# Booking.com Reviews Scraper (`huggable_quote/booking-reviews-scraper`) Actor Scrape guest reviews from Booking.com hotel pages using GraphQL API. Supports multi-language filtering, score filtering, and extracts up to 1000 reviews per hotel. - **URL**: https://apify.com/huggable\_quote/booking-reviews-scraper.md - **Developed by:** [OrbitData Labs](https://apify.com/huggable_quote) (community) - **Categories:** Travel, Other - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 1,000 review extracteds This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 Extract guest reviews from Booking.com hotel pages at scale. This Apify Actor uses Booking.com's internal GraphQL API to retrieve structured review data — including reviewer info, scores, positive/negative text, room type, and stay details — without browser rendering. It supports multi-language filtering, score-based filtering, and can extract up to 1,000 reviews per hotel. ### Why Use It - **GraphQL-based extraction**: Fetches reviews via Booking.com's internal API instead of parsing HTML, returning structured JSON with 25 reviews per request. Falls back to HTML parsing automatically if the API structure changes. - **Multi-language support**: Filter reviews by 12 languages (English, Japanese, Korean, Chinese, Spanish, French, German, Italian, Portuguese, Russian) or retrieve all languages at once. - **Score filtering**: Extract only reviews within a specific score range (0–10 scale), useful for sentiment analysis or quality monitoring. - **Anti-bot handling**: Uses Apify Residential Proxies by default, rotates User-Agent headers, and applies random delays between requests. Includes exponential backoff on rate-limited responses. ### How To Use #### 1. Create a new task Go to the [Booking.com Reviews Scraper](https://apify.com/huggable_quote/booking-reviews-scraper) page on Apify and click **Try for free**. #### 2. Configure input Add one or more Booking.com hotel URLs. Each URL should point to a hotel detail page: ```` https://www.booking.com/hotel/jp/the-okura-tokyo.html https://www.booking.com/hotel/us/paramount-new-york.html ```` #### 3. Set options Choose the maximum number of reviews per hotel, language filter, sort order, and score range. #### 4. Run and download Click **Start** and wait for the run to complete. Download results as JSON, CSV, or Excel from the Dataset tab. ### Input Configuration | Field | Type | Default | Description | |-------|------|---------|-------------| | `startUrls` | array | *(required)* | List of Booking.com hotel page URLs. Min 1, max 100. | | `maxReviewsPerHotel` | integer | `100` | Maximum reviews to extract per hotel (1–1,000). | | `language` | string | `"all"` | Filter by review language. Options: `all`, `en`, `ja`, `ko`, `zh-cn`, `zh-tw`, `es`, `fr`, `de`, `it`, `pt`, `ru`. | | `sortBy` | string | `"newest"` | Sort order. Options: `newest`, `oldest`, `highest_score`, `lowest_score`, `most_relevant`. | | `minReviewScore` | number | `0` | Minimum review score (0–10). | | `maxReviewScore` | number | `10` | Maximum review score (0–10). | | `includeReviewerInfo` | boolean | `true` | Include reviewer name, country, room type, and traveler type. Set to `false` to exclude personal data. | | `proxyConfiguration` | object | Residential | Proxy settings. Residential proxies are recommended — Booking.com blocks most datacenter IPs. | #### Example Input ```json { "startUrls": [ { "url": "https://www.booking.com/hotel/jp/the-okura-tokyo.html" }, { "url": "https://www.booking.com/hotel/us/paramount-new-york.html" } ], "maxReviewsPerHotel": 200, "language": "en", "sortBy": "newest", "minReviewScore": 7, "maxReviewScore": 10, "includeReviewerInfo": true, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"] } } ```` ### Output Format Each review is stored as a separate record in the dataset: ```json { "hotelUrl": "https://www.booking.com/hotel/jp/the-okura-tokyo.html", "hotelName": "The Okura Tokyo", "hotelLocation": "Tokyo, Japan", "reviewId": "abc123def456", "reviewerName": "John D.", "reviewerCountry": "United States", "reviewerCountryCode": "us", "reviewDate": "2026-03-15", "stayDate": "2026-02", "roomType": "Deluxe Twin Room", "lengthOfStay": 3, "travelerType": "Couple", "reviewScore": 9.0, "reviewTitle": "Excellent stay", "positiveText": "Great location and service", "negativeText": "Wifi