Google Maps Reviews Scraper This Actor scrapes reviews from Google Maps locations. It allows you to extract detailed review data including reviewer information, ratings, review text, and more. ## Features - Scrapes reviews from Google Maps location pages - Extracts reviewer name, rating, review text, date, and other metadata - Handles consent screens and expands "See more" buttons - Scrolls to load more reviews - Deduplicates reviews to avoid duplicates - Configurable maximum number of reviews to scrape per URL ## Use cases - Market Research: Analyze customer feedback and reviews to understand customer sentiment, identify trends, and make data-driven decisions. - Competitor Analysis: Scrape reviews from competitor locations to benchmark performance and identify areas for improvement. - Content Planning: Gather customer reviews to inform content strategy, product development, and marketing initiatives. ## Input The Actor accepts the following input parameters: - startUrls (required): An array of Google Maps URLs to scrape reviews from - maxReviewsPerUrl (optional): Maximum number of reviews to scrape per URL (default: 50) Example input: json { "startUrls": [ { "url": "https://www.google.com/maps/place/Noma/@55.6828273,12.6079059,16z/data=!3m1!4b1!4m6!3m5!1s0x4652533b679080a5:0x42eaecc5eb37e114!8m2!3d55.6828273!4d12.6104808!16s%2Fm%2F02qsmm3!5m1!1e4?entry=ttu&g_ep=EgoyMDI0MTAyMC4xIKXMDSoASAFQAw%3D%3D" }, { "url": "https://www.google.com/maps/place/Disfrutar/@41.3877627,2.1506241,17z/data=!3m1!4b1!4m6!3m5!1s0x12a4a285bbc62c4d:0xcd8a70d67beb3993!8m2!3d41.3877627!4d2.153199!16s%2Fg%2F11b6p9j0sw!5m1!1e4?entry=ttu&g_ep=EgoyMDI0MTAyMC4xIKXMDSoASAFQAw%3D%3D" } ], "maxReviewsPerUrl": 100 } ## Output The Actor outputs a dataset with the following fields: - url: The URL of the Google Maps location - locationName: The name of the location - reviewId: The ID of the review - reviewerName: The name of the reviewer - isLocalGuide: Whether the reviewer is a local guide - reviewsAmount: The total number of reviews by this reviewer - photosAmount: The total number of photos by this reviewer - reviewerLink: The link to the reviewer's Google Maps profile - rating: The rating of the review - date: The date of the review - text: The text of the review - photos: An array of photo URLs used in the review Example output: json { "url": "https://www.google.com/maps/place/Noma/@55.6828273,12.6079059,16z/data=!3m1!4b1!4m6!3m5!1s0x4652533b679080a5:0x42eaecc5eb37e114!8m2!3d55.6828273!4d12.6104808!16s%2Fm%2F02qsmm3!5m1!1e4?entry=ttu&g_ep=EgoyMDI0MTAyMC4xIKXMDSoASAFQAw%3D%3D", "locationName": "Noma", "reviewId": "ChZDSUhNMG9nS0VJQ0FnSURydU5tU1JREAE", "reviewerName": "Bel", "isLocalGuide": true, "reviewsAmount": 425, "photosAmount": 812, "reviewerLink": "https://www.google.com/maps/contrib/115565173774207530812", "rating": 4, "date": "3 months ago", "text": "Finally we got to try the famous Noma. It's the vegetable season and some say it is when you get the most creative dishes. We were indeed marvelled by all the plates beautifully presented to us. Taste was mostly great. The bamboo dish was a bit surprising to me. Staff told us to eat it like a panda. For drinks, we are not heavy wine drinkers. So, as the staff also recommended, one of us had wine, and the other had juice. We just shared the drinks with each other. We also liked the casual and friendly atmosphere. Most customers did not dress up to dine here. Overall, despite all the positives, I felt that I had to give 4 stars because it is just too expensive. I cannot help thinking that the cost of a meal here can feed a family elsewhere for a month (or more).", "photos": [ "https://lh5.googleusercontent.com/p/AF1QipO-6TflfLgtGsMQX9VPvDpK3tU_JSDR5KxyDFUz=w450-h338-p-k-no", "https://lh5.googleusercontent.com/p/AF1QipPoVaPypk_rWYRBuuKr0l7Jnz2xtuEdaK_C-sV5=w450-h338-p-k-no", "https://lh5.googleusercontent.com/p/AF1QipPSQef4csntQqxxFwszeLu_nKOhUzfD3BWopqPJ=w450-h338-p-k-no", "https://lh5.googleusercontent.com/p/AF1QipNdJ02uN2XkeAwQpsfqBNYrhcRZlY9zBlZOc7dU=w450-h338-p-k-no" ] } ## Usage To use this Actor, follow these steps: 1. Set up your input: Prepare a JSON object with the startUrls array containing the Google Maps location URLs you want to scrape reviews from, and optionally set the maxReviewsPerUrl value. 2. Run the Actor: You can run the Actor through the Apify Console, API, or using the Apify CLI. 3. Retrieve the results: Once the Actor has finished running, you can access the scraped review data in the "Dataset" tab of your Actor run, or via the Apify API.