Google Maps Reviews Scraper Extract detailed reviews from any Google Maps business page. This scraper retrieves reviewer information, ratings, review text, dates, likes, and owner responses. ## Features - 📝 Complete Review Data: Extract reviewer names, ratings, full review text, and posting dates - 👤 Reviewer Information: Get reviewer profile URLs and avatar images - 👍 Engagement Metrics: Collect like counts for each review - 💬 Owner Responses: Capture business owner replies and response dates - 🔄 Automatic Scrolling: Automatically loads more reviews by scrolling - 📊 Business Overview: Includes business name, overall rating, and total review count - 🎯 Customizable: Specify exactly how many reviews you want to extract ## Input The scraper requires the following input parameters: | Field | Type | Required | Description | | ------------ | ------- | -------- | ------------------------------------------------------------ | | placeUrl | String | Yes | Full URL of the Google Maps business/place page | | maxReviews | Integer | No | Maximum number of reviews to extract (default: 50, max: 500) | ### Example Input json { "placeUrl": "https://www.google.com/maps/place/Eataly+NYC+Flatiron/@40.742045,-73.9900845,17z/...", "maxReviews": 100 } ### How to Get the Place URL 1. Go to Google Maps 2. Search for the business you want to scrape reviews from 3. Click on the business to open its details page 4. Copy the complete URL from your browser's address bar ## Output The scraper returns a single JSON object containing: ### Business Information - place_url: URL of the Google Maps place - scraped_at: ISO timestamp of when data was collected - business_name: Name of the business - rating: Average rating (e.g., 4.5) - total_reviews: Total number of reviews on Google Maps - category: Business category (e.g., "Italian restaurant") - address: Business address ### Reviews Array Each review in the reviews array contains: - review_id: Unique identifier for the review - reviewer_name: Name of the reviewer - reviewer_profile_url: Google Maps profile URL - reviewer_avatar: Avatar image URL - rating: Star rating (1-5) - review_text: Full review content - review_date: When the review was posted - likes: Number of helpful votes - owner_response: Business owner's response (if any) - owner_response_date: When owner responded ### Example Output json { "place_url": "https://www.google.com/maps/place/...", "scraped_at": "2025-10-23T10:30:00", "business_name": "Eataly NYC Flatiron", "rating": 4.4, "total_reviews": 9729, "category": "Italian restaurant", "address": "200 5th Ave, New York, NY 10010, United States", "reviews": [ { "review_id": "ChZDSUhNMG9nS0VJQ0FnSUNOeF...", "reviewer_name": "John Doe", "reviewer_profile_url": "https://www.google.com/maps/contrib/...", "reviewer_avatar": "https://lh3.googleusercontent.com/...", "rating": 5, "review_text": "Amazing Italian food and great atmosphere! The pasta is authentic and delicious.", "review_date": "2 weeks ago", "likes": 12, "owner_response": "Thank you for your wonderful review!", "owner_response_date": "1 week ago" } ] } ## Use Cases - 📊 Sentiment Analysis: Analyze customer sentiment and feedback trends - 🔍 Competitive Research: Compare reviews across competing businesses - 📈 Business Intelligence: Track reputation and customer satisfaction over time - 🤖 Review Monitoring: Automated monitoring of new reviews - 💼 Market Research: Understand customer preferences and pain points - 📱 App Development: Build review aggregation or comparison tools ## Performance - Average scraping time: 30-60 seconds for 50 reviews - Handles dynamic content loading through automatic scrolling - Reliable extraction with multiple fallback selectors ## Notes - The scraper automatically expands truncated reviews by clicking "More" buttons - Review dates are in relative format (e.g., "2 weeks ago") as shown on Google Maps - Not all reviews may have owner responses - this field will be null if absent - The scraper respects Google Maps' rate limits and includes appropriate delays ## Requirements - Python 3.12+ - Apify SDK 3.0.1+ - Playwright (Chromium) ## Local Development 1. Install dependencies: bash pip install -r requirements.txt 2. Install Playwright browsers: bash playwright install chromium 3. Create .actor/INPUT.json with your test parameters 4. Run the scraper: bash python -m src ## Deployment This scraper is ready to be deployed on the Apify platform: bash apify push ## Support For issues or questions: - Check the Apify Documentation - Review the input schema for parameter details - Ensure the place URL is complete and valid ## Version Current version: 1.0.0