1) Data Introduction • The Hotels from Around the World Dataset provides over 1,000 hotel data (including ratings, reviews, and room rates) provided by Booking.com .

2) Data Utilization (1) Hotels from Around the World Dataset has characteristics that: • This dataset is a list of over 10 major city hotels worldwide. This includes ratings, city, country, and number of customer reviews. • This dataset was extracted on February 18, 2025 and is based on a one-night reservation from March 18-19, 2025. (2) Hotels from Around the World Dataset can be used to: • Analysis of hotel ratings and reviews : Using hotel-specific ratings and review data, it can be used for text mining and emotional analysis studies such as customer satisfaction analysis, hotel service quality assessment, and classification of positive and negative reviews. • Tourism and Location Strategy Research : It can be used for research on the tourism industry and real estate market, including comparing characteristics by popular area, location strategy, and hotel rating by analyzing various characteristics such as hotel location, rating, convenience facilities, and number of reviews.

No of Hotel Rooms: MF: Corsica data was reported at 88.000 Unit th in Feb 2025. This records an increase from the previous number of 87.000 Unit th for Jan 2025. No of Hotel Rooms: MF: Corsica data is updated monthly, averaging 233.000 Unit th from Jan 2011 (Median) to Feb 2025, with 170 observations. The data reached an all-time high of 390.000 Unit th in Aug 2024 and a record low of 49.000 Unit th in Jan 2021. No of Hotel Rooms: MF: Corsica data remains active status in CEIC and is reported by National Institute of Statistics and Economic Studies. The data is categorized under Global Database’s France – Table FR.Q010: Hotels Statistics: Number of Hotel Rooms.

No of Hotel Rooms: DOM: Guadeloupe data was reported at 86.090 Unit th in Feb 2025. This records a decrease from the previous number of 95.070 Unit th for Jan 2025. No of Hotel Rooms: DOM: Guadeloupe data is updated monthly, averaging 95.215 Unit th from Jan 2011 (Median) to Feb 2025, with 170 observations. The data reached an all-time high of 108.700 Unit th in Dec 2016 and a record low of 11.500 Unit th in Apr 2020. No of Hotel Rooms: DOM: Guadeloupe data remains active status in CEIC and is reported by National Institute of Statistics and Economic Studies. The data is categorized under Global Database’s France – Table FR.Q010: Hotels Statistics: Number of Hotel Rooms.

The Agoda Hotel Listings Dataset provides a structured and detailed view of accommodations worldwide, offering essential data for travel industry professionals, market analysts, and businesses. This dataset includes key details such as hotel names, locations, review scores, pricing, availability, room configurations, amenities, guest reviews, property highlights, and property surroundings.

With this dataset, users can:

Analyze market trends to understand booking behaviors, pricing dynamics, and seasonal demand.
Enhance travel recommendations by identifying top-rated hotels based on reviews, location, and amenities.
Optimize pricing and revenue strategies by benchmarking property performance and availability patterns.
Assess guest satisfaction through sentiment analysis of ratings and reviews.
Refine location-based insights by analyzing property surroundings and nearby attractions.

Designed for hospitality businesses, travel platforms, AI-powered recommendation engines, and pricing strategists, this dataset enables data-driven decision-making to improve customer experience and business performance.

Use Cases

Agoda Hotel Listings in Thailand
Gain insights into Thailand’s hospitality market, from luxury resorts in Phuket to boutique hotels in Bangkok. Analyze review scores, availability trends, and traveler preferences to refine booking strategies.
Agoda Hotel Listings in Japan
Explore hotel data across Japan’s major cities and rural retreats, ideal for travel planners targeting visitors to Tokyo, Kyoto, and Osaka. This dataset includes review scores, pricing, and property highlights.
Agoda Hotel Listings with Review Scores Greater Than 9
A curated selection of high-rated hotels worldwide, ideal for luxury travel planners and market researchers focused on premium accommodations that consistently exceed guest expectations.
Agoda Hotel Listings in the United States with More Than 1000 Reviews
Analyze well-established and highly reviewed hotels across the U.S., ensuring reliable guest feedback for market insights and customer satisfaction benchmarking.

This dataset serves as an indispensable resource for travel analysts, hospitality businesses, and data-driven decision-makers, providing the intelligence needed to stay competitive in the ever-evolving travel industry.

Egypt Number of Hotel Rooms data was reported at 166,287.000 Unit in 2020. This records a decrease from the previous number of 168,322.000 Unit for 2019. Egypt Number of Hotel Rooms data is updated yearly, averaging 109,562.000 Unit from Dec 1982 (Median) to 2020, with 39 observations. The data reached an all-time high of 197,830.000 Unit in 2017 and a record low of 18,100.000 Unit in 1982. Egypt Number of Hotel Rooms data remains active status in CEIC and is reported by Ministry of Tourism and Antiquities. The data is categorized under Global Database’s Egypt – Table EG.Q017: Number of Hotels, Rooms and Beds.

