Picture Sofia at her kitchen table on a Tuesday night. The kids are down, the dishwasher is running, and she has a dozen browser tabs open trying to settle one question: which town gets the second truck. She owns a plumbing company, she's ready to expand, and she's decided to do the homework herself rather than guess.

By eleven she has four tabs of Census tables, two commercial listing sites, a Google Maps search for every plumber in a forty-mile spread, and a spreadsheet she's already renamed twice. It's genuine research, and most owners who start it never finish. An adjacent-market study is that same night of homework, handed back to you and run for every town in range instead of the two you had a hunch about.

I wrote a general walkthrough of what's in an expansion study a while back. Think of this as the narrower cut: the specific homework behind choosing your next adjacent town, and the evenings it takes to do by hand.

Every candidate town, not the two you already like

Sofia's list starts with two names, the towns she drives through and already pictures a truck in. The homework she keeps skipping is the boring part: writing down every town 18 to 25 miles out, including the ones she has no feel for. That radius usually holds ten or a dozen candidates, and the winner is often one she'd never have shortlisted.

Widening that list is the whole point of asking which adjacent town to pick with data instead of instinct. A study builds the full list first, so nothing gets excluded just because it wasn't already on her mind.

The housing and income read for each one

For every town on that list, the same three numbers get pulled from public Census data: how old the housing stock is, how much of it is owner-occupied, and the median household income. Old homes owned by the people living in them, with enough income to pay for real repairs, is the profile that predicts steady work. Reading a local market off housing and income goes deeper on why those particular numbers matter.

Doing this by hand is where Sofia's evening disappears. The data is free and public. Finding the right table, pulling it for a dozen towns, and lining the results up so they actually compare is the slow part.

Competitor density by trade, rated

Now the map search. For each candidate office location, the study counts the competitors physically operating within about ten miles, broken out by trade line so an electrician isn't padding a plumber's count. Then each area gets rated Low, Medium, or High on density and staying power, weighing review counts and distance rather than the bare fact that other shops exist.

Everywhere has other plumbers, so a raw head count tells Sofia almost nothing. What she needs is a read on whether the top of the local pack is beatable or already locked up, and that takes judgment applied the same way across every town.

A real office with open ground around it

A Google Business Profile needs a real, staffable address, so the study also finds one. Not any address: a private suite with room around it, no direct rival sitting a few hundred feet down the road. In one case we've looked at, the recommended suite had no same-trade competitor in the building and the nearest one a couple of miles off, and the rent ran $345 a month, furnished and month to month. That was the cheapest office in the whole study, though, so read it as the floor rather than the going rate: most of the suites in that study sat between about $400 and $850. Either way it's a fraction of an ad budget, and it's an example we've seen rather than a price anyone is promised.

Finding an office with open ground around it is its own search, and drive time from the existing base is the kind of tiebreaker that doesn't show up in the Census at all.

The two-office pairing

If Sofia already runs one location, the question isn't only which single town scores best. It's which second address pairs with the first to cover the most ground with the least overlap. By hand that means sketching drive-time circles on a map and eyeballing where they double up. The study works the pairing out and keeps the overlap as small as it can, so the two offices reach as far as possible without stepping on each other.

The done-for-you version

Run all of it (a dozen towns, three kinds of data each, a competitor count, an office search, and the pairing math) and you've spent several weeknights on what a study returns as one ranked answer. That is the done-for-you version of Sofia's homework: same inputs, same public data, pulled for every candidate instead of the two she'd have checked, and scored the same way so the result is a decision rather than a folder of tabs. Strip the jargon and an expansion study for home services is just that night at the kitchen table, finished properly and run for the whole map.

FAQ

Can't I just do this research myself? Yes. Every input is public: Census housing and income tables, Google Maps for competitors, commercial listing sites for office space. The cost isn't access, it's time and consistency. A dozen towns at a few hours each, scored the same way so they actually compare, is a real project most owners start and don't finish.

How is this different from a general expansion study? It's the same engine pointed at one decision. The general expansion study explains the full method for any local service business. This piece is specifically about the adjacent-market call: the towns just outside your current reach, and the manual homework of comparing them well.

How many towns does it actually look at? Every town roughly 18 to 25 miles from your existing office, usually ten or a dozen, not a preselected two or three. The wide net is deliberate, because the market that scores best is often one you wouldn't have picked from the driver's seat.