Booking.com Hotel Scraper

Extract hotel prices, ratings, reviews, and availability data from Booking.com with an automated web scraper. Export structured hotel data in seconds for price monitoring, market research, and travel automation.

What is Booking.com?

Booking.com is the world's largest online accommodation booking platform, offering over 28 million listings across 228 countries and territories. The platform processes millions of room-night reservations daily, making it the primary source for hotel pricing, availability, and guest review data worldwide. Travel agencies, price comparison platforms, and market researchers rely on Booking.com data to understand hospitality market dynamics, competitive pricing strategies, and traveler sentiment across destinations.

Manually monitoring hotel prices, review scores, and availability across multiple properties and dates is time-consuming and error-prone. This Booking.com Hotel Scraper automates the data extraction process, simulating real user searches to bypass anti-bot protections while collecting comprehensive hotel information. Whether you're tracking seasonal pricing trends, building a hotel recommendation engine, or conducting competitive market analysis, automated scraping provides accurate, real-time data at scale.

The scraper fills Booking.com's search form interactively, navigates calendar interfaces to select check-in and check-out dates, and extracts structured data from property cards across multiple result pages. All extracted data is returned in clean JSON format, ready for analysis, database integration, or downstream automation workflows.

Data Fields

The scraper extracts the following fields for each hotel:

Field	Type	Description
hotelName	String	Full name of the hotel or accommodation property
price	Number	Nightly price (numeric value extracted from price text)
currency	String	Currency symbol or ISO code (e.g., €, $, USD, GBP)
rating	String	Text rating label (e.g., "Exceptional", "Very Good", "Good")
reviewScore	Number	Numerical review score from 0-10 (e.g., 9.2, 8.4)
reviewCount	Number	Total number of guest reviews
location	String	Address, neighborhood, or district location
distance	String	Distance from city center or landmark (e.g., "2.5 km from centre")
stars	Number	Star rating classification (1-5 stars)
imageUrl	String	URL to main hotel image
bookingUrl	String	Full URL to hotel booking page on Booking.com

How to Scrape Booking.com Hotels

Follow these 7 steps to extract hotel data from Booking.com:

Step 1: Open the Actor

Navigate to the Booking.com Hotel Scraper in Apify Console and click "Try for free" or "Start".

Step 2: Configure Destination

Enter your target destination in the "Destination" field. You can search by city name (e.g., "Paris"), country (e.g., "Spain"), landmark (e.g., "Eiffel Tower"), or specific hotel name. The scraper will use Booking.com's autocomplete to select the best match.

Step 3: Set Check-in and Check-out Dates

Optionally specify check-in and check-out dates in YYYY-MM-DD format (e.g., "2026-03-20" and "2026-03-23"). If omitted, Booking.com will display default availability. The scraper navigates the calendar interface automatically to select your specified dates.

Step 4: Set Maximum Results

Specify how many hotels you want to extract in the "Max results" field. Default is 20. Set to 0 for unlimited results (scraper will continue until all available properties are extracted or 50 pages are reached).

Step 5: Run the Scraper

Click "Start" to launch the scraper. The actor will fill Booking.com's search form, select dates via calendar navigation, and begin extracting property cards from search results pages.

Step 6: Monitor Progress

Watch the log output to see extraction progress. The scraper reports how many property cards are found on each page and tracks total results extracted. Pagination is handled automatically.

Step 7: Download Results

Once complete, download results in JSON, CSV, or Excel format from the Dataset tab. Each hotel record contains all extracted fields in structured format, ready for analysis or integration.

Input Parameters

Parameter	Type	Required	Default	Description
destination	String	Yes	-	City, region, landmark, or hotel name to search. Uses Booking.com autocomplete.
checkIn	String	No	-	Check-in date in YYYY-MM-DD format (e.g., "2026-03-15"). Calendar navigates up to 12 months ahead.
checkOut	String	No	-	Check-out date in YYYY-MM-DD format (e.g., "2026-03-18"). Must be after check-in date.
maxResults	Integer	No	20	Maximum number of hotel results to extract. Set to 0 for unlimited (up to 50 pages).
sortBy	String	No	"popularity"	Sorting mode: "popularity", "price", or "rating" (configured in input schema but not yet implemented in code).
guests	Integer	No	2	Number of adult guests (configured in input schema but not yet implemented in code).

Example Input

{
  "destination": "Barcelona",
  "checkIn": "2026-03-20",
  "checkOut": "2026-03-23",
  "maxResults": 50
}

This configuration searches for hotels in Barcelona with a 3-night stay in March 2026, extracting up to 50 properties.

