Booking.com data extraction

Who this is for

Revenue managers benchmarking competitor pricing, OTA tools feeding market data engines, travel investors scoping a hotel acquisition or portfolio value, PropTech companies building hospitality datasets, and tourist boards tracking market dynamics.

What we extract per hotel

• Identity: hotel name, Booking ID, URL, star rating, category (hotel, apart-hotel, B&B, hostel, resort).
• Location: full address, city, GPS, neighbourhood, distance to key POIs (airport, city centre, beach).
• Content: description, images (up to 30 per hotel), key amenities list, check-in/out times.
• Inventory: room types with capacity, bed configuration, price for the requested date window, availability flag, cancellation policy.
• Ratings: aggregate review score, review count, score breakdown (cleanliness, comfort, location, staff, value, WiFi).
• Reviews: individual reviews with date, traveller country, stay length, type (business/leisure/family), positive and negative comments.
• Signals: Genius discount flag, free cancellation flag, breakfast included flag, WiFi quality score, sustainability badge.

Typical extraction scenarios

• Competitor pricing: 50 direct competitor hotels in a target city, daily rate pull for a 90-day rolling window, fed into a revenue engine.
• Market intelligence: every 4-5 star hotel in Barcelona with reviews, for a portfolio valuation study.
• Review sentiment: all reviews of a target hotel chain across 20 cities, with sentiment scoring and traveller segmentation.
• Acquisition scoping: hotels with a 7.5+ score and 100+ reviews in a target investment city, for M&A pipeline.
• Event pricing: daily rate evolution in a target city around a major event (F1, fashion week, concerts).

How the delivery works

1. Brief: destination (city, region, GPS radius), date window, traveller profile, star filter, amenities required.
2. Extraction: parameterised search with date-aware rate pull per hotel.
3. Enrichment: rate history aggregation, competitive-set scoring, sentiment analysis on reviews, event-calendar overlay.
4. Dedup: on Booking ID and on hotel name + address combination.
5. Delivery: CSV / Google Sheet / BigQuery / S3 within 48-72h, or scheduled daily revenue feed.

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