This Hotel Dataset: Rates, Reviews & Amenities(6k+) dataset includes hotel rates, guest reviews, and available amenities from two popular travel websites, TripAdvisor and Booking.com. The dataset can be used to analyze trends and insights in the hospitality industry, and inform decisions related to pricing, marketing, and customer service. Booking.com: Founded in 1996 in Amsterdam, Booking.com has grown from a small Dutch start-up to one of the world’s leading digital travel companies. Part of Booking Holdings Inc. (NASDAQ: BKNG), Booking.com’s mission is to make it easier for everyone to experience the world.

By investing in technology that takes the friction out of travel, Booking.com seamlessly connects millions of travelers to memorable experiences, a variety of transportation options, and incredible places to stay – from homes to hotels, and much more. As one of the world’s largest travel marketplaces for both established brands and entrepreneurs of all sizes, Booking.com enables properties around the world to reach a global audience and grow their businesses.

Booking.com is available in 43 languages and offers more than 28 million reported accommodation listings, including over 6.6 million homes, apartments, and other unique places to stay. Wherever you want to go and whatever you want to do, Booking.com makes it easy and supports you with 24/7 customer support. Tripadvisor, the world's largest travel guidance platform*, helps hundreds of millions of people each month** become better travelers, from planning to booking to taking a trip. Travelers across the globe use the Tripadvisor site and app to discover where to stay, what to do and where to eat based on guidance from those who have been there before. With more than 1 billion reviews and opinions of nearly 8 million businesses, travelers turn to Tripadvisor to find deals on accommodations, book experiences, reserve tables at delicious restaurants and discover great places nearby. As a travel guidance company available in 43 markets and 22 languages, Tripadvisor makes planning easy no matter the trip type. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), own and operate a portfolio of travel media brands and businesses, operating under various websites and apps.

The Global Hotel Data dataset is an extensive collection of data providing insights into the hotel industry worldwide. This dataset encompasses diverse information, including hotel profiles, room types, amenities, pricing, occupancy rates, and guest reviews. With a size of 500k lines, the Global Hotel Data offers valuable information for hotel chains, independent hotels, travel agencies, and researchers to understand market trends, optimize pricing strategies, and enhance guest experiences globally.

Features:

1. Hotel Profiles: Data on hotel properties, including location, star ratings, facilities, and contact information, enabling analysis of hotel distribution and market positioning.
2. Room Types: Information about room categories, room sizes, bed configurations, and amenities, allowing travelers to compare room options and make informed booking decisions.
3. Amenities: Details about hotel amenities and services, such as Wi-Fi availability, parking facilities, swimming pools, and restaurants, facilitating guest preferences and satisfaction assessments.
4. Pricing: Metrics such as room rates, seasonal pricing variations, and promotional offers, enabling hoteliers and revenue managers to optimize pricing strategies and maximize revenue.
5. Occupancy Rates: Data on room occupancy rates, demand patterns, and booking lead times, allowing hoteliers to forecast demand, manage inventory, and allocate resources effectively.
6. Guest Reviews: Ratings and feedback from guests regarding their stay experience, including cleanliness, staff friendliness, and overall satisfaction, providing insights into hotel reputation and service quality.
7. Size: The dataset comprises 500 thousand lines of data.

Potential Applications:

1. Competitive Analysis: Hotel chains can analyze competitor profiles, pricing strategies, and guest reviews to benchmark their performance and identify areas for improvement and differentiation.
2. Revenue Optimization: Revenue managers can use the dataset to monitor demand trends, adjust pricing strategies dynamically, and maximize revenue through strategic pricing and distribution decisions.
3. Guest Experience Enhancement: Hoteliers can leverage guest feedback and reviews to identify service gaps, address guest concerns, and enhance overall guest satisfaction and loyalty.
4. Market Research: Travel agencies and researchers can analyze hotel data to understand market trends, traveler preferences, and destination popularity, informing product development and marketing strategies.

Usage Considerations:

1. Data Privacy: Protect guest privacy and personal information in compliance with data protection regulations, ensuring secure handling and storage of sensitive guest data while analyzing and sharing hotel data.
2. Data Quality: Validate the accuracy and reliability of hotel data sources and performance metrics to ensure data integrity and reliability for decision-making and analysis.
3. Ethical Use: Use hotel data ethically and responsibly, respecting guest consent and preferences regarding data collection, usage, and sharing in hotel analytics and research.