The Booking Hotel Listings Dataset provides a structured and in-depth view of accommodations worldwide, offering essential data for travel industry professionals, market analysts, and businesses. This dataset includes key details such as hotel names, locations, star ratings, pricing, availability, room configurations, amenities, guest reviews, sustainability features, and cancellation policies.

With this dataset, users can:

Analyze market trends to understand booking behaviors, pricing dynamics, and seasonal demand.
Enhance travel recommendations by identifying top-rated hotels based on reviews, location, and amenities.
Optimize pricing and revenue strategies by benchmarking property performance and availability patterns.
Assess guest satisfaction through sentiment analysis of ratings and reviews.
Evaluate sustainability efforts by examining eco-friendly features and certifications.

Designed for hospitality businesses, travel platforms, AI-powered recommendation engines, and pricing strategists, this dataset enables data-driven decision-making to improve customer experience and business performance.

Use Cases

Booking Hotel Listings in Greece
Gain insights into Greece’s diverse hospitality landscape, from luxury resorts in Santorini to boutique hotels in Athens. Analyze review scores, availability trends, and traveler preferences to refine booking strategies.

Booking Hotel Listings in Croatia
Explore hotel data across Croatia’s coastal and inland destinations, ideal for travel planners targeting visitors to Dubrovnik, Split, and Plitvice Lakes. This dataset includes review scores, pricing, and sustainability features.

Booking Hotel Listings with Review Scores Greater Than 9
A curated selection of high-rated hotels worldwide, ideal for luxury travel planners and market researchers focused on premium accommodations that consistently exceed guest expectations.

Booking Hotel Listings in France with More Than 1000 Reviews
Analyze well-established and highly reviewed hotels across France, ensuring reliable guest feedback for market insights and customer satisfaction benchmarking.

This dataset serves as an indispensable resource for travel analysts, hospitality businesses, and data-driven decision-makers, providing the intelligence needed to stay competitive in the ever-evolving travel industry.

Our travel datasets provide extensive, structured data covering various aspects of the global travel and hospitality industry. These datasets are ideal for businesses, analysts, and developers looking to gain insights into hotel pricing, short-term rentals, restaurant listings, and travel trends. Whether you're optimizing pricing strategies, analyzing market trends, or enhancing travel-related applications, our datasets offer the depth and accuracy you need.

Key Travel Datasets Available:

  Hotel & Rental Listings: Access detailed data on hotel properties, short-term rentals, and vacation stays from platforms like 
    Airbnb, Booking.com, and other OTAs. This includes property details, pricing, availability, guest reviews, and amenities.

  Real-Time & Historical Pricing Data: Track hotel room pricing, rental occupancy rates, and pricing trends 
    to optimize revenue management and competitive analysis.

  Restaurant Listings & Reviews: Explore restaurant data from Tripadvisor, OpenTable, Zomato, Deliveroo, and Talabat, 
    including restaurant details, customer ratings, menus, and delivery availability.

  Market & Trend Analysis: Use structured datasets to analyze travel demand, seasonal trends, and consumer preferences 
    across different regions.

  Geo-Targeted Data: Get location-specific insights with city, state, and country-level segmentation, 
    allowing for precise market research and localized business strategies.



Use Cases for Travel Datasets:

  Dynamic Pricing & Revenue Optimization: Adjust pricing strategies based on real-time market trends and competitor analysis.
  Market Research & Competitive Intelligence: Identify emerging travel trends, monitor competitor performance, and assess market demand.
  Travel & Hospitality App Development: Enhance travel platforms with accurate, up-to-date data on hotels, restaurants, and rental properties.
  Investment & Financial Analysis: Evaluate travel industry performance for investment decisions and economic forecasting.



  Our travel datasets are available in multiple formats (JSON, CSV, Excel) and can be delivered via 
  API, cloud storage (AWS, Google Cloud, Azure), or direct download. 
  Stay ahead in the travel industry with high-quality, structured data that powers smarter decisions.

1) Data Introduction • The TripAdvisor Hotels Dataset is a travel and lodging analysis dataset that collects information about hotels around the world in a tabular format, including locations, ratings, number of reviews, price points, amenities, room types, and user reviews.

2) Data Utilization (1) TripAdvisor Hotels Dataset has characteristics that: • Each row contains a variety of attributes needed to choose and evaluate accommodation, including hotel name, address (including latitude and longitude), rating, number of reviews, price range, room and amenities information, user reviews, language, and nearby attractions. • Data is available in various formats such as JSON and CSV, and includes detailed reviews, rating distribution, and service details (clean, location, service, etc.) by hotel for multi-faceted analysis. (2) TripAdvisor Hotels Dataset can be used to: • Analysis of hotel ratings and reviews: Various information such as ratings, review texts, amenities, etc. can be used to assess hotel service quality, analyze user satisfaction, and calculate popular hotel rankings. • Traveler's Customized Recommendation and Marketing Strategy: Based on data such as location, price, and review pattern, it can be applied to developing a customized hotel recommendation system, establishing a regional marketing strategy, and analyzing competitors.

