Accor Hotel Scraper

Get structured, up-to-date data on Accor hotels — availability, room rates, and property details — pulled from Booking.com and Accor's official site. Built for hotel price comparison, travel research, rate monitoring, and hospitality analytics.

This Accor hotel scraper covers the full Accor portfolio: Raffles, Fairmont, Sofitel, MGallery, Pullman, Swissôtel, Novotel, Mercure, Mama Shelter, ibis, ibis Styles, ibis budget, and more. It never mixes in hotels from other chains.

What you can scrape

• Accor hotel availability for specific dates
• Room types and rates from Booking.com
• Official Accor property resolution — confirmed address, city, postal code
• Hotel details: address, city, country, star rating, review score
• Amenities and images (via Booking.com)
• Cancellation policies and refundability
• Meal plans (breakfast included, etc.)
• Date-specific hotel pricing for any check-in/check-out combination

How it works

Search by:

• Hotel name — target one specific Accor property, e.g. Sofitel New York
• Area / city — discover Accor-family hotels in a destination, e.g. Paris
• ZIP / postal code — discover Accor-family hotels near a postal code, e.g. 10036

Choose your data source:

• booking_com — live rates and availability from Booking.com
• official — property resolution from Accor's own site
• both — both sources, clearly labeled per record

Every record includes source, source_url, and observed_at so you always know where the data came from and when it was collected.

Set check-in/check-out dates, number of adults, children, and rooms, and a preferred currency. Results are returned as clean, normalized JSON — no raw HTML, no duplicate records.

Input example

{
  "hotel": "Sofitel New York",
  "source": "both",
  "check_in": "2026-10-15",
  "check_out": "2026-10-17",
  "adults": 2,
  "children": 0,
  "rooms": 1,
  "currency": "USD",
  "limit": 5
}

Or discover hotels in an area:

{
  "area": "Paris",
  "source": "booking_com",
  "check_in": "2026-11-01",
  "check_out": "2026-11-03",
  "adults": 2,
  "limit": 10
}

Output example

{
  "hotel_id": "2185",
  "source": "booking_com",
  "source_url": "https://www.booking.com/hotel/us/sofitel-new-york.html",
  "observed_at": "2026-08-22T00:00:00.000Z",
  "hotel_name": "Sofitel New York",
  "brand": "Accor",
  "check_in": "2026-10-15",
  "check_out": "2026-10-17",
  "length_of_stay": 2,
  "adults": 2,
  "children": 0,
  "rooms": 1,
  "room_type": "Superior Room",
  "price": 450,
  "total_price": 450,
  "currency": "USD",
  "availability": true,
  "address": "45 West 44th Street",
  "city": "New York",
  "country": "US",
  "star_rating": 4,
  "review_score": 8.4,
  "review_count": 3285
}

Use cases

• Hotel price comparison across Accor properties
• Hotel market research and competitive pricing analysis
• Travel data pipelines and rate monitoring
• Hospitality analytics and demand forecasting
• Hotel availability monitoring for revenue management

Notes

• Fields that aren't available for a given hotel or source are returned as null — nothing is fabricated. Accor's official-site resolution confirms a matched address but not always a room rate or property name, so those fields may be null on official-source records even when the address is confirmed.
• When source is both, Booking.com and official-site data are always kept in separate, clearly labeled records rather than merged.
• If one source is temporarily unavailable, the Actor continues with the other rather than failing the whole run.