Disclaimer:

While the Global Hotel Data dataset provides valuable insights into the hotel industry and guest preferences, users are reminded to use the data responsibly and ethically. Hotel data analytics should be interpreted with caution, considering factors such as data biases, seasonal variations, and market dynamics, and any actions taken based on the dataset should prioritize guest satisfaction, data privacy, and regulatory compliance.

It's a sample from 515K Hotel Reviews Data in Europe this link with encoded the Reviewer score column to be three classes which contain (High_Reviewer_Score, Intermediate_Reviewer_Score and Low_Reviewer_Score ). It contain 290k of records instead of 515k.

Data Content The csv file contains 17 fields. The description of each field is as below:

Hotel_Address: Address of hotel. Review_Date: Date when reviewer posted the corresponding review. Average_Score: Average Score of the hotel, calculated based on the latest comment in the last year. Hotel_Name: Name of Hotel Reviewer_Nationality: Nationality of Reviewer Negative_Review: Negative Review the reviewer gave to the hotel. If the reviewer does not give the negative review, then it should be: 'No Negative' Review_Total_Negative_Word_Counts: Total number of words in the negative review. Positive_Review: Positive Review the reviewer gave to the hotel. If the reviewer does not give the negative review, then it should be: 'No Positive' Review_Total_Positive_Word_Counts: Total number of words in the positive review. Reviewer_Score: Score the reviewer has given to the hotel, based on his/her experience Total_Number_of_Reviews_Reviewer_Has_Given: Number of Reviews the reviewers has given in the past. Total_Number_of_Reviews: Total number of valid reviews the hotel has. Tags: Tags reviewer gave the hotel. days_since_review: Duration between the review date and scrape date. Additional_Number_of_Scoring: There are also some guests who just made a scoring on the service rather than a review. This number indicates how many valid scores without review in there. lat: Latitude of the hotel lng: longtitude of the hotel

Analysis of ‘Hotel Prices - Beginner Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/sveneschlbeck/hotel-prices-beginner-dataset on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

This dataset addresses Data Science students and/or Beginners who want to dive into Regression or Clustering without the need to pre-clean the data first.

Content

This dataset consists of a pre-cleaned .csv table that has been translated from German to English.

There are four columns in this dataset:

• Profit (How much money does this hotel make in a year)
• Price in Millions (€)
• Square Meter (Hotel Area)
• City

Here, "Hotel Prices" does not refer to the cost of spending a night at those hotels but the price for buying them. This would be an interesting chart for someone who wants to buy a hotel and needs to judge whether he/she is overpaying or getting a great deal depending on similar objects in other comparable cities.

--- Original source retains full ownership of the source dataset ---

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.

No of Hotel Rooms: MF: Hauts-de-France data was reported at 818.000 Unit th in Feb 2025. This records a decrease from the previous number of 866.000 Unit th for Jan 2025. No of Hotel Rooms: MF: Hauts-de-France data is updated monthly, averaging 869.500 Unit th from Jan 2011 (Median) to Feb 2025, with 170 observations. The data reached an all-time high of 937.000 Unit th in May 2023 and a record low of 223.000 Unit th in Apr 2020. No of Hotel Rooms: MF: Hauts-de-France 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: 5 Stars: Region: Normandy data was reported at 888.000 Unit in 2016. No of Hotel Rooms: 5 Stars: Region: Normandy data is updated yearly, averaging 888.000 Unit from Dec 2016 (Median) to 2016, with 1 observations. No of Hotel Rooms: 5 Stars: Region: Normandy data remains active status in CEIC and is reported by Directorate General for Enterprise. The data is categorized under Global Database’s France – Table FR.Q006: Hotels Statistics: Number of Hotel Rooms.

No of Hotel Rooms: 4 Stars: Region: Corsica data was reported at 1,595.000 Unit in 2016. This records an increase from the previous number of 1,533.000 Unit for 2015. No of Hotel Rooms: 4 Stars: Region: Corsica data is updated yearly, averaging 1,393.000 Unit from Dec 2012 (Median) to 2016, with 5 observations. The data reached an all-time high of 1,595.000 Unit in 2016 and a record low of 1,284.000 Unit in 2012. No of Hotel Rooms: 4 Stars: Region: Corsica data remains active status in CEIC and is reported by Directorate General for Enterprise. The data is categorized under Global Database’s France – Table FR.Q006: Hotels Statistics: Number of Hotel Rooms.

