Google Maps data extraction
Google Maps data extractor
Maps holds a usable dataset about local commerce: who operates where, in what category, at what rating, with what review volume. Getting it into a spreadsheet is what makes it analysable. This page is about the data itself, its shape and its limits, rather than about outreach.
What you get
- Consistent columns across every export, so files stack cleanly
- Category, rating, review count, hours and coordinates per listing
- Address captured as written on the listing for later parsing
- Deduplication so repeat captures do not skew counts
- CSV and Excel output for spreadsheet and BI tooling
- Google Maps URL retained for manual verification of any row
What each column actually contains
Business name, category, full address, phone, website, rating, review count, opening hours and the Maps URL come from the listing. Latitude and longitude come with it where Maps exposes them. Email is the one field that is derived rather than read, since it comes from the linked website. Knowing which fields are read and which are derived matters when you judge how complete a dataset is.
Categories are Google labels, not your taxonomy
Google assigns each listing a primary category from its own list, and business owners pick it themselves. The result is that similar businesses land under different labels and some labels are broader than they look. Treat the category field as a starting filter and expect to reclassify against your own taxonomy if the analysis depends on clean segmentation.
Addresses arrive as written, not parsed
Listings store the address as a single formatted string, and the format varies by country. Splitting it into street, city, region and postcode is a parsing step you do after export, and the rules differ per market. Keeping the original string in the export means you can re-parse later without re-scraping, which is why it is preserved rather than split at extraction time.
What the dataset cannot tell you
Maps shows what businesses and Google have published. It does not carry revenue, headcount, ownership structure or whether a business is still trading today. Listings for closed businesses linger. Rating and review count are the only quality signals available, and both are gameable. Any analysis resting on this data should treat it as a directory snapshot, not a verified register.
Building a dataset you can compare over time
Single snapshots answer less than repeated ones. Running the same searches on a schedule and keeping each export dated lets you see which businesses appeared, disappeared or changed rating between runs. That is where this data becomes genuinely interesting for market research, and it only works if the searches stay identical between runs.
Frequently asked questions
Which fields come from the listing and which are derived?
Name, category, address, phone, website, rating, review count, hours and coordinates are read from the listing. Email is derived by visiting the linked website.
Is the address split into separate columns?
No. It is exported as the formatted string Maps holds, because address formats vary by country and parsing them is better done once, after export.
Can I rely on the category field for segmentation?
Only as a first pass. Categories are chosen by business owners from Google list, so similar businesses often sit under different labels.
Does the data include revenue or company size?
No. Google Maps does not publish those, so they are not available at any price. Rating and review count are the only quality signals in the set.
How do I track changes over time?
Re-run identical searches on a schedule and keep each export dated. Comparing dated snapshots shows openings, closures and rating movement.