# Booking.com Reviews Scraper (`automation-lab/booking-reviews-scraper`) Actor Extract guest reviews from any Booking.com hotel page. Get review scores, positive/negative comments, reviewer details, stay dates, and room types. Perfect for hospitality analysis and competitor monitoring. - **URL**: https://apify.com/automation-lab/booking-reviews-scraper.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** Travel - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Booking.com Reviews Scraper Scrape guest reviews from any hotel on [Booking.com](https://www.booking.com). Extract reviewer names, countries, scores, positive and negative comments, stay dates, room types, traveller types, and more. Supports multiple hotels, pagination, language filtering, and custom sorting. ### Features - **Multiple hotels** in a single run -- provide a list of Booking.com hotel URLs - **Pagination** -- automatically scrapes all reviews up to your specified limit - **Language filtering** -- filter reviews by language (English, German, French, Spanish, etc.) - **Sort options** -- sort reviews by relevance, newest/oldest first, or highest/lowest scores - **Rich data** -- extracts 13+ fields per review including positive/negative text, room type, nights stayed - **Pay per result** -- only pay for the reviews you actually scrape - **Export** -- download results in JSON, CSV, Excel, or connect via API ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `hotelUrls` | Array of strings | (required) | Booking.com hotel URLs to scrape reviews from | | `maxReviews` | Integer | 50 | Maximum reviews per hotel (0 = unlimited) | | `language` | String | `all` | Filter reviews by language code (`en`, `de`, `fr`, `es`, `it`, `pt`, `ja`, `zh`, etc.) | | `sortBy` | String | `most_relevant` | Sort order: `most_relevant`, `newest_first`, `oldest_first`, `highest_scores`, `lowest_scores` | #### How to get hotel URLs 1. Go to [Booking.com](https://www.booking.com) 2. Search for a hotel or city 3. Click on a hotel to open its page 4. Copy the URL from your browser The URL should look like: `https://www.booking.com/hotel/gb/the-savoy.html` #### Example input ```json { "hotelUrls": [ "https://www.booking.com/hotel/gb/the-savoy.html", "https://www.booking.com/hotel/us/the-plaza.html" ], "maxReviews": 50, "language": "en", "sortBy": "newest_first" } ```` ### Output Each review is output as a JSON object with the following fields: | Field | Type | Description | |-------|------|-------------| | `hotelName` | String | Name of the hotel | | `hotelUrl` | String | Original Booking.com hotel URL | | `reviewerName` | String | Name of the reviewer | | `reviewerCountry` | String | Country of the reviewer | | `reviewDate` | String | When the review was posted (e.g., "March 22, 2026") | | `score` | Number | Review score from 0 to 10 | | `title` | String | Review title/headline | | `positive` | String | What the guest liked | | `negative` | String | What the guest disliked | | `stayDate` | String | Month and year of the stay (e.g., "March 2026") | | `nightsStayed` | Integer | Number of nights stayed | | `roomType` | String | Type of room booked | | `travellerType` | String | Solo traveller, Couple, Family, Group, etc. | | `scrapedAt` | String | ISO timestamp when the review was scraped | #### Example output ```json { "hotelName": "The Savoy", "hotelUrl": "https://www.booking.com/hotel/gb/the-savoy.html", "reviewerName": "Cohen", "reviewerCountry": "United States", "reviewDate": "November 12, 2024", "score": 10, "title": "Exceeded expectations and loved our stay!", "positive": "Location. Gorgeous property. Wonderful staff", "negative": "", "stayDate": "November 2024", "nightsStayed": 4, "roomType": "Superior Queen Room", "travellerType": "Group", "scrapedAt": "2026-03-27T04:09:54.188Z" } ``` ### How much does it cost? The scraper uses a pay-per-result pricing model: | Event | Price | |-------|-------| | Run started | $0.01 (one-time per run) | | Review scraped | $0.003 per review | **Example costs:** - 50 reviews from 1 hotel: $0.01 + (50 x $0.003) = **$0.16** - 100 reviews from 2 hotels: $0.01 + (100 x $0.003) = **$0.31** - 500 reviews from 5 hotels: $0.01 + (500 x $0.003) = **$1.51** Platform compute costs are minimal (typically under $0.01 per run) since the scraper uses lightweight HTTP requests to fetch review pages. ### Use cases #### Hotel market research Compare guest satisfaction across competing hotels in the same area. Analyze what guests like and dislike about each property to identify competitive advantages. #### Sentiment analysis Feed review data into NLP tools to analyze guest sentiment trends over time. Track how renovations, management changes, or seasonal factors affect reviews. #### Travel planning Collect reviews for hotels you're considering to make informed booking decisions. Filter by language to find reviews from travellers who share your background. #### Hospitality benchmarking Monitor review scores and common complaints across your hotel portfolio. Identify properties that need attention and track improvement over time. #### Content creation Gather authentic guest feedback for travel blogs, hotel comparison sites, or recommendation engines. ### Supported URL formats The scraper accepts standard Booking.com hotel URLs: ``` https://www.booking.com/hotel/gb/the-savoy.html https://www.booking.com/hotel/us/the-plaza.html https://www.booking.com/hotel/fr/hotel-le-bristol-paris.html https://www.booking.com/hotel/it/hassler-roma.html?aid=12345&label=test https://www.booking.com/hotel/fr/hotel-le-bristol-paris.en-gb.html ``` The scraper extracts the country code and hotel identifier from the URL path. Query parameters and language suffixes are handled automatically. ### Language codes Common language filter values: | Code | Language | |------|----------| | `all` | All languages (default) | | `en` | English | | `de` | German | | `fr` | French | | `es` | Spanish | | `it` | Italian | | `pt` | Portuguese | | `ja` | Japanese | | `zh` | Chinese | | `ko` | Korean | | `ru` | Russian | | `ar` | Arabic | | `nl` | Dutch | | `pl` | Polish | | `sv` | Swedish | ### Tips - **Start small**: Test with `maxReviews: 10` to verify