Analysis of ‘Saudi Arabia Booking.com’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/moayadmagadmi/saudi-arabia-bookingcom on 14 February 2022.

--- Dataset description provided by original source is as follows ---

Context

In this dataset, I implemented web-scrapping (selenium technique) to create a dataset from Booking.com. it is about data of 1025 hotels in Saudi Arabian in specific date 24Apr 2020. As you know travel plans and hotels price may be affected by Coronavirus (COVID-19). for that, I just choose a randomly day just to collect data without considering room price.

Content

This dataset contains the most hotels in the KSA collected from the most common booking website in the world Booking.com. you will get an overview of each hotel, resort, or accommodation by the 21 features that provided in the dataset explained bellow.

Result

By analysising the dataset, we will know the best and the worst cities in Saudi Arabia in hotels services. will know the most common hotels and its reviews as well. That will help when you decide for traveling plan, or to help to enhance the hotels services in the worst cities.

--- Original source retains full ownership of the source dataset ---

Jordan Number of Classified Hotels data was reported at 290.000 Unit in 2022. This records a decrease from the previous number of 294.000 Unit for 2021. Jordan Number of Classified Hotels data is updated yearly, averaging 247.000 Unit from Dec 1998 (Median) to 2022, with 25 observations. The data reached an all-time high of 322.000 Unit in 2004 and a record low of 197.000 Unit in 2007. Jordan Number of Classified Hotels data remains active status in CEIC and is reported by Ministry of Tourism and Antiquities. The data is categorized under Global Database’s Jordan – Table JO.Q013: Tourist Accommodation Establishments Statistics.

Success.ai’s B2B Contact Data for Global Hospitality Executives provides access to verified contact information for decision-makers shaping the hotel and hospitality industry worldwide. Sourced from over 170 million verified professional profiles, this dataset includes work emails, direct phone numbers, and LinkedIn profiles for key executives and leaders in hotels, resorts, and hospitality groups. Whether you’re targeting hotel owners, general managers, revenue directors, or operations executives, Success.ai delivers accurate, relevant, and timely data to enhance your outreach and drive business growth.

Why Choose Success.ai’s Hospitality Executives Data?

1. Comprehensive Contact Information
2. Access verified work emails, phone numbers, and LinkedIn profiles of hospitality executives worldwide.

3. AI-driven validation ensures 99% accuracy, enabling confident and efficient communication with the right individuals.

4. Global Reach Across Hospitality Segments

5. Includes profiles of hotel owners, general managers, sales directors, revenue managers, and operations leaders in hotels, resorts, and hospitality chains.

6. Covers North America, Europe, Asia-Pacific, South America, and the Middle East, ensuring a truly global perspective.

7. Continuously Updated Datasets

8. Real-time updates keep your data fresh and actionable, allowing you to engage with the most current decision-makers in the hospitality industry.

9. Ethical and Compliant

10. Adheres to GDPR, CCPA, and other global data privacy regulations, ensuring that all outreach efforts are ethical and legally compliant.

Data Highlights:

• 170M+ Verified Professional Profiles: Includes hospitality executives and decision-makers across diverse markets.
• 50M Work Emails: AI-validated for precise, reliable outreach.
• 30M Company Profiles: Offering insights into hotel groups, hospitality brands, and independent properties.
• 700M Global Professional Profiles: Enriched data supporting a broad range of strategic initiatives.

Key Features of the Dataset:

1. Hospitality Decision-Maker Profiles
2. Identify and connect with CEOs, general managers, sales directors, and revenue managers responsible for key operational and strategic decisions in hotels and related hospitality businesses.

3. Engage with individuals who shape guest experiences, manage pricing strategies, oversee supply chains, and direct marketing efforts.

4. Advanced Filters for Precision Targeting

5. Filter contacts by region, hotel brand, property size, star rating, job title, and other criteria to tailor your outreach for maximum relevance and impact.

6. Refine campaigns to target decision-makers aligned with your product or service offerings.

7. AI-Driven Enrichment

8. Profiles are enriched with actionable data points, giving you the insights needed to personalize messaging and boost engagement rates.

Strategic Use Cases:

1. Sales and Vendor Relationships
2. Present technology solutions, guest amenities, or operational improvements to hotel owners, procurement managers, or operations leaders.

3. Build partnerships with hospitality executives seeking quality suppliers and innovative offerings.

4. Marketing and Brand Expansion

5. Target marketing and revenue directors to promote your services—such as branding, digital marketing tools, or loyalty programs—across hotel portfolios.

