Description
Explore over 20.6 million authentic
Tripadvisor hotel reviews
, providing an unparalleled look into global travel sentiment and guest experiences. Sourced directly from tripadvisor.com, this extensive dataset includes crucial details such as Hotel Name, Hotel City, Rating, Review Title, and the comprehensive Review Text. You'll also find valuable context like Language, Reviewer Name, Stayed At and Reviewed At dates, alongside Helpful Count and Reviewer Location. Spanning a vast array of hotels worldwide, this collection offers deep insights into diverse guest experiences across numerous regions and cities. It is ideal for market research, competitive analysis, customer sentiment analysis, and powering AI/ML models within the travel and hospitality domain. Leverage these rich insights to optimize your strategies, enhance customer satisfaction, and gain a significant competitive edge in a dynamic industry.
Highlights
Over 20.6 million Tripadvisor reviews.
Extensive global coverage across hotels.
Includes recently scraped review data.
Detailed ratings, review text, helpfulness, photos.
Sample Data
Preview of available data:
| Url | Photos | Rating | Source | Uniq Id | Version | Language | Review Id | Stayed At | Hotel City | Hotel Name | Scraped At | Location Id | Review Text | Reviewed At | Imported At | Hotel Region | Review Title | Helpful Count | Reviewer Name | Source Domain | Total Reviews | Reviewer Location | Additional Details | Additional Ratings |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| https://www.tripadvisor.com... | [] | 5 | tripadvisor | cdf143d6273b5b6c | 1781640166706 | in | 1000000013 | 2025-03-31 | Tangerang | Mercure Serpong Alam Sutera | 2026-06-15 10:27:17 | 4432913 | Buka puasa bersama keluarga... | 2025-03-27 | 2026-06-16 20:02:46 | Province Java | Iftar keluarga di mercure | 0 | Daydream12649063685 | tripadvisor.com | 3975 | \N | {"trip_type": "BUSINESS", "... | [] |
| https://www.tripadvisor.com... | [{"image": "https://dynamic... | 5 | tripadvisor | bb90dbfcc88c0533 | 1781425751651 | fr | 1000000027 | 2025-03-31 | Houmt | TUI BLUE Palm Beach Palace | 2026-06-11 22:26:20 | 8075809 | Superbe expérience, équipe ... | 2025-03-27 | 2026-06-14 08:29:11 | Medenine Governorate | Au top !!! À faire !!! | 0 | Julie L | tripadvisor.com | 2650 | \N | {"trip_type": "COUPLES", "p... | [{"name": "Value", "rating"... |
| https://www.tripadvisor.com... | [] | 5 | tripadvisor | 725b88d2a12832ee | 1781425751651 | en | 1000000086 | 2025-03-31 | Punta | Dreams Macao Beach Punta Cana | 2026-06-05 08:28:47 | 19985038 | We had a great time at Drea... | 2025-03-27 | 2026-06-14 08:29:11 | Dominican Republic | Great family vacay destination | 0 | Lacey S | tripadvisor.com | 10072 | \N | {"trip_type": "NONE", "plac... | [] |
| https://www.tripadvisor.com... | [] | 5 | tripadvisor | 11847f07d68f6b69 | 1781425751651 | en | 1000000099 | 2025-03-31 | Beer | Beer Head Holiday Park | 2026-06-07 21:37:36 | 4493458 | Always perfect. A pleasant,... | 2025-03-27 | 2026-06-14 08:29:11 | Devon England | Perfect spot. | 0 | Rachel C | tripadvisor.com | 927 | Poole, United Kingdom | {"trip_type": "SOLO", "plac... | [{"name": "Value", "rating"... |
| https://www.tripadvisor.com... | [{"image": "https://dynamic... | 5 | tripadvisor | 8635b071f12b3397 | 1781425751651 | en | 1000000139 | 2025-03-31 | Hammam | Marhaba Palace | 2026-06-12 02:29:57 | 316751 | Well what can I say ! One o... | 2025-03-27 | 2026-06-14 08:29:11 | Sousse Governorate | Amazing holiday! | 0 | Lesley F | tripadvisor.com | 5780 | \N | {"trip_type": "FRIENDS", "p... | [{"name": "Value", "rating"... |
| https://www.tripadvisor.com... | [] | 5 | tripadvisor | 2eb39931b7edd24d | 1781425751651 | en | 1000000232 | 2025-03-31 | Palmar | Ambre Mauritius | 2026-06-11 14:13:59 | 316733 | Ten points to all members o... | 2025-03-27 | 2026-06-14 08:29:11 | Palmar | Perfect holiday | 1 | slavica1003 | tripadvisor.com | 11926 | Düsseldorf, Germany | {"trip_type": "NONE", "plac... | [{"name": "Value", "rating"... |
| https://www.tripadvisor.com... | [{"image": "https://dynamic... | 5 | tripadvisor | 3c55c9aab24da733 | 1781425751651 | tr | 1000000256 | 2024-10-31 | Turkler | Aydinbey Gold Dreams | 2026-06-08 22:07:35 | 557161 | Aydınbey Gold Dreams Otel’d... | 2025-03-27 | 2026-06-14 08:29:11 | Mediterranean Coast | Eğlence ve Konforun Buluştu... | 0 | poseydon | tripadvisor.com | 1721 | Izmir, Türkiye | {"trip_type": "COUPLES", "p... | [{"name": "Value", "rating"... |
| https://www.tripadvisor.com... | [] | 4 | tripadvisor | 85d16190ca451c1f | 1781640166706 | in | 1000000287 | 2025-03-31 | Tanjung | Sheraton Belitung Resort | 2026-06-14 20:30:32 | 19339211 | bagus, dengan makanan yang ... | 2025-03-27 | 2026-06-16 20:02:46 | Islands Suma | bagus | 0 | Traveler43966829183 | tripadvisor.com | 750 | \N | {"trip_type": "FAMILY", "pl... | [] |
Data Fields
This dataset includes the following data points:
Why This Data
This hotel reviews dataset from Tripadvisor 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 & Competitor Analysis: E-commerce platforms can analyze competitor hotel ratings, review sentiment, and amenity mentions in specific regions to optimize dynamic pricing and travel package deals.
Hotel Performance Benchmarking: Hotel chains can benchmark their property performance against competitors by comparing average ratings, sentiment trends, and specific positive/negative mentions across cities and regions for competitive intelligence.
Automated Customer Feedback Analysis: Train an AI model using Review Text and Rating to automatically classify and extract sentiment for specific aspects of hotel stays, providing scalable insights into customer satisfaction.
Amenity & Service Prioritization: Hotel developers can analyze Review Text and Additional Details to identify desired amenities, service gaps, and emerging preferences that guide future product development.
Localized Content & SEO Strategy: Travel blogs and OTAs can extract frequently mentioned keywords and popular themes from Review Title and Review Text to optimize local SEO content and create engaging travel guides for specific destinations.
Emerging Destination Market Research: Identify new or trending regions and cities with increasing positive reviews and high ratings over time to inform investment in new hotel properties or marketing campaigns.
Proactive Reputation Management: Hotel groups can use aspect-based sentiment analysis on Review Text to quickly detect recurring service issues or common complaints across their properties, enabling proactive service improvements.
Travel Trend Forecasting: Analyze Review Text over time, filtered by Stayed At or Reviewed At, to identify shifts in traveler preferences for specific hotel features or experiences, aiding future product development.
Get Access to This Dataset
Start using this dataset today. Available in CSV, JSON, and Excel formats with flexible access options.