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.

The Booking.com Reviews Dataset is a comprehensive collection of user-generated reviews for hotels, hostels, bed & breakfasts, and other accommodations listed on Booking.com. This dataset provides detailed information on customer reviews, including ratings, review text, review dates, customer demographics, and more. It is a valuable resource for analyzing customer sentiment, service quality, and overall guest experiences across different types of accommodations worldwide.

Key Features:

• Review Data: Includes detailed customer reviews with both positive and negative feedback, providing insights into customer experiences and satisfaction levels.
• Ratings: Features individual ratings for various aspects of the accommodations, such as cleanliness, location, service, value for money, and overall satisfaction.
• Review Dates: Provides the dates of each review, enabling trend analysis over time.
• Accommodation Details: Includes information about the accommodations being reviewed, such as name and location.
• Language Support: Reviews are available in multiple languages, reflecting the diverse user base of Booking.com.

Use Cases:

• Sentiment Analysis: Ideal for businesses and researchers conducting sentiment analysis to understand customer opinions and trends in the hospitality industry.
• Market Research: Useful for market research and competitive analysis, identifying strengths and weaknesses of different accommodation types and regions.
• Machine Learning: Beneficial for developing machine learning models for natural language processing, sentiment classification, and recommendation systems.
• Customer Experience Improvement: Helps hotel managers and owners understand customer feedback to improve services and guest experiences.
• Academic Research: Suitable for academic research in hospitality management, consumer behavior, data science, and artificial intelligence.

Dataset Format:

The dataset is available in CSV format making it easy to use for data analysis, machine learning, and application development.

Access 3 million+ US hotel reviews — submit your request today.

Dataset

This dataset was created by Pat Tae

Released under CC BY-SA 4.0

Contents

The number of bookings recorded by Booking Holdings grew by ** percent in 2024 over the previous year. Over the period considered, room nights represented the company's leading business segment, peaking at over *** billion in 2024. That year, bookings of airline tickets reported the highest year-on-year growth, with a ** percent annual increase. How much does Booking Holdings earn? With the increase in total bookings, Booking Holdings' revenue also grew in 2024 over the previous year, peaking at almost ** billion U.S. dollars. Ultimately, Booking Holdings' net income amounted to almost *** billion U.S. dollars in 2024, the highest figure reported by the company to date. What are the most visited travel websites worldwide? In 2025, booking.com, the website of Booking Holdings's flagship brand, was the most visited travel and tourism website worldwide. Tripadvisor.com, the web page of Tripadvisor, Inc.'s leading brand, and airbnb.com followed in the ranking.

36275 unique values Booking_ID no_of_adults no_of_children no_of_weekend_nights no_of_week_nights type_of_meal_plan required_car_parking_space room_type_reserved lead_time arrival_year arrival_month arrival_date market_segment_type repeated_guest no_of_previous_cancellations no_of_previous_bookings_not_canceled avg_price_per_room no_of_special_requests booking_status

mahimtalukder/hotel-booking-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

In July 2025, the number of visits to the travel and tourism website booking.com increased over the previous month, totaling approximately *** million. In 2025, Booking's web page was the most visited travel and tourism website worldwide.

Intro

Booking.com provides a unique dataset based on millions of real anonymized bookings to encourage the research on sequential recommendation problems. Many travelers go on trips which include more than one destination. Our mission at Booking.com is to make it easier for everyone to experience the world, and we can help to do that by providing real-time recommendations for what their next in-trip destination will be. By making accurate predictions, we help deliver a frictionless… See the full description on the dataset page: https://huggingface.co/datasets/Booking-com/multi-destination-trip-dataset.

Many people enjoy traveling. When comparing the people booking hotel or private accomodation in selected countries worldwide, the highest share can be found in Malaysia, where ** percent of consumers fall into this category. Vietnam ranks second with ** percent of respondents being part of this category as well.Statista Consumer Insights offer you all results of our exclusive Statista surveys, based on more than ********* interviews.

Booking

## Overview

Booking is a dataset for object detection tasks - it contains Available annotations for 747 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

Hotel Booking Engine Market Outlook

The global hotel booking engine market size was valued at approximately USD 3.5 billion in 2023 and is expected to grow to USD 7.8 billion by 2032, reflecting a compound annual growth rate (CAGR) of 9.2%. The market's growth is driven by the increasing adoption of digital platforms for travel bookings and the growing preference for online reservations among consumers. The ease of access and the convenience provided by hotel booking engines are key factors contributing to this rapid expansion.

One of the primary growth factors for the hotel booking engine market is the proliferation of internet usage and the widespread adoption of smartphones. As more people gain access to high-speed internet and increasingly rely on their mobile devices for various daily activities, the trend towards online booking has surged. This has prompted hotels and travel agencies to invest in advanced booking engines to streamline their operations and enhance customer experiences. Furthermore, the convenience offered by these platforms, such as instant booking confirmations and secure payment options, has significantly bolstered their popularity.

Another significant driver is the growing emphasis on customer experience and personalization in the hospitality industry. Modern consumers expect a seamless and customized booking experience, which has led to the integration of artificial intelligence (AI) and machine learning (ML) technologies into booking engines. These technologies analyze user behavior and preferences to provide personalized recommendations, thereby improving customer satisfaction and loyalty. Additionally, the incorporation of features like virtual tours and real-time room availability updates further enhances the user experience, driving market growth.

The increasing competition among hotels and the need for a competitive edge have also fueled the adoption of advanced hotel booking engines. Hotels are leveraging these platforms to offