FAST Booking.com Scraper

Extract hotel reviews, ratings, and data from any Booking.com property at scale — starting at just $0.90 per 1,000 results. This fast Booking.com scraper handles pagination, proxies, and anti-bot protection so you can focus on analysis, not infrastructure.

Use Cases

• Hotel Sentiment Analysis — Aggregate thousands of guest reviews to identify sentiment trends, common complaints, and praised amenities across properties.
• Competitor Benchmarking — Compare ratings, review volume, and guest feedback across competing hotels in the same market or chain.
• Bulk Review Extraction — Pull complete review histories for academic research, investment due diligence, or hospitality consulting.
• Market Research — Map guest satisfaction patterns across destinations, hotel tiers, and seasons to inform pricing and positioning.
• Review Monitoring — Track new reviews over time to detect quality shifts, reputation crises, or service improvements.
• Revenue Intelligence — Correlate review trends with pricing and occupancy signals to build demand forecasting models.

How It Works

1. Input a Booking.com hotel URL — Point the scraper to any property page.
2. Configure depth and concurrency — Set maxPages to control how many review pages to crawl and concurrency for parallel requests.
3. Run the Actor — The scraper navigates review pages, extracts structured data (reviewer name, date, score, title, body, stay type), handles pagination, and respects rate limits.
4. Get your dataset — Results are returned as clean JSON rows in an Apify dataset, ready for download, API access, or pipeline integration.

Input

Field	Type	Default	Description
startUrl	string	required	Single Booking.com hotel URL (e.g. https://www.booking.com/hotel/us/example.html)
maxPages	integer	10	Maximum number of review pages to scrape per run
concurrency	integer	5	Number of parallel browser tabs for faster extraction
useSystemChrome	boolean	false	Use the system-installed Chrome instead of bundled Chromium
headless	boolean	false	Run browser in headless mode (no visible window)
proxy	object	—	Proxy configuration for IP rotation and geo-targeting

Output

Each row in the dataset contains:

Field	Description
hotelName	Name of the property
hotelUrl	Canonical Booking.com URL
reviewerName	Guest name (or pseudonym)
reviewDate	Date of the review
rating	Numerical score (e.g. 8.5)
reviewTitle	Headline of the review
reviewBody	Full review text
stayType	Room type or travel purpose if available
scrapedAt	Timestamp of extraction

Example

Input

{
  "startUrl": "https://www.booking.com/hotel/us/example-property.html",
  "maxPages": 5,
  "concurrency": 3,
  "headless": true
}

Output (first 2 rows)

[
  {
    "hotelName": "Example Grand Hotel",
    "hotelUrl": "https://www.booking.com/hotel/us/example-property.html",
    "reviewerName": "Sarah M.",
    "reviewDate": "2026-07-15",
    "rating": 9.2,
    "reviewTitle": "Exceptional stay, will return",
    "reviewBody": "Everything from check-in to checkout was seamless. The staff remembered our names...",
    "stayType": "Couple trip",
    "scrapedAt": "2026-08-30T14:22:01Z"
  },
  {
    "hotelName": "Example Grand Hotel",
    "hotelUrl": "https://www.booking.com/hotel/us/example-property.html",
    "reviewerName": "James K.",
    "reviewDate": "2026-07-10",
    "rating": 7.8,
    "reviewTitle": "Good but room for improvement",
    "reviewBody": "Location is unbeatable. Breakfast was crowded and the gym equipment needs updating...",
    "stayType": "Business trip",
    "scrapedAt": "2026-08-30T14:22:01Z"
  }
]

Integrations

• Google Sheets / Excel — Export dataset via API or download as CSV for spreadsheet analysis.
• Snowflake / BigQuery — Push dataset rows into your data warehouse for SQL-based analytics.
• Zapier / Make — Trigger workflows on new dataset items (e.g. alert when average rating drops).
• Python / Node.js — Use the Apify Client to pull results directly into your scripts.
• Slack / Email — Set up notifications for run completion or anomaly detection.
• LLM Pipelines — Feed review text into GPT/Claude for theme extraction, summarization, or classification.

Related Actors

• Booking.com Review Scraper — Dedicated review-focused extractor with sentiment tagging.
• Booking.com Hotel Details Scraper — Extract pricing, amenities, and property metadata.
• Booking.com Search Scraper — Crawl search results to discover hotels by destination and dates.

FAQ

How many reviews can I scrape per run? Depends on maxPages. Each page typically contains 10-25 reviews. With maxPages: 10, expect 100-250 reviews per hotel.

Does this work with JavaScript-rendered content? Yes. The Actor uses a real browser engine, so all dynamically loaded reviews and metadata are captured.

Can I scrape multiple hotels in one run? This Actor is optimized for single-URL input. For multi-hotel crawling, run multiple instances in parallel or use a scheduling orchestration layer.

Is a proxy required? No, but recommended for high-volume or repeated scraping. Configure via the proxy input field.

What Booking.com domains are supported? All Booking.com country domains (.com, .co.uk, .de, .fr, etc.) are supported.

Can I use this for pricing data? This Actor focuses on reviews. For pricing and availability, see our Booking.com hotel details scraper.

SEO Keywords

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For AI Agents

This Actor is designed for programmatic use by AI agents and automated pipelines. Key considerations:

• Deterministic input — Pass startUrl as a fully qualified Booking.com property URL. Avoid ambiguous or malformed URLs.
• Structured output — Dataset rows follow a consistent schema, making them easy to parse and route.
• Pipeline-friendly — Use waitSecs: 0 for fire-and-forget runs, then poll via get-actor-run and fetch results with get-dataset-items.
• Cost control — Set maxPages explicitly to cap extraction volume and cost per run.
• Retry logic — If a run fails (timeout, blocked), reduce concurrency or enable proxy rotation before retrying.

Legal Disclaimer

This Actor extracts publicly available review data from Booking.com. It does not bypass authentication, access private user accounts, or circumvent access controls. Users are responsible for ensuring their use complies with Booking.com's Terms of Service and applicable data protection regulations (GDPR, CCPA, etc.). Scraped data should not be republished in ways that violate platform policies or intellectual property rights.