How to analyze google maps reviews
Google Maps reviews sit on the place page: the listing customers open when they search for a restaurant, clinic, shop, or service business. They are the same reviews that often appear in the local map pack, which is why operators and local SEO teams keep coming back to them.
Maps does not offer a download button on the place page. Copying a few comments by hand works for a quiet listing. It falls apart once you have dozens or hundreds of reviews, truncated "More" text, owner replies, and dates you want to chart.
The honest way to get a file is our Google Maps Reviews Exporter, a Chrome extension we built for this job. Open the business on Google Maps, run the extension, and download CSV or Excel. It scrolls the reviews panel, expands truncated text, and can include reviewer name, star rating, full text, date, likes, owner replies, and photos. The free plan covers up to 100 reviews per export. Pro removes that cap and can queue several places. Get the extension from the product page, then come back here with the file.
We do not have a second extension for Google Search snippets, and we do not sell a Maps scraper API. If you already exported a listing last quarter, you can upload that older file too. Comparing two exports from different months is often more useful than one giant dump.
Sign in to Google in the browser before you export. When you are signed out, Maps often shows a short sample of reviews instead of the full list. Export for your own analysis. Do not republish reviewers' words as marketing copy.
Columns that matter for Maps files: rating, review text, date, reviewer name, owner reply, and like count. Rating and text are required for this analyzer. Date powers the trend chart. Owner reply shows response coverage. If you queue several places in Pro, keep each place in its own file, or add a place-name column, so downtown and airport locations do not collapse into one fake average.
Insights on Maps are local and operational. Look for wait time, parking, "they were closed," staff tone, cleanliness, and hours that do not match the listing. Restaurants should watch ticket time, food temperature, and noise. Clinics should watch booking and front desk. Multi-location brands should compare the same complaint theme across files rather than only comparing star averages.
A useful session looks like this: export one place, upload the CSV on this page, read the low-star themes, pick one fix the manager can make this week, then export again next month. The analyzer is deterministic keyword and phrase extraction, not a generative model, so the themes come from words that actually appear in the reviews.
Everything on this page runs in your browser. The file is not sent to Bozoma Labs.
Columns to include
- Rating / stars (required)
- Review text (required)
- Date
- Reviewer name
- Owner reply
- Like count
- Place or location name, if you combine listings