was a bit slow", "language": "en", "isVerifiedStay": true, "scrapedAt": "2026-04-16T10:00:00Z" } ``` #### Output Fields | Field | Type | Description | |-------|------|-------------| | `hotelUrl` | string | Original hotel page URL | | `hotelName` | string | Hotel name as displayed on Booking.com | | `hotelLocation` | string | Hotel city and country | | `reviewId` | string | Booking.com internal review identifier | | `reviewerName` | string | Reviewer display name (empty if `includeReviewerInfo` is false) | | `reviewerCountry` | string | Reviewer's country name | | `reviewerCountryCode` | string | ISO 3166-1 alpha-2 country code (lowercase) | | `reviewDate` | string | Review submission date (YYYY-MM-DD) | | `stayDate` | string | Month of stay (YYYY-MM) | | `roomType` | string | Room type the reviewer stayed in | | `lengthOfStay` | integer | Number of nights | | `travelerType` | string | Traveler category (e.g., Couple, Family, Solo traveler) | | `reviewScore` | number | Review score on a 0–10 scale | | `reviewTitle` | string | Review headline | | `positiveText` | string | Positive review comments | | `negativeText` | string | Negative review comments | | `language` | string | Review language code | | `isVerifiedStay` | boolean | Whether the reviewer's stay was verified by Booking.com | | `scrapedAt` | string | Timestamp when the review was extracted (ISO 8601 UTC) | ### Use Cases - **Hotel operators**: Monitor guest feedback across properties, identify recurring complaints, and track satisfaction trends over time. - **Travel metasearch platforms**: Aggregate review data from Booking.com alongside other OTAs for comparison features. - **Sentiment analysis**: Feed review text into NLP pipelines to extract sentiment scores, topic clusters, or staff performance insights. - **Market research**: Analyze competitor hotels' guest satisfaction, pricing perception, and seasonal review patterns. - **Academic research**: Study traveler behavior, cross-cultural review differences, or hospitality service quality at scale. ### Pricing This Actor uses the **pay-per-event** pricing model. You are only charged for the reviews actually extracted. | Event | Price per unit | Example | |-------|---------------|---------| | `review-extracted` | $0.0002 | 1,000 reviews = $0.20 | You can set a **maximum spend per run** in the Apify Console to control costs. The Actor automatically stops extracting when your spending limit is reached and returns all reviews collected up to that point. Residential proxy usage is billed separately by Apify based on data transfer. Typical usage: ~0.5 MB per 100 reviews. ### Limitations & FAQ **Q: How many reviews can I extract per hotel?** A: Up to 1,000 per run. Booking.com may have fewer reviews available for some properties. **Q: Why do I need residential proxies?** A: Booking.com blocks most datacenter IP ranges. Residential proxies route requests through consumer IP addresses, which are not blocked. Without residential proxies, requests will likely return CAPTCHA pages or 403 errors. **Q: Can I scrape reviews without a Booking.com account?** A: Yes. This Actor does not require any Booking.com credentials. Reviews are publicly accessible. **Q: How often does the GraphQL API structure change?** A: Booking.com updates their frontend periodically. This Actor includes automatic fallback to HTML parsing when the GraphQL structure changes, so it continues working across most updates. If both methods fail, an update to the Actor will be released. **Q: Are there rate limits?** A: The Actor includes built-in delays (1–3 seconds between requests) and exponential backoff on 429 responses. Up to 3 hotels are processed concurrently by default. **Q: What happens if a hotel URL is invalid?