TravelWatch — Booking.com Hotel Price Tracker

Search and extract hotel prices from Booking.com for any destination and date range. Compare hotel rates, ratings, review scores, locations, and amenities to find the best accommodation deals. Built for travel agencies, price comparison services, and savvy travelers who want data-driven booking decisions.

Data extracted

• Hotel name — Official property name from the listing
• Price — Nightly or total stay price with currency
• Rating — Guest review score from Booking.com (out of 10)
• Review count — Total number of guest reviews
• Review score — Qualitative score label (e.g., "Superb", "Very Good")
• Location — Neighborhood or area within the destination
• Amenities — Available facilities such as WiFi, parking, pool, breakfast
• Image — Primary hotel photo URL
• Direct link — URL to the Booking.com property page for the given dates

Use cases

• Price comparison — Compare hotel prices across properties for specific dates
• Travel planning — Find the best rated hotels within your budget for any destination
• Market research — Analyze hotel pricing trends across cities, seasons, and property types
• Revenue management — Monitor competitor hotel pricing for dynamic rate adjustments
• Travel agency automation — Build automated hotel search and recommendation pipelines
• Deal alerts — Track hotel prices over time and get notified when rates drop

Features

• Search any destination worldwide with specific check-in and check-out dates
• Guest count customization for accurate pricing
• Residential proxy support for reliable Booking.com access
• Automatic pagination through search results pages
• Structured JSON output with all key hotel attributes

How to use

1. Enter a destination (e.g., "Paris, France", "New York", "Tokyo")
2. Set checkIn and checkOut dates in YYYY-MM-DD format
3. Optionally adjust the number of guests (default: 2)
4. Set maxResults to control how many hotel listings to return (default: 100)
5. Enable a residential proxy for reliable Booking.com access on larger searches
6. Run the actor and get structured JSON data with hotel names, prices, ratings, amenities, and direct booking links

Example input

{
  "destination": "Paris, France",
  "checkIn": "2026-06-01",
  "checkOut": "2026-06-05",
  "guests": 2,
  "maxResults": 100
}

Example output

{
  "name": "Hotel Le Marais",
  "price": 185,
  "currency": "EUR",
  "rating": 8.7,
  "reviewCount": 3421,
  "reviewScore": "Fabulous",
  "location": "Le Marais, 4th arr., Paris",
  "amenities": ["Free WiFi", "Breakfast included", "Air conditioning"],
  "url": "https://www.booking.com/hotel/fr/le-marais.html?checkin=2026-06-01&checkout=2026-06-05",
  "imageUrl": "https://cf.bstatic.com/xdata/images/hotel/...",
  "checkIn": "2026-06-01",
  "checkOut": "2026-06-05",
  "scrapedAt": "2026-02-14T12:00:00.000Z"
}

Pricing

• $0.50 per actor start
• $0.003 per hotel listing extracted

Example: Searching 200 hotels in Paris costs $0.50 + $0.60 = $1.10 total.

Tips

• Search multiple destinations in a single run. Queue up several destination searches to pay the $0.50 start fee once. Compare hotel prices across cities for the same dates to find the best value destination.
• Use realistic date ranges. Booking.com shows different prices and availability depending on lead time. Search 2-4 weeks ahead for the most accurate pricing data.
• Enable residential proxies for large searches. Booking.com rate-limits aggressive crawling. Use Apify residential proxies for reliable extraction when collecting 100+ hotel listings.
• Schedule weekly runs for price trend tracking. Hotel prices fluctuate significantly by season and day of week. Set up recurring runs to build a price history dataset and identify the cheapest booking windows.
• Filter by rating and reviewCount for quality leads. High rating (8.0+) combined with high review count (500+) signals consistently good properties — useful for travel agencies building curated recommendation lists.

Notes

This v1 focuses on Booking.com hotel search results. Google Flights integration requires Playwright for JavaScript-heavy rendering and is planned for a future version.