Description
Unlock nearly 50 million historical Booking.com hotel reviews and guest ratings, collected from 2010 to 2024. This extensive dataset provides unparalleled insights into global traveler experiences across countless properties. Each record features rich details including positive and negative review texts, individual ratings, average hotel scores, reviewer demographics, and specific hotel attributes like address and country. Ideal for comprehensive sentiment analysis, identifying emerging market trends, competitive benchmarking, and training advanced AI/ML models. This invaluable resource empowers travel & hospitality businesses, researchers, and data scientists to deeply understand guest satisfaction and industry dynamics directly from Booking.com.
Highlights
Nearly 50 million Booking.com reviews.
Global Booking.com hotel review coverage.
Reviews from 2010 to 2024.
Includes full review text, sentiment, ratings.
Sample Data
Preview of available data:
| Url | Tags | Rating | Source | Country | Uniq Id | Version | Hotel Id | Language | Stayed At | Hotel Name | Scraped At | Reviewed At | Imported At | Review Title | Average Score | Helpful Count | Hotel Address | Reviewer Name | Source Domain | Reviewer Country | Negative Review Text | Positive Review Text |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| https://www.booking.com/hot... | Leisure trip, Family with y... | 9 | Booking | إسبانيا | 0000000000000000 | 1782244445465 | 2816895 | fr | Stayed in July 2023 | بي فري غرانادا | 2026-06-23 10:45:00 | 2023-07-15 23:27:34 UTC | 2026-06-23 19:54:05 | Allez y les yeux fermés, | 8.3 | 0 | Calle Tiburón, 2, Chana, 18... | Nafaa | https://www.booking.com | France | \N | Personnel au top ,fait tout... |
| https://www.booking.com/hot... | Leisure trip, Couple, Class... | 9 | Booking | United Kingdom | 00000013a005bd4f | 1780898753813 | 178052 | en | Stayed in September 2024 | The Golden Fleece Hotel, Th... | 2026-06-03 12:05:16 | 2024-09-20 20:17:21 UTC | 2026-06-08 06:05:53 | Great stay in a lovely coac... | 8.4 | 0 | 42 Market Place, Thirsk, YO... | Philip | https://www.booking.com | United Kingdom | \N | Super. Position and excelle... |
| https://www.booking.com/hot... | Leisure trip, Family with y... | 8 | Booking | France | 00000015a2b0e747 | 1780462723111 | 1052044 | fr | Stayed in February 2024 | Hôtel & Spa Les Carrettes | 2026-05-26 16:32:52 | 2024-03-08 12:43:04 UTC | 2026-06-03 04:58:43 | Very good | 8 | \N | Les Islettes, 73450 Valmein... | Mathieu | https://www.booking.com | France | \N | \N |
| https://www.booking.com/hot... | Leisure trip, Family with y... | 6 | Booking | 일본 | 0000001912eb4a56 | 1782030741133 | 1281296 | xu | Stayed in May 2025 | 사쿠라 테라스 더 갤러리 | 2026-06-20 10:22:58 | 2025-06-09 06:45:24 UTC | 2026-06-21 08:32:21 | Overall good. We enjoyed th... | 8.8 | 0 | 601-8002 교토후, 교토, Minami-ku... | Erlie | https://www.booking.com | United States | Overall, the stay was good.... | Welcome drinks, breakfast. |
| https://www.booking.com/hot... | Leisure trip, Couple, Queen... | 5 | Booking | United States | 000000768359893c | 1779695550011 | 1911599 | de | Stayed in May 2023 | Arlo Williamsburg | 2026-05-21 00:52:05 | 2023-05-23 16:44:28 UTC | 2026-05-25 07:52:30 | Passable | 8.1 | \N | 96 Wythe Avenue, Brooklyn, ... | Alice | https://www.booking.com | United States | \N | \N |
| https://www.booking.com/hot... | Leisure trip, Couple, Doubl... | 9 | Booking | France | 000000788e891552 | 1780898753813 | 340605 | nl | Stayed in September 2024 | Zenitude Hôtel-Résidences M... | 2026-06-06 16:33:57 | 2024-09-15 19:05:54 UTC | 2026-06-08 06:05:53 | Superb | 7.3 | 0 | 50 Route de Port Royal des ... | Peter | https://www.booking.com | Netherlands | Niets. | De ligging, de grootte van ... |
| https://www.booking.com/hot... | Leisure trip, Solo traveler... | 8 | Booking | Αυστρία | 0000014e678979e0 | 1782030741133 | 409693 | de | Stayed in February 2025 | Hotel Orangerie | 2026-06-15 23:51:21 | 2025-02-23 12:17:56 UTC | 2026-06-21 08:32:21 | Very good | 8 | \N | Grieshofgasse 11, 12. Meidl... | Stefan | https://www.booking.com | Germany | \N | \N |
| https://www.booking.com/hot... | Leisure trip, Couple, Good ... | 7 | Booking | Almanya | 0000015953da7f20 | 1781377760816 | 61441 | de | Stayed in January 2026 | Good Morning+ Halle Leipzig | 2026-06-12 09:47:18 | 2026-01-09 21:08:09 UTC | 2026-06-13 19:09:20 | Ein gutes Hotel für eine Na... | 7.8 | 1 | Hotelstr.1, 06184 Halle an ... | Walter | https://www.booking.com | Germany | Dass die Sauna nur per Beza... | Gutes Frühstück und ein ger... |
Data Fields
This dataset includes the following data points:
Why This Data
This hotel reviews dataset from Booking provides comprehensive market intelligence and competitive insights. Perfect for:
- Market Research: Understand market trends and customer preferences
- Competitive Analysis: Compare pricing, products, and strategies
- Business Intelligence: Make data-driven decisions
- Price Monitoring: Track price changes and optimize your pricing
Use Cases
This dataset is perfect for various applications:
Dynamic Pricing Optimization: Analyze historical Average Score, Rating, and Reviewed At trends to adjust hotel pricing in real-time for maximum occupancy and revenue on Booking.com.
Competitor Performance Benchmarking: Benchmark competitor hotels by analyzing their Average Score, Negative Review Text, and Positive Review Text to identify market gaps and service improvement areas on Booking.com.
Advanced Sentiment Analysis Model Training: Train machine learning models using the Negative Review Text and Positive Review Text to automate sentiment detection and categorize specific guest feedback topics for Booking.com listings.
Traveler Preference & Amenity Forecasting: Identify emerging traveler preferences and recurring pain points by analyzing Tags and themes in Positive Review Text/Negative Review Text across Booking.com hotels to inform new product offerings.
Targeted Content & Keyword Strategy: Extract popular keywords and phrases from Review Title, Negative Review Text, and Positive Review Text to optimize Booking.com hotel descriptions and generate engaging travel content for specific Reviewer Country audiences.
Get Access to This Dataset
Start using this dataset today. Available in CSV, JSON, and Excel formats with flexible access options.