A Google Reviews scraper for any Maps place page
The Kavex Google Reviews scraper exports the review history of any business on Google Maps into a clean, sortable file. Paste the place URLs you want and get back every review with its rating, text, author and date — no copy-pasting from the Maps panel one comment at a time. It is built for reputation tracking and competitor research where you need the raw feedback, not a summary star count. You pay per review returned.
Sign up to useWhat it does
Give the Google Reviews scraper one or more Google Maps place URLs and it opens each listing and reads the reviews the way a visitor would, scrolling through the history rather than stopping at the first handful Maps shows by default.
Every review is returned as its own row with the star rating, the full text, the author name and the date it was posted, alongside the place name and its overall rating and review count. That gives you both the headline numbers and the detail behind them in a single export.
You control how deep to go with a per-place cap, so you can pull a recent sample from many businesses or the full history of a few. Either way the output is structured and ready for a spreadsheet, a dashboard or a text analysis.
The detail is where the value sits. A four-star average tells you little, but the reviews behind it tell you whether customers complain about wait times, pricing, staff or parking — and which of those a competitor consistently gets wrong. Pulling the full text rather than the score turns Google Reviews into a source of marketing angles, product feedback and outreach hooks. Run the same place list on a schedule and the export also becomes a tracker: fresh rows each week show how sentiment is moving, which negative themes are growing, and whether a recent change landed well. For a multi-location brand, that is a reputation dashboard built from one repeatable job.
Use cases
- Multi-location operators tracking review sentiment across every branch from one weekly export.
- Competitive analysts mining a rival’s reviews for the complaints that make the sharpest marketing angles.
- Agencies building a sentiment dashboard for a chain or franchise client.
- Product teams collecting customer language in volume to inform messaging and roadmap priorities.
Sample output
Each review is one row, tied to its place:
| Place | Overall rating | Author | Rating | Date | Review |
|---|---|---|---|---|---|
| Heilige Boontjes | 4.5 | Sanne K. | 5 | 2026-04-28 | Best flat white in Rotterdam, friendly staff. |
| Heilige Boontjes | 4.5 | Tom B. | 3 | 2026-04-20 | Good coffee but a long wait at peak times. |
| Hopper Coffee | 4.4 | Aisha L. | 5 | 2026-04-26 | Lovely space to work, strong wifi. |
| Hopper Coffee | 4.4 | Jens P. | 2 | 2026-04-15 | Tables were not cleared, felt rushed. |
How it works
The Google Reviews scraper loads each place page in a real browser and paginates through the review feed, collecting entries until it reaches your per-place limit. Traffic routes through rotating residential proxies, because Google throttles repeated requests from data-centre IP ranges and a proxied job completes in full.
Every run is a live scrape, so the reviews reflect what is on the listing that day, including comments posted hours earlier. Reviews are tied back to their place, so a job covering several businesses returns one file you can split or pivot by location.
Frequently asked questions
How many reviews can it pull per place?
You set a per-place cap and the scraper paginates up to it. That lets you take a quick recent sample across many places or a deep history on a few, with predictable job size.
Can I scrape several places in one job?
Yes. Paste a list of Google Maps place URLs and the scraper processes them in sequence, returning one combined file with each review tied to its place.
What if a place has no reviews?
A place with no reviews is returned with its name and a zero count rather than causing the job to fail, so you can see clearly which businesses simply have no feedback yet.
How do results export?
Reviews download as a CSV with one review per row, including place, author, rating, date and full text — ready for a pivot table or a sentiment analysis.
Try it free — 1000 credits on us
Pay per result — no subscription, no seats. New accounts start with 1,000 free credits.