Google Maps data extraction
Bulk Google Maps scraper
Building a list that covers a whole state means running the same search across dozens of cities. The problem is not the scraping, it is what happens when those exports overlap. This page covers how to run large sessions and end up with one clean row per business instead of a spreadsheet full of near-duplicates.
What you get
- Queue many city and category searches in one session
- Deduplicates by place identity, not just by business name
- One million monthly credits on the Pro plan
- Keeps a session history so an interrupted run can be resumed
- Consistent column order across every export in a session
- Excel output for lists too large to open comfortably as CSV
Google caps results per search, so split the search
A single Maps query stops returning new results well before it has shown you every matching business. Asking for plumbers in California returns a fraction of them no matter how long you scroll. The way around it is many narrow searches rather than one broad one: run the query per city, and in dense metros, per suburb or postcode. Twenty narrow searches beat one wide one every time.
Why overlapping searches produce duplicates
Adjacent searches share territory. A business on the boundary between two suburbs shows up in both. Matching on business name alone does not catch it, because chains legitimately share names across locations and the same listing can render with slightly different formatting. Deduplication works on the underlying place identity, so two captures of one location collapse and two genuine branches stay separate.
Planning a run before you spend credits
Decide the geography first and write the list of searches down. For a state, that is usually the top forty or fifty population centres rather than every town. Run one of them, export it, and look at the fill rate on the columns you care about. If emails come back empty across the board in that category, you want to know after one search rather than after fifty.
What a large export costs in credits
Credits are consumed per business row extracted, so a run that touches 20,000 listings costs 20,000 credits. Pro includes one million a month, which covers most agency workloads without rationing. The cost worth watching is not credits but time spent cleaning a list you extracted too broadly, which is why narrowing filters before the run pays for itself.
Handling the file once it is large
CSV stops being pleasant somewhere around a hundred thousand rows, and Excel has its own limits. Export in per-city batches rather than one enormous file, keep the batches named by search, and load them into your CRM separately. If a batch turns out to be bad, you re-run one city instead of the entire state.
Frequently asked questions
Why does one search stop returning new results?
Google limits how many results a single Maps query will surface. Splitting the query by city, suburb or postcode is what increases coverage, not scrolling for longer.
Will the same business appear twice across overlapping searches?
No. Deduplication works on place identity rather than business name, so one location captured in two searches collapses to a single row while genuine branches stay separate.
How many credits does a bulk run consume?
One credit per business row extracted. Pro includes one million credits a month, which covers most large agency runs.
What happens if a long session is interrupted?
Completed searches stay in your session history, so you can resume from the ones that did not finish rather than starting the whole run again.
Should I export one large file or several?
Several. Batching by city keeps files a manageable size and means a bad batch costs you one re-run instead of the whole list.