The change in monthly hotel bookings in October 2023 compared to 2019 was minus four percent. This follows an annual trend where a decline in bookings is seen in October at the start of winter.

The year-over-year monthly change in the number of hotel bookings worldwide dropped to -66 percent in April 2020. The sharp change in hotel bookings was due to the impact of the coronavirus (COVID-19) pandemic on international travel and the hotel industry. Three years later, in April 2023, the monthly change in the number of hotel bookings was 99 percent.

We will create a customized hotel bookings dataset tailored to your specific requirements. Data points may include hotel names, location details, pricing information, amenity lists, guest ratings, occupancy rates, and other relevant metrics.

Utilize our hotels bookings datasets for a variety of applications to boost strategic planning and market analysis. Analyzing these datasets can help organizations understand guest preferences and market trends within the hospitality industry, allowing for more precise operational adjustments and marketing strategies. You can choose to access the complete dataset or a customized subset based on your business needs.

Popular use cases include: optimizing booking strategies, enhancing guest experience, and competitive benchmarking.

This statistic shows the distribution of hotel room nights booked in the United States by channel in the third quarter of 2016. In this period, 21.6 percent of hotel bookings were made through an online travel agent or an OTA.

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.

These data sets contain the information on 6050 hotel bookings between in the year of 2024. Each observation represents a hotel booking. The dataset contains 6,050 hotel transactions with 36 columns, covering various aspects of hotel bookings, customer details, sales performance, and financial metrics.

The Key Features included: Hotel Information: Hotel Name, Region, State, Hotel Type Customer Details: Customer Name, Phone Number, Email, Repeated Guest, Previous Cancellations Booking Information: Reservation Status, Check-in & Check-out Dates, Number of Guests (Adults/Children), Room Type, Duration (Nights) Financial Data: Price Per Room, Gross Sales, Discounts, Net Sales, Payment Method, Deposit Amount & Status, Commission Customer Feedback: Customer Rating, Customer Review Sales Performance: Sales Person, Position

The Report Covers Global Online Hotel Booking Industry Trends and is Segmented by Platform (Mobile Application, Website), Mode of Booking (Third-party online portals, Direct/captive portals), Geographical Region (North America, Asia Pacific, Europe, Latin America, Middle East, and Africa).

This statistic shows the results of a survey conducted in the United States in January 2017. U.S. adults who would like to go on a spring vacation were asked which channel they prefer to use when booking a hotel for a vacation. During the survey, 88 percent of the respondents said they prefer using an online channel to book a hotel.

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.

Dataset

This dataset was created by sssakibbb

Contents

Context

PromptCloud and DataStock extracted this data from Booking.com to find out the rates and prices and states hotels were available for the period of 1 year from December 2018 to December 2019. This is a sample dataset of 30K records.

You can download the full dataset here

Content

This dataset was procured to give knowledge about the various hotels that are present on Booking.com. This dataset will be helpful for the researchers and students who want these type of specific datasets that can be used for various case studies and projects based on different hotels across the globe that is available on booking.com

The Data Fields That This File Contain Are: Root Folders 456 Root Folders Each Root Folder Contains - Uniq_ID - Hotel_ID - Hotel_Name - Review_Count - Default_Rank - Price_Rank - OTA

Acknowledgements

This dataset was created by PromptCloud's In-House Data Crawling Team

Inspiration

We want users to use clean and raw data which will help them gain access to knowledge about different sites and help them in their various projects or research that they might conduct. We want our customers to feel that they can depend on datasets like this from us and that is what drives us. Customer satisfaction is our main priority and we only wish the best for them and they keep us going.### Context

PromptCloud and DataStock extracted this data from Booking.com to find out the rates and prices and states hotels were available for the time period of 1 year from December 2018 to December 2019. This is a sample dataset of 30K records.

You can download the full dataset here

Content

This dataset was procured to give knowledge about the various hotels that are present on Booking.com. This dataset will be helpful for the researchers and students who want these type of specific datasets that can be used for various case studies and projects based on different hotels across the globe that is available on booking.com

The Data Fields That This File Contain Are: Root Folders 456 Root Folders Each Root Folder Contains - Uniq_ID - Hotel_ID - Hotel_Name - Review_Count - Default_Rank - Price_Rank - OTA

Acknowledgements

This dataset was created by PromptCloud's In-House Data Crawling Team

Inspiration

We want users to use clean and raw data which will help them gain access to knowledge about different sites and help them in their various projects or research that they might conduct. We want our customers to feel that they can depend on datasets like this from us and that is what drives us. Customer satisfaction is our main priority and we only wish the best for them and they keep us going.

