6 Best Google Maps Reviews Scraping Providers Benchmarked

To test how web scraping providers handle Google review extraction, we ran 2,500 requests across 5 providers on 500 Google Maps business URLs, and measured success rate, completion time, and metadata output.

Google Maps reviews scraping benchmark

You can read benchmark methodology for more details on testing process.

Domain coverage and available metadata fields by provider

✅✅ Structured JSON: Provider returns parsed review data with named fields, ready to use without additional parsing.
✅ HTML: Provider returns rendered HTML. 

Google Maps reviews scraping benchmark results

Bright Data reached a 39% success rate on Google Maps using its dedicated Google Maps Reviews dataset API, returning structured JSON with 26 fields per review including reviewer name, review text, rating, date, owner responses, photos, and place-level metadata. It was the only provider to return structured data on this domain.

Oxylabs offers a dedicated Google Maps source for local search results, but it is designed for retrieving location-based listings rather than extracting reviews from individual business pages. Since no dedicated review extraction source was available, we used the general Google source API (source: google) which accepts any URL. The API returned empty results across all 500 URLs, resulting in a 0% success rate.

Decodo offers various Google scraping configurations including Google Search and Google Maps local results, but does not have a dedicated endpoint for Google Maps review extraction. We used the web unblocker proxy with JavaScript rendering as a fallback, but it returned empty or error responses across all 500 URLs, resulting in a 0% success rate.

Zyte achieved the highest success rate on Google Maps at 41% using its Extract API with headless browser rendering. Review data was extracted from the rendered HTML using CSS selectors. While this was the top score on the domain, it reflects the broader challenge of scraping Google Maps, where reviews require JavaScript execution and often user interaction to fully load.

Nimble used its Web API with JavaScript rendering enabled, returning rendered HTML parsed with CSS selectors. It recorded a 1% success rate on Google Maps. Although the pages were rendered, the review content did not load in most cases, indicating that Google Maps requires more than standard browser rendering to display reviews.

How does Google Maps compare to other review platforms for scraping?

Google Maps was the most difficult domain in our reviews scraping benchmark. The highest success rate was 41%, far below what we measured in our Amazon review scraping benchmark (96%). Even our Yelp review scraping benchmark, where two providers scored 0%, saw a top result of 77%.

On Google Maps, two out of five providers recorded 0%, one scored 1%, and the top two reached 39% and 41%. No other domain in the benchmark had such uniformly low results across providers.

The main difference is how review content is delivered. On Amazon and Trustpilot, reviews are present in the initial page HTML or available through structured APIs with high reliability. On Google Maps, reviews are loaded entirely through JavaScript after the initial page render, making them inaccessible to most scraping approaches.

Why is Google Maps the hardest review platform to scrape?

Google Maps reviews are not included in the initial page HTML. The page loads a shell first, then executes multiple JavaScript calls to fetch and render review content. In many cases, reviews beyond the first few require scroll interaction or clicking a “More reviews” button to appear.

This means standard HTTP requests return a page with no review data at all. Even headless browser rendering, which worked well on platforms like Tripadvisor and Yelp, produced limited results on Google Maps. The highest success rate among HTML-based providers was 41%, and two providers using proxy-based approaches recorded 0%.

Google Maps also uses aggressive anti-bot detection, including request fingerprinting and dynamic content gating. Combined with the JavaScript-dependent review loading, this makes Google Maps significantly harder to scrape than other review platforms where content is server-rendered or available through dedicated APIs.

Google Maps reviews benchmark methodology

We tested 5 web scraping providers on 500 Google Maps business review URLs, running each URL through all providers for a total of 2,500 requests. Providers were selected from web scraping companies with at least 100 employees. Each provider received an identical URL set, and we evaluated three metrics: success rate, completion time, and available metadata fields.

Response types

One provider (Bright Data) returned structured JSON with 26 parsed review fields via its dedicated Google Maps Reviews dataset API. The other four returned rendered HTML, from which we extracted review data using CSS selectors for five standard fields: reviewer_name, review_text, rating, review_date, and review_title.

Validation

Responses were validated in three stages:

1. Submission: The provider had to return an HTTP status code between 200-399, or 404.
2. Execution: For providers with asynchronous processing, the job had to finish without timeout or error.
3. Data check: The response had to include extractable review data. For JSON, this required at least one review containing a review_text string or a rating integer. For HTML, at least one CSS selector had to return content.

We pre-tested each provider with broken URLs, known 404 pages, and pages with no reviews to understand how they report these cases. When a provider correctly signaled a missing or empty page, the result was counted as valid.

A cross-provider check was then applied: if one provider returned no data on a URL where another provider successfully extracted reviews, that empty result was marked as a failure. This separated pages with no reviews from cases where the provider failed to extract available data.

Completion time

We measured wall-clock time from the initial request to the final response, including any async polling or queue time.

URL selection

The 500 URLs were drawn from Google Maps business pages across a range of review counts, business types, and locations. Both maps/search and maps/place URL formats were included. Locale parameters and invalid formats were removed before testing.

Test conditions

All providers operated under the same constraints:

• One request at a time, no parallel execution
• 2-second delay between requests
• HTTP 429 handled with 30-second backoff and up to 3 retries
• 300-second submission timeout
• 600-second execution timeout
• Single run per URL per provider

Provider configurations

Bright Data used its Dataset API with a dedicated Google Maps Reviews dataset, returning structured JSON with 26 fields per review. The API was polled via the /progress/{snapshot_id} endpoint at 1-second intervals until ready.

Oxylabs used a dedicated Google source API (source: google), but the configuration returned empty results across all URLs on this domain.

Zyte used its Extract API with browserHtml enabled, rendering pages through a headless browser and returning HTML parsed with CSS selectors.

Nimble used its Web API with render: true for JavaScript rendering, returning rendered HTML parsed with CSS selectors.

Decodo used its web unblocker proxy with the X-SU-Headless header for JavaScript rendering.

FAQs about Google Maps reviews scraping

AI Researcher

Nazlı Şipi

AI Researcher

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Nazlı is a data analyst at AIMultiple. She has prior experience in data analysis across various industries, where she worked on transforming complex datasets into actionable insights.

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