Scraping Google Reviews
You can legally scrape the 5 most recent reviews from any Google business profile page using our Google Reviews Scraper, which works through data scraping the official Google Maps API.
You’ll be able to scrape the full Google review text as well as extract data on the reviewer and timestamp of the review. This can be really helpful if you’re scraping a large set of Google businesses and want to get a sense of the general reviews for a given business category and location (perhaps to train a large language model with).
Scrape a Single Business
To collect the reviews from Google Maps of a single business, you’ll need to collect an identifier of that Google business profile and then provide that identifier to a given API to fetch the reviews back.
Via Google Maps API
We suggest using the Google Maps API as it’s the official API that Google provides and will never stop working. The only downside is that it will only return the most recent 5 reviews at a time. This can be OK if you’re more interested in extracting the reviews of a single business over time - you just need to query the API on an ongoing basis.
To fetch the reviews for a single business, you’ll need to know it’s Google Maps API “Place ID,” which you find from our Google Maps Search Results Scraper. Enter your search query (e.g. business name) along with coordinates and then look for the place_id column as shown below:
Once you have the Place ID, head to the Google Maps Place Details Lookup and supply the Place ID there to download the 5 most recent reviews in the result › reviews collection as shown below:
Via SERP APIs
If you absolutely must scrape all of the reviews for a particular business, there are a few unofficial APIs that provide a wrapper around Google Maps’ public pages and collect the data through unofficial means.
We cannot recommend using them for legal reasons (as they likely facilitate a breach of Google’s Terms of Service), but realize that some people will use them anyway! Also bear in mind these APIs will typically be very slow and can be expensive if scraping a lot of data.
SERP API
Serp API provides a Google Maps Review API you can refer to, where you simply provide a Google Place ID and you’ll be able to paginate through all of the reviews using the next_page_token parameter.
If you need help accessing this API, we offer a SERP API Google Reviews Scraper, which will access the SERP API endpoint on your behalf and extract out the data for you.
Scale SERP
Another company that offers this API is Scale SERP, with their Google Place Reviews API, which works similarly to SerpAPI’s to scrape reviews.
You can also access this through our Scale SERP Google Reviews Scraper as an alternative to building your own client.
Scrape 1,000s of Businesses
If you’re not as obsessed in the number of reviews scraped per business, but are more interested in collecting a large sample of reviews for a given business type and area, then we’ll walk through how to do this using the official Google Maps API, which returns the most recent 5 reviews for each business.
1. Collect Place IDs
You’ll need to build a list of all the Place IDs you want to scrape the reviews of. You can use our Google Maps Search Results Scraper to do this, where you can provide any search term and location and our tools will extract out the businesses for you.
2. Extract the Reviews via Workflows
Once you’re happy with the types of businesses you’re getting back from your query, you can use the Google Maps Search Results to Place Details Workflow to automatically run the search for all places and then look up the 5 most recent reviews for each place. The workflow will automatically combine the results into a dedicated CSV file just for the reviews, where each row will contain a single review and reference to its parent business.
Why Scrape Google Reviews?
One of the best ways to perform market research is to ask customers what they think of existing businesses. Web scraping Google Maps reviews allows us to do that effortlessly, as we get a somewhat unbiased snapshot of what everyone is saying about businesses in a given area. When fed to a large language model, it can then extract out patterns that may help you find a new business opportunity you hadn’t considered before.