6. Engage with decision-makers who can influence brand positioning and campaign investments.

7. Investment and Development Opportunities

8. Connect with hospitality executives exploring renovations, expansions, or new property launches.

9. Identify strategic partners for joint ventures or acquisitions within the hospitality sector.

10. Recruitment and Talent Acquisition

11. Reach HR professionals or general managers looking to staff hotels with high-quality personnel.

12. Offer recruitment solutions, training programs, or staffing services directly to key decision-makers.

Why Choose Success.ai?

1. Best Price Guarantee

2. Access top-quality verified data at competitive prices, ensuring you maximize ROI on your outreach efforts.

3. Seamless Integration

4. Integrate verified contact data into your CRM or marketing automation platforms via APIs or downloadable formats for effortless data management.

5. Data Accuracy with AI Validation

6. Trust in 99% accuracy for confident targeting, optimized conversions, and enhanced relationship-building in the hospitality sector.

7. Customizable and Scalable Solutions

8. Tailor datasets to focus on specific regions, hospitality segments, or job functions, adapting as your business goals evolve.

APIs for Enhanced Functionality:

1. Data Enrichment API

2. Enrich existing CRM records with verified hospitality contact data to sharpen targeting and personalization.

3. Lead Generation API

4. Automate lead generation, streamlining your outreach and enabling efficient scalin...

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.

Spain Number of Hotels data was reported at 12,133.000 Unit in Feb 2025. This records an increase from the previous number of 11,362.000 Unit for Jan 2025. Spain Number of Hotels data is updated monthly, averaging 14,545.000 Unit from Jan 1999 (Median) to Feb 2025, with 314 observations. The data reached an all-time high of 17,116.000 Unit in Jul 2019 and a record low of 0.000 Unit in Apr 2020. Spain Number of Hotels data remains active status in CEIC and is reported by National Statistics Institute. The data is categorized under Global Database’s Spain – Table ES.Q021: Hotel Statistics.

No of Hotel Rooms: Overseas Departments (DOM) data was reported at 323.000 Unit th in Feb 2025. This records a decrease from the previous number of 346.300 Unit th for Jan 2025. No of Hotel Rooms: Overseas Departments (DOM) data is updated monthly, averaging 324.000 Unit th from Jan 2011 (Median) to Feb 2025, with 169 observations. The data reached an all-time high of 372.300 Unit th in Jan 2020 and a record low of 82.300 Unit th in Apr 2020. No of Hotel Rooms: Overseas Departments (DOM) 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: 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: 4 Stars: Region: Center-Val de Loire data was reported at 2,703.000 Unit in 2016. This records an increase from the previous number of 2,636.000 Unit for 2015. No of Hotel Rooms: 4 Stars: Region: Center-Val de Loire data is updated yearly, averaging 2,636.000 Unit from Dec 2012 (Median) to 2016, with 5 observations. The data reached an all-time high of 2,703.000 Unit in 2016 and a record low of 2,565.000 Unit in 2014. No of Hotel Rooms: 4 Stars: Region: Center-Val de Loire data remains active status in CEIC and is reported by Directorate General for Enterprise. The data is categorized under Global Database’s France – Table FR.Q006: Hotels Statistics: Number of Hotel Rooms.

No. of Hotel Room: Tourist Center: Uxmal data was reported at 1,624.000 Unit in 28 Apr 2024. This stayed constant from the previous number of 1,624.000 Unit for 21 Apr 2024. No. of Hotel Room: Tourist Center: Uxmal data is updated weekly, averaging 1,365.000 Unit from Jan 2006 (Median) to 28 Apr 2024, with 912 observations. The data reached an all-time high of 1,666.000 Unit in 21 May 2023 and a record low of 600.000 Unit in 25 Apr 2010. No. of Hotel Room: Tourist Center: Uxmal 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]

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.

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.

No. of Hotel Room: Tourist Center: Palenque data was reported at 14,511.000 Unit in 28 Apr 2024. This stayed constant from the previous number of 14,511.000 Unit for 21 Apr 2024. No. of Hotel Room: Tourist Center: Palenque data is updated weekly, averaging 14,703.000 Unit from Jan 2005 (Median) to 28 Apr 2024, with 965 observations. The data reached an all-time high of 16,454.000 Unit in 29 Jun 2014 and a record low of 13,365.000 Unit in 15 Jul 2007. No. of Hotel Room: Tourist Center: Palenque 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]