No. of Hotel Room: Tourist Center: Tuxtla Gutiérrez data was reported at 29,317.000 Unit in 31 Mar 2024. This records an increase from the previous number of 29,301.000 Unit for 24 Mar 2024. No. of Hotel Room: Tourist Center: Tuxtla Gutiérrez data is updated weekly, averaging 24,465.000 Unit from May 2003 (Median) to 31 Mar 2024, with 1076 observations. The data reached an all-time high of 31,346.000 Unit in 31 May 2020 and a record low of 15,126.000 Unit in 06 Jul 2003. No. of Hotel Room: Tourist Center: Tuxtla Gutiérrez data remains active status in CEIC and is reported by Secretary of Tourism. The data is categorized under Global Database’s Mexico – Table MX.Q019: Number of Hotel Room: by Tourist Center. [COVID-19-IMPACT]

No. of Hotel Room: Tourist Center: Valladolid data was reported at 7,706.000 Unit in 28 Apr 2024. This records an increase from the previous number of 7,676.000 Unit for 21 Apr 2024. No. of Hotel Room: Tourist Center: Valladolid data is updated weekly, averaging 4,585.000 Unit from Jan 2005 (Median) to 28 Apr 2024, with 961 observations. The data reached an all-time high of 7,902.000 Unit in 03 Dec 2023 and a record low of 3,250.000 Unit in 28 Oct 2007. No. of Hotel Room: Tourist Center: Valladolid data remains active status in CEIC and is reported by Secretary of Tourism. The data is categorized under Global Database’s Mexico – Table MX.Q019: Number of Hotel Room: by Tourist Center. [COVID-19-IMPACT]

India Number of Hotels Rooms: Above Five Star data was reported at 34,444.000 Unit in 2017. This records an increase from the previous number of 31,037.000 Unit for 2016. India Number of Hotels Rooms: Above Five Star data is updated yearly, averaging 19,309.500 Unit from Dec 1997 (Median) to 2017, with 20 observations. The data reached an all-time high of 34,444.000 Unit in 2017 and a record low of 10,864.000 Unit in 1997. India Number of Hotels Rooms: Above Five Star data remains active status in CEIC and is reported by Ministry of Tourism. The data is categorized under Global Database’s India – Table IN.QG004: Memo Items: Number of Hotels and Hotel Rooms.

No. of Hotel Room: Tourist Center: Culiacan data was reported at 12,033.000 Unit in 31 Mar 2024. This stayed constant from the previous number of 12,033.000 Unit for 24 Mar 2024. No. of Hotel Room: Tourist Center: Culiacan data is updated weekly, averaging 16,709.000 Unit from Jan 2006 (Median) to 31 Mar 2024, with 952 observations. The data reached an all-time high of 19,915.000 Unit in 28 Nov 2021 and a record low of 12,033.000 Unit in 31 Mar 2024. No. of Hotel Room: Tourist Center: Culiacan data remains active status in CEIC and is reported by Secretary of Tourism. The data is categorized under Global Database’s Mexico – Table MX.Q019: Number of Hotel Room: by Tourist Center. [COVID-19-IMPACT]

No. of Hotel Room: Tourist Center: San Felipe data was reported at 5,789.000 Unit in 31 Mar 2024. This stayed constant from the previous number of 5,789.000 Unit for 24 Mar 2024. No. of Hotel Room: Tourist Center: San Felipe data is updated weekly, averaging 4,673.000 Unit from Jan 2008 (Median) to 31 Mar 2024, with 826 observations. The data reached an all-time high of 6,251.000 Unit in 30 Jun 2019 and a record low of 2,506.000 Unit in 03 Jan 2016. No. of Hotel Room: Tourist Center: San Felipe data remains active status in CEIC and is reported by Secretary of Tourism. The data is categorized under Global Database’s Mexico – Table MX.Q019: Number of Hotel Room: by Tourist Center. [COVID-19-IMPACT]

Macau Number of Hotel Beds: Hotels data was reported at 101,400.000 Unit in Oct 2018. This records a decrease from the previous number of 101,657.000 Unit for Sep 2018. Macau Number of Hotel Beds: Hotels data is updated monthly, averaging 36,459.000 Unit from Jan 1998 (Median) to Oct 2018, with 250 observations. The data reached an all-time high of 101,657.000 Unit in Sep 2018 and a record low of 16,926.000 Unit in Jun 2001. Macau Number of Hotel Beds: Hotels data remains active status in CEIC and is reported by Statistics and Census Service. The data is categorized under Global Database’s Macau SAR – Table MO.Q014: Number of Hotels, Hotel Rooms and Hotel Beds.