Example Output

{
  "hotelName": "Hotel Arts Barcelona",
  "price": 450,
  "currency": "€",
  "rating": "Exceptional",
  "reviewScore": 9.2,
  "reviewCount": 1847,
  "location": "Port Olímpic, Barcelona",
  "distance": "2.5 km from centre",
  "stars": 5,
  "imageUrl": "https://cf.bstatic.com/xdata/images/hotel/square240/123456789.jpg",
  "bookingUrl": "https://www.booking.com/hotel/es/arts-barcelona.html"
}

{
  "hotelName": "W Barcelona",
  "price": 380,
  "currency": "€",
  "rating": "Very Good",
  "reviewScore": 8.4,
  "reviewCount": 2156,
  "location": "Barceloneta, Barcelona",
  "distance": "3.1 km from centre",
  "stars": 5,
  "imageUrl": "https://cf.bstatic.com/xdata/images/hotel/square240/987654321.jpg",
  "bookingUrl": "https://www.booking.com/hotel/es/w-barcelona.html"
}

{
  "hotelName": "Casa Bonay",
  "price": 165,
  "currency": "€",
  "rating": "Good",
  "reviewScore": 8.1,
  "reviewCount": 892,
  "location": "Eixample, Barcelona",
  "distance": "1.2 km from centre",
  "stars": 4,
  "imageUrl": "https://cf.bstatic.com/xdata/images/hotel/square240/456789123.jpg",
  "bookingUrl": "https://www.booking.com/hotel/es/casa-bonay.html"
}

Is It Legal to Scrape Booking.com?

Web scraping public data from Booking.com for personal research, price monitoring, and market analysis is generally permitted under fair use principles in many jurisdictions. Booking.com displays hotel listings, prices, and reviews as publicly accessible information without requiring user authentication. Courts in the United States and European Union have established precedents protecting the scraping of publicly available data when done responsibly, without circumventing technical protections or violating terms of service that constitute enforceable contracts.

However, legal interpretations vary by jurisdiction, and Booking.com's Terms of Service may prohibit automated scraping. Users of this scraper should review applicable laws in their region, respect rate limits to avoid disrupting Booking.com's services, and ensure scraped data is used ethically and in compliance with data protection regulations such as GDPR. This actor is intended for research and analysis purposes. Commercial redistribution of scraped data may violate Booking.com's intellectual property rights or database protection laws. Always consult legal counsel when scraping data for business purposes.

Pricing

This actor uses Playwright (headless browser automation), which consumes more compute units than HTTP-only scrapers due to full browser rendering and JavaScript execution.

Estimated costs:

• 0.04-0.06 compute units (CU) per hotel scraped
• 50 hotels: approximately 2.5-3 CU
• 100 hotels: approximately 5-6 CU
• 500 hotels: approximately 25-30 CU

Apify's free tier includes 5 compute units per month, sufficient for approximately 80-100 hotels. Paid plans start at $49/month with 200 CU included. For large-scale scraping (1000+ hotels), consider scheduling runs during off-peak hours or using Apify's residential proxy options to reduce blocking risks.

See Apify pricing for detailed compute unit rates and plan comparisons.

Frequently Asked Questions

Can I scrape hotels from multiple destinations in one run?

Currently, the scraper supports a single destination per run. To scrape multiple cities or regions, create separate actor runs for each destination or use Apify's Scheduler to queue multiple runs with different input configurations. You can also use the API to programmatically start runs for multiple destinations and aggregate results.

Why does the scraper fill the search form instead of using direct URLs?

Booking.com employs sophisticated anti-bot protection that strips query parameters from direct URLs and redirects users to the homepage. By filling the search form interactively, typing the destination slowly to trigger autocomplete, and clicking through the calendar interface, the scraper mimics genuine user behavior, significantly reducing detection and blocking risks.

What happens if check-in or check-out dates are not provided?

If dates are omitted, the scraper proceeds without selecting calendar dates, and Booking.com displays default availability (typically the next available night or flexible date ranges). This is useful for general price research where specific dates are less critical than overall property listings and average pricing.

How does the scraper handle pagination?

The scraper automatically detects "Next page" buttons or links at the bottom of search results and enqueues subsequent pages for extraction. Pagination continues until the specified maxResults limit is reached, no more pages are available, or the maximum page limit (50 pages) is hit. Each page typically contains 20-30 property cards.

Can I filter results by price range or star rating?

The current implementation extracts all properties returned by Booking.com's search results. Filtering by price, star rating, or guest rating can be applied post-extraction using dataset filtering in Apify Console or by processing the JSON output programmatically. Future versions may support pre-filtering via additional input parameters.

Related Actors

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Developer: lanky_quantifier Framework: Crawlee 3.16 + Playwright Support: For issues, feature requests, or custom scraping solutions, contact via Apify Console or GitHub.