Chains and franchises show up on Google Maps the same way single-location businesses do, as individual listings, one per branch. A coffee chain with forty outlets is forty listings. That's easy to miss, and it means the multi-location structure of a market is hidden in plain sight. If you want to find every branch of a brand, or spot which businesses in a category run several locations, the data is all there. It just has to be pulled and grouped.
This matters because a multi-location business is a different kind of prospect and a different kind of competitor than a single-site one. Bigger accounts, decisions made at a head office, expansion worth tracking. This guide covers why multi-location structure is worth surfacing, how chains appear on Maps, and how to find and group them with Livescraper.
Why Multi-Location Structure Matters
Knowing whether a business runs one location or twenty changes how you treat it:
- Account size. A multi-location business is usually a larger account, sold to differently and worth more, so identifying them lets sales prioritise.
- Where the decision sits. A franchise or chain often buys at head office rather than branch by branch, which changes who you contact.
- Competitor expansion. Tracking how many locations a competitor runs, and watching that number over time, is a direct read on how aggressively they're growing.
- Expansion-ready single-site businesses. The flip side is also useful, since a strong single-location business can be a prospect for anyone selling what a business needs to open its second.
How Chains Appear on Maps
A multi-location brand doesn't announce itself as one entity. Each branch is its own listing with its own address, reviews, and hours, but the branches share signals: the same or a very similar business name, often the same website domain, and sometimes a shared central phone number. Those shared fields are what let you group separate listings back into the brand they belong to.
Finding and Grouping Them
This is the one case where you don't want to deduplicate. Normally overlapping results get collapsed; here the separate branch listings are exactly what you're after, and the goal is to group rather than remove. The method is to pull the category across the areas you care about, then group the results by business name, website domain, or shared phone. Count the listings per group, and the brands with several locations sort themselves to the top. What you get is a view of which businesses in the market are multi-location and how many branches each runs.
Use Cases
- Enterprise sales teams identifying larger, head-office-led accounts
- Franchise suppliers mapping every branch of a target brand
- Competitive intelligence tracking a rival's location count over time
- Analysts measuring how consolidated or fragmented a category is
Key Livescraper Features for Finding Multi-Location Businesses
- Google Maps Data Scraper returns each branch as its own record with name, website, phone, and address, which are the fields you group on.
- Multi-area pulls cover a brand's full footprint by running the category across every region in one task.
- Structured export in CSV or JSON supports grouping and counting by name, domain, or phone.
- Scheduled re-runs let you track a competitor's location count over time by comparing pulls.
Tracking Growth Over Time
The method gets more useful when it's repeated. Re-run the same category-and-area pull on a schedule, group again, and compare the location counts to the last run. A brand that's gone from eight branches to eleven is expanding, and that's a leading signal worth acting on, whether you sell to them, compete with them, or track the market. A single snapshot tells you the current structure; repeated snapshots tell you the direction.
A Worked Grouping Example
Say you pull every dry cleaner across a metro area and get four hundred listings back. Grouped by business name and website domain, the picture changes. Most of the four hundred are single-location independents, each appearing once. But a handful of names repeat: one brand shows up eleven times, another seven, a third four. Those are the chains, and you just found every one of their branches in the market along with an exact location count for each.
That count is the useful part. The eleven-branch operator is a different sales target than a single independent, likely with a head office that makes purchasing decisions and a budget to match. The independents, all four hundred minus the chains, are a different play entirely, better suited to a product that helps a small business run better rather than one that serves a multi-site operation.
Handling the Edge Cases
Grouping isn't always clean, and a couple of situations are worth watching. Some franchises operate each branch as a separate legal business with slightly different names, so exact name matching misses them; grouping on the shared website domain or a central phone catches those better. On the other side, two unrelated independents can happen to share a common name, so a match on name alone occasionally groups businesses that aren't related. Checking that grouped listings also share a domain or phone before treating them as one brand avoids that.
For most purposes, grouping on the combination of name and domain gets you an accurate read, and the exceptions are few enough to eyeball. The output is a clear split between the chains worth an enterprise approach and the independents worth a volume one, which is a more useful starting point than a flat list that treats a forty-branch operator and a corner shop the same way.
Conclusion
Multi-location businesses hide in plain sight on Google Maps, since each branch is just another listing. Grouping those listings by shared name, domain, or phone, rather than deduplicating them, surfaces which businesses run several locations and how many each has. Livescraper pulls the branches across a whole region and keeps the fields you group on, so a flat list of listings becomes a clear view of the chains and franchises in a market, and repeated pulls turn that into a read on who's expanding.
Related reading: How to Use Google Maps Reviews for Competitor Analysis, How to Find Industry-Specific Businesses Using Google Maps, How Google Maps Data Powers Location Intelligence.
Frequently asked questions
How do chains show up on Google Maps?
As separate listings, one per branch, each with its own address and reviews. They share signals like the same business name, website domain, and sometimes a central phone, which is what lets you group them.
Should I deduplicate the results?
No. Here the separate branch listings are what you want. Group by name, domain, or phone and count, rather than removing repeats.
Why does multi-location structure matter for sales?
Multi-location businesses are usually larger accounts that often buy at head office, so identifying them changes both prioritisation and who you contact.
Can I track a competitor's expansion?
Yes. Re-run the pull on a schedule and compare location counts. A rising count is a direct read on how fast a competitor is growing.
What fields do I need to group on?
Business name, website domain, and phone number. Keeping those in the export is what makes grouping reliable.