the data format meets your needs before running larger scrapes. - **Use language filter**: If you only need English reviews, set `language: "en"` to skip reviews in other languages and reduce run time. - **Sort by newest**: Use `sortBy: "newest_first"` to get the most recent reviews first. Useful for monitoring. - **Multiple hotels**: You can scrape reviews from multiple hotels in a single run. The scraper processes them sequentially. - **URL format**: Make sure your URLs follow the pattern `https://www.booking.com/hotel/{country_code}/{hotel-slug}.html`. ### Integrations Connect Booking.com Reviews Scraper with your existing tools: - **Google Sheets** -- automatically export reviews to a spreadsheet - **Slack** -- get notified when new reviews are scraped - **Zapier / Make** -- build automated workflows with review data - **API** -- access results programmatically via the Apify API - **Webhooks** -- trigger actions when a scraping run completes ### Limitations - The scraper extracts reviews from the public Booking.com review pages. Private or removed reviews are not accessible. - Review dates show month and year of the stay, not the exact check-in/check-out dates. - The hotel name is derived from the URL slug. In rare cases, it may differ slightly from the official hotel name on Booking.com. - Very high-volume scraping (thousands of reviews per hotel) may encounter rate limiting. The scraper includes polite delays between page requests. ### FAQ **Q: Can I scrape reviews for any hotel on Booking.com?** A: Yes, as long as you have the hotel's Booking.com URL, you can scrape its public reviews. **Q: How many reviews can I scrape?** A: There is no hard limit. Set `maxReviews` to 0 for unlimited. The scraper will paginate through all available reviews. **Q: Can I filter reviews by score?** A: Use the `sortBy` option with `highest_scores` or `lowest_scores` to prioritize reviews by score. Combined with `maxReviews`, this effectively filters by score range. **Q: How fresh is the data?** A: Reviews are scraped in real-time from Booking.com. The `scrapedAt` timestamp shows exactly when each review was collected. **Q: Can I run this on a schedule?** A: Yes! Use Apify's scheduling feature to run the scraper daily, weekly, or at any interval to monitor new reviews. **Q: What happens if a hotel URL is invalid?** A: The scraper logs a warning and skips invalid URLs. It continues processing the remaining valid URLs in your list. **Q: Do I need a Booking.com account?** A: No. The scraper extracts publicly available review data. No login or account is required. **Q: Can I combine this with other Apify actors?** A: Absolutely. Use the Booking.com Scraper to find hotel URLs, then feed them into this Reviews Scraper for detailed review data. Chain actors together using Apify's API or integration tools. # Actor input Schema ## `hotelUrls` (type: `array`): List of Booking.com hotel URLs to scrape reviews from. Example: https://www.booking.com/hotel/gb/the-savoy.html ## `maxReviews` (type: `integer`): Maximum number of reviews to scrape per hotel. Set to 0 for unlimited. ## `language` (type: `string`): Filter reviews by language. Use ISO language codes: en (English), de (German), fr (French), es (Spanish), it (Italian), pt (Portuguese), ja (Japanese), zh (Chinese), etc. Leave empty or set to 'all' for all languages. ## `sortBy` (type: `string`): How to sort reviews. ## Actor input object example ```json { "hotelUrls": [ "https://www.booking.com/hotel/gb/the-savoy.html" ], "maxReviews": 20, "language": "all", "sortBy": "most_relevant" } ``` # Actor output Schema ## `reviews` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "hotelUrls": [ "https://www.booking.com/hotel/gb/the-savoy.html" ], "maxReviews": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/booking-reviews-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "hotelUrls": ["https://www.booking.com/hotel/gb/the-savoy.html"], "maxReviews": 20, } # Run the Actor and wait for it to finish run = client.actor("automation-lab/booking-reviews-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "hotelUrls": [ "https://www.booking.com/hotel/gb/the-savoy.html" ], "maxReviews": 20 }' | apify call automation-lab/booking-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/booking-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Booking.com Reviews Scraper", "description": "Extract guest reviews from any Booking.com hotel page. Get review scores, positive/negative comments, reviewer details, stay dates, and room types. Perfect for hospitality analysis and competitor monitoring.", "version": "0.1", "x-build-id": "scUA7FUEPHVlAKl3q" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~booking-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-booking-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automation-lab~booking-reviews-scraper/runs": { "post": { "operationId": "runs-sync-automation-lab-booking-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automation-lab~booking-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-automation-lab-booking-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "hotelUrls" ], "properties": { "hotelUrls": { "title": "Hotel URLs", "type": "array", "description": "List of Booking.com hotel URLs to scrape reviews from. Example: https://www.booking.com/hotel/gb/the-savoy.html", "items": { "type": "string" } }, "maxReviews": { "title": "Max reviews per hotel", "minimum": 0, "type": "integer", "description": "Maximum number of reviews to scrape per hotel. Set to 0 for unlimited.", "default": 50 }, "language": { "title": "Review language filter", "type": "string", "description": "Filter reviews by language. Use ISO language codes: en (English), de (German), fr (French), es (Spanish), it (Italian), pt (Portuguese), ja (Japanese), zh (Chinese), etc. Leave empty or set to 'all' for all languages.", "default": "all" }, "sortBy": { "title": "Sort reviews by", "enum": [ "most_relevant", "newest_first", "oldest_first", "highest_scores", "lowest_scores" ], "type": "string", "description": "How to sort reviews.", "default": "most_relevant" } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```