Mexico No. of Hotel Room: Tourist Center: Puerto Vallarta data was reported at 93,835.000 Unit in 31 Mar 2024. This records an increase from the previous number of 93,834.000 Unit for 24 Mar 2024. Mexico No. of Hotel Room: Tourist Center: Puerto Vallarta data is updated weekly, averaging 82,847.000 Unit from May 2003 (Median) to 31 Mar 2024, with 1070 observations. The data reached an all-time high of 93,835.000 Unit in 31 Mar 2024 and a record low of 69,776.000 Unit in 26 Dec 2010. Mexico No. of Hotel Room: Tourist Center: Puerto Vallarta data remains active status in CEIC and is reported by Secretary of Tourism. The data is categorized under Global Database’s Mexico – Table MX.Q019: Number of Hotel Room: by Tourist Center. [COVID-19-IMPACT]

Uzbekistan Number of Hotel Rooms data was reported at 39,833.000 Unit in 2017. This records an increase from the previous number of 37,795.000 Unit for 2016. Uzbekistan Number of Hotel Rooms data is updated yearly, averaging 25,526.000 Unit from Dec 2005 (Median) to 2017, with 13 observations. The data reached an all-time high of 39,833.000 Unit in 2017 and a record low of 16,284.000 Unit in 2008. Uzbekistan Number of Hotel Rooms data remains active status in CEIC and is reported by State Committee of the Republic of Uzbekistan on Statistics. The data is categorized under Global Database’s Uzbekistan – Table UZ.Q002: Accommodations Statistics.

Hong Kong SAR (China) Number of Hotel Rooms: Total data was reported at 103,690.000 Unit in Mar 2025. This records a decrease from the previous number of 103,724.000 Unit for Feb 2025. Hong Kong SAR (China) Number of Hotel Rooms: Total data is updated monthly, averaging 76,627.000 Unit from Jan 2002 (Median) to Mar 2025, with 279 observations. The data reached an all-time high of 1,003,798.000 Unit in Nov 2024 and a record low of 41,829.000 Unit in Mar 2002. Hong Kong SAR (China) Number of Hotel Rooms: Total data remains active status in CEIC and is reported by Hong Kong Tourism Board. The data is categorized under Global Database’s Hong Kong SAR (China) – Table HK.Q035: Hotel Statistics: Number of Hotel Rooms. Starting from January 2014, this series includes the categories of High Tariff A & B, Medium Tariff, Unclassified and Guesthouses. Prior to 2014, this series includes the category of Tourist Guesthouses (Series ID: 18246001) in place of Guesthouses.

Macau SAR (China) Number of Hotel Rooms data was reported at 43,914.000 Unit in Mar 2025. This records an increase from the previous number of 43,815.000 Unit for Feb 2025. Macau SAR (China) Number of Hotel Rooms data is updated monthly, averaging 22,123.000 Unit from Jan 1998 (Median) to Mar 2025, with 327 observations. The data reached an all-time high of 46,946.000 Unit in Apr 2024 and a record low of 8,650.000 Unit in Jun 2001. Macau SAR (China) Number of Hotel Rooms data remains active status in CEIC and is reported by Statistics and Census Service. The data is categorized under Global Database’s Macau SAR (China) – Table MO.Q015: Number of Hotels, Hotel Rooms and Hotel Beds.

Panama Number of Hotel Rooms data was reported at 0.000 Unit in Dec 2023. This stayed constant from the previous number of 0.000 Unit for Nov 2023. Panama Number of Hotel Rooms data is updated monthly, averaging 5,764.000 Unit from Jan 2000 (Median) to Dec 2023, with 288 observations. The data reached an all-time high of 10,501.000 Unit in Jul 2015 and a record low of 0.000 Unit in Dec 2023. Panama Number of Hotel Rooms data remains active status in CEIC and is reported by National Institute of Statistics and Census. The data is categorized under Global Database’s Panama – Table PA.Q004: Hotel Statistics.

China Number of Hotel Rooms: Total data was reported at 1,067,203.000 Unit in 2023. This records a decrease from the previous number of 1,114,141.000 Unit for 2022. China Number of Hotel Rooms: Total data is updated yearly, averaging 1,365,170.000 Unit from Dec 1999 (Median) to 2023, with 25 observations. The data reached an all-time high of 1,709,966.000 Unit in 2010 and a record low of 524,894.000 Unit in 1999. China Number of Hotel Rooms: Total data remains active status in CEIC and is reported by Ministry of Culture and Tourism. The data is categorized under Global Database’s China – Table CN.QHA: Star-Rated Hotel Operation.