Google Maps data for franchise site selection
By Doug Nielsen, Product Manager · Updated · first published
For franchise site selection, Google Maps listings measure competitor density well, incumbent strength roughly, and under-service only once divided by population. Settle those before signing a lease or granting a territory.
Our Google Maps data extractor gives each competitor's postal code, coordinates, rating and review count, enough to count, map and grade them. For a baseline, our local market size calculator estimates how many of a business type a town's population typically supports.
Key takeaways
- Count competitors and substitutes, one search per ZIP code.
- Rank areas by businesses per resident, not raw counts.
- Listings show the competition, not revenue, foot traffic or rent.
- Re-scrape right before signing; new entrants change the picture.
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What the data genuinely supports
Competitor density: scraping your category across every ZIP in a region gives a saturation map, gaps included.
Co-tenancy: map the categories that sit near your concept (a gym near a smoothie bar) to find where that cluster already exists.
Incumbent strength: ratings and review counts separate strong incumbents from tired 3.6-star operators.
A five-step site-selection process
Define the competitive set narrowly and broadly
Count direct competitors and substitutes, what a customer would choose instead. The substitute count is the one people forget.Scrape the whole region by ZIP code
One search per ZIP code keeps most result sets under Google's feed cap, so area counts stay comparable instead of all hitting the same ceiling.Normalize by population or households
Raw counts favor dense ZIPs. Businesses per 10,000 residents, from census or ONS population, is what identifies genuine under-service.Use review velocity as a demand proxy
Total reviews divided by roughly how long the business has operated hints at throughput, directionally only: review counts also reflect how hard a business asks for reviews.Re-run before committing
A site that looked under-served six months ago may have two new entrants.
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What Maps data cannot tell you
Revenue, foot traffic, rent, lease terms, road traffic counts, whether the plaza's anchor tenant is leaving: none of that is in a listing. Use listings for the competitive layer and mobility data, demographic data and a site visit for the rest.
Franchise territory design
The same per-ZIP counts size exclusive territories at a target customer density and show where two would cannibalize each other. Building a territory list for field reps covers grouping ZIPs into balanced units.
Common questions
Can I measure how busy a location is?
How large an area can I scrape for this?
Written by
Doug Nielsen, Product Manager
Doug works on Hubertino; the guides on this site are published under his name. Last updated .