** A: Invalid URLs are skipped with a warning log. Other hotels in the same run continue processing normally. ### Author & Contact **Author**: [huggable\_quote](https://apify.com/huggable_quote) **License**: Apache-2.0 For bug reports or feature requests, open an issue on the [GitHub repository](https://github.com/huggable_quote/booking-reviews-scraper) or contact via Apify. # Actor input Schema ## `startUrls` (type: `array`): List of Booking.com hotel page URLs to scrape reviews from. Each URL should point to a hotel detail page (e.g., https://www.booking.com/hotel/jp/the-okura-tokyo.html). ## `maxReviewsPerHotel` (type: `integer`): Maximum number of reviews to extract per hotel. The actor stops fetching once this limit is reached. ## `language` (type: `string`): Filter reviews by language. Select 'all' to get reviews in all languages. ## `sortBy` (type: `string`): How to sort the reviews before extraction. ## `minReviewScore` (type: `number`): Only extract reviews with a score equal to or above this value (0-10 scale). ## `maxReviewScore` (type: `number`): Only extract reviews with a score equal to or below this value (0-10 scale). ## `includeReviewerInfo` (type: `boolean`): When enabled, includes reviewer name, country, room type, and traveler type in the output. ## `proxyConfiguration` (type: `object`): Proxy settings for the actor. Residential proxies are strongly recommended because Booking.com blocks most datacenter IPs. ## Actor input object example ```json { "maxReviewsPerHotel": 100, "language": "all", "sortBy": "newest", "minReviewScore": 0, "maxReviewScore": 10, "includeReviewerInfo": true, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("huggable_quote/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 = {} # Run the Actor and wait for it to finish run = client.actor("huggable_quote/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 '{}' | apify call huggable_quote/booking-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=huggable_quote/booking-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Booking.com Reviews Scraper", "description": "Scrape guest reviews from Booking.com hotel pages using GraphQL API. Supports multi-language filtering, score filtering, and extracts up to 1000 reviews per hotel.", "version": "0.1", "x-build-id": "8ODHLXx5k7HItbBoK" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/huggable_quote~booking-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-huggable_quote-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/huggable_quote~booking-reviews-scraper/runs": { "post": { "operationId": "runs-sync-huggable_quote-booking-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/huggable_quote~booking-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-huggable_quote-booking-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "startUrls" ], "properties": { "startUrls": { "title": "Hotel URLs", "minItems": 1, "maxItems": 100, "type": "array", "description": "List of Booking.com hotel page URLs to scrape reviews from. Each URL should point to a hotel detail page (e.g., https://www.booking.com/hotel/jp/the-okura-tokyo.html).", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL", "description": "Booking.com hotel detail page URL (e.g., https://www.booking.com/hotel/jp/the-okura-tokyo.html)" } } } }, "maxReviewsPerHotel": { "title": "Max Reviews Per Hotel", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of reviews to extract per hotel. The actor stops fetching once this limit is reached.", "default": 100 }, "language": { "title": "Review Language", "enum": [ "all", "en", "ja", "ko", "zh-cn", "zh-tw", "es", "fr", "de", "it", "pt", "ru" ], "type": "string", "description": "Filter reviews by language. Select 'all' to get reviews in all languages.", "default": "all" }, "sortBy": { "title": "Sort Reviews By", "enum": [ "newest", "oldest", "highest_score", "lowest_score", "most_relevant" ], "type": "string", "description": "How to sort the reviews before extraction.", "default": "newest" }, "minReviewScore": { "title": "Minimum Review Score", "minimum": 0, "maximum": 10, "type": "number", "description": "Only extract reviews with a score equal to or above this value (0-10 scale).", "default": 0 }, "maxReviewScore": { "title": "Maximum Review Score", "minimum": 0, "maximum": 10, "type": "number", "description": "Only extract reviews with a score equal to or below this value (0-10 scale).", "default": 10 }, "includeReviewerInfo": { "title": "Include Reviewer Info", "type": "boolean", "description": "When enabled, includes reviewer name, country, room type, and traveler type in the output.", "default": true }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for the actor. Residential proxies are strongly recommended because Booking.com blocks most datacenter IPs.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } } }, "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 } } } } } } } } } } ```