Dataset

This dataset was created by SUNEEL KUMAR PATEL

Contents

The market size of the hotel and resort sector worldwide peaked at 1.5 trillion U.S. dollars in 2023. This showed five percent growth over the previous year's figure of 1.43 trillion U.S. dollars. What are the leading hotel brands globally? In 2023, among hotel brands with the highest brand values globally were industry giants like Hilton, Hyatt, and Hampton Inn. Hilton was reported to have a brand value exceeding 11 billion U.S. dollars. However, while Hilton led brand value, Wyndham hotels and resorts claimed the top spot for the hotel company with the largest number of properties worldwide, boasting over nine thousand hotels globally, while Hilton ranked fourth. Hotel booking behavior of global travelers In 2023, hotel booking growth worldwide peaked in January and February, surpassing 130 percent - there was also a notable increase in hotel booking growth during the summer months of June and August. As of 2024, Vietnam and China stood out as the countries with the highest share of consumers booking hotels or private accommodation. Meanwhile, countries with the lowest share of hotel and private accommodation bookings were Hungary and Pakistan.

Dataset

This dataset was created by Atul Pachauri

Contents

This statistic shows the share of gross hotel booking revenue coming from bookings made through online travel agencies (OTAs) in Europe between 2012 and 2016. In 2014 online travel agencies accounted for almost 20 percent of gross hotel bookings.

The Report Covers Global Luxury Hotel Market Share and is Segmented by Type (Business Hotels, Airport Hotels, Suite Hotels, Resorts, and Other Hotels) and by Geography (North America, Europe, Asia-Pacific, South America, and Middle-East and Africa).

Dataset

This dataset was created by AMRI Yasmina

Released under Apache 2.0

Contents

The year-over-year monthly change in the number of hotel bookings worldwide decreased across all regions during March and April 2020. The most extreme decline in number of hotel bookings was seen in Africa in April 2020, at -94 percent. The sharp decrease in hotel searches was due to the impact of the coronavirus (COVID-19) pandemic on international travel and the hotel industry.

Hotel Reservation Software Market Size And Forecast

Hotel Reservation Software Market size is growing at a faster pace with substantial growth rates over the last few years and is estimated that the market will grow significantly in the forecasted period i.e. 2024 to 2031.

Global Hotel Reservation Software Market Drivers

The market drivers for the Hotel Reservation Software Market can be influenced by various factors. These may include:

Growing Travel and tourist Industry: The demand for hotel reservation software is being driven by the travel and tourist industry’s expansion, which is being fueled by rising disposable incomes, an expanding middle class, and an increasing preference for vacation experiences. Hotels use reservation software to effectively handle bookings as more tourists look for places to stay.

Transition to internet Booking Channels: Because of the ease of use and accessibility provided by internet platforms, there has been a notable transition away from traditional booking techniques and towards online channels. Travellers may make bookings more easily and enjoy a better overall booking experience when hotels are able to interact with websites, mobile applications, and online booking portals thanks to hotel reservation software.

Growing Adoption of Cloud-Based Solutions: When compared to on-premises solutions, cloud-based hotel reservation software offers cost-effectiveness, scalability, and flexibility. The popularity of cloud-based software is fueled by hotels’ preference for it due to its capacity to centralise data, simplify operations, and offer real-time access to reservation information from any location.

Emphasis on Personalisation and the Guest Experience: In order to satisfy guests’ changing needs and expectations, hotels are placing a greater emphasis on personalisation. By including features like guest profiles, preference tracking, and targeted marketing, reservation software with advanced capabilities lets hotels personalise services and offers, ultimately increasing guest happiness and loyalty.

Integration with Property Management Systems (PMS): Hotels can streamline operations, including booking management, check-in/check-out procedures, and room inventory management, by integrating their reservation software and PMS seamlessly. Integration guarantees data consistency, lowers human error rates, and boosts overall productivity.

Emergence of Mobile Booking Trends: Travellers’ methods for making hotel reservations have changed as a result of the widespread use of smartphones and mobile apps. Hotels may take advantage of the expanding mobile booking market and satisfy the needs of technologically aware tourists by using hotel reservation software with booking features and mobile compatibility.

Increasing Focus on Revenue Management: By dynamically modifying room prices in response to changes in demand, industry trends, and rival pricing, revenue management helps hotels maximise their profitability. Hotels can successfully implement pricing plans and maximise income by utilising revenue management solutions integrated into their hotel reservation software.

Demand for Analytics and Business Intelligence: In order to make wise decisions and boost company performance, hoteliers are depending more and more on data-driven insights. With the analytics and business intelligence features that advanced reservation software provides, hotels may monitor performance indicators, examine booking trends, and improve their marketing tactics to get better results.

Requirement for Cost-Reduction and Operational Efficiency: Hotels look for software solutions that can save expenses, simplify operations, and eliminate manual labour in a cutthroat hospitality market. Software for hotel reservations streamlines and lowers costs by automating tasks like reporting, invoicing, and booking administration.

Japan's Online Accommodation Market is segmented By Platform type (Mobile application, Website) and Mode of Booking Type (Third Party online portals, Direct/Captive portals).