it is not really about any of them.
The useful version of the question is narrower. Given this catchment, its existing mix, and what customers here already complain about, which operators are underrepresented, could trade here, and would want to? That question has evidence behind it, and a fair amount of that evidence is public.
What follows is the manual method. It works. It also takes the better part of a day per scheme, which is the honest reason products like ours exist.
A decision about one unit, made from everything around it.
Written for
A ten minute walk is not a circle. It is bounded by a dual carriageway on one side, a river on another, and it stretches further along the desire line people actually use. Draw the boundary by hand, and if you are not sure where it goes, walk it. Everything downstream is a count of what is inside this line, so getting the line wrong quietly ruins every number that follows.
Any routing tool that draws travel-time areas rather than distance rings.
What it misses. Better than a radius, still a model. It knows the road network but not that nobody crosses that underpass after dark.
One hour, on a weekday and again on a Saturday.
What it misses. The only source that tells you where the footfall actually stops. Slower than everything else here and worth more than most of it.
Go through the boundary systematically and record every operator and its category. The output you want is a count and a share per category: eleven coffee, three bakeries, one greengrocer, no homeware. Counts are what turn an impression into an argument, and the share matters more than the count because it is comparable with another area.
Search each category term inside the area and list what comes back.
What it misses. The broadest picture of what is trading, and the messiest. Categories are self-assigned and inconsistent, closed businesses linger for months, and one operator can appear under three labels.
Community-maintained map data, browsable in any map viewer built on it.
What it misses. Free and structured, and only as good as the local mappers. Coverage is excellent in some towns and close to absent in others, so use it to cross-check a list you built another way rather than as the list itself.
Walk the boundary with your phone and photograph every frontage.
What it misses. The only method that catches the unit that is trading but has no online presence, and the one that is boarded up but still listed.
Pick the category you are considering and read the reviews of the operators already in it, in this area. Not the star averages, the written text. You are looking for what recurs: queues, staff, price, cleanliness, opening hours, parking. If three of the four incumbents are being told the same thing, that is a market gap described by the market itself, and a well-run entrant walks into it.
On each operator's listing, read the last hundred and note what repeats.
What it misses. The single richest free source about a place. The default sort is not chronological, so change it, or you will read the same flattering three-year-old reviews everyone else has read.
The same exercise, on the operators that have a presence there.
What it misses. Longer reviews and a more deliberate reviewer, which suits hospitality. Much patchier outside it.
Before you build a case for an operator, find out whether they are opening at all, and where. A brand consolidating estate is not a target no matter how well they would fit. Their filings say more about this than their press does.
Search the operating company, then read the accounts and the filing history.
What it misses. Free and definitive on ownership, incorporation date, charges and the shape of the accounts. It will not tell you store-level performance, and small companies file very little.
Compare it against a copy from six months ago in the Internet Archive.
What it misses. A rough but real read on whether the estate is growing or shrinking, and in which regions.
Search the council's planning portal by applicant name, and check the premises licence register.
What it misses. Where new sites appear first, often months before an announcement. Coverage and search quality vary a lot by council.
The last check is whether the people this operator needs are actually in the catchment. This is the part where demographic data earns its place, and it is also the part that is least decisive on its own: two catchments with identical income profiles can be completely different propositions once you know what is already trading in them.
Build a custom dataset for the output areas your boundary covers.
What it misses. Authoritative, granular, and about residents only. In a destination that draws visitors, residents are a minority of the customers.
Compare search interest for the brand and the category by region and over time.
What it misses. Good for relative interest and rising queries. It is search behaviour, not spend, and small areas return noisy results.
Assets get compared with other assets of a similar size or ownership. Visitors do not think that way. They compare where they went with the other places they could have gone that afternoon, which is a geography question. Pick your comparison areas by where your visitors could plausibly have gone instead.
A category can be shrinking nationally and be underprovided on your street. The national number describes an average of thousands of places, none of which is yours. Use it for context and never as the finding.
An operator can hold a 4.4 while its written reviews are steadily complaining about the same thing. The rating is an average over years, weighted by whoever bothered to rate. The text is what people are saying now.
Or have it run for you
Draw the boundary once and every place inside it is collected for you, with category, rating and review volume.
The review text for those places is read rather than counted, and the recurring themes come back named.
A prospective brand is checked against that specific catchment instead of against a general sense of the market.
Run it again in six months and the answer is comparable, because the method does not change between runs.
Should we sign this brand?
The brand against your catchment on local competitors, customer experience, audience, pricing and category fit, on one page you can put in front of a landlord or a partner.
Which categories are we actually short of?
Your area against up to three others, with the category gaps ranked and each one carrying its evidence. Differences resting on thin evidence are reported as thin.
Sign up free. The first area is on us, and it takes a couple of minutes to set up.
Get started free