Wyndham Hotel Scraper

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

This Wyndham hotel scraper covers the full Wyndham Hotels & Resorts portfolio: Wyndham, Wyndham Garden, Wyndham Grand, Ramada, Days Inn, Super 8, Howard Johnson, Travelodge, La Quinta, Baymont, Microtel, and more. It never mixes in hotels from other chains.

What you can scrape

• Wyndham hotel availability for specific dates
• Room types, bed types, and maximum occupancy
• Booking.com hotel prices and rate plans
• Official Wyndham hotel details — address, geo-coordinates, phone, amenities, guest rating
• Hotel details: address, city, country, coordinates, star rating, review score
• Amenities and images
• 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 Wyndham property, e.g. Wyndham Garden Chinatown New York
• Area / city — discover Wyndham-family hotels in a destination, e.g. New York
• ZIP / postal code — discover Wyndham-family hotels near a postal code, e.g. 10019

Choose your data source:

• booking_com — live rates and availability from Booking.com
• official — property data from Wyndham's own hotel directory
• 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": "Wyndham Garden Chinatown 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": "New York",
  "source": "official",
  "check_in": "2026-11-01",
  "check_out": "2026-11-03",
  "adults": 2,
  "limit": 10
}

Output example

{
  "hotel_id": "17720",
  "source": "official",
  "source_url": "https://www.wyndhamhotels.com/wyndham-garden/new-york-new-york/wyndham-garden-chinatown/overview",
  "observed_at": "2026-08-22T00:00:00.000Z",
  "hotel_name": "Wyndham Garden Chinatown",
  "brand": "Wyndham",
  "check_in": "2026-10-15",
  "check_out": "2026-10-17",
  "length_of_stay": 2,
  "adults": 2,
  "children": 0,
  "rooms": 1,
  "address": "93 Bowery",
  "city": "New York",
  "country": "US",
  "postal_code": "10002",
  "latitude": 40.717136,
  "longitude": -73.995453,
  "review_score": 3.9,
  "review_count": 674,
  "metadata": {
    "amenities": ["BRKFST", "GYM", "RSTRNT"],
    "phone": "646-3293400"
  }
}

Use cases

• Hotel price comparison across Wyndham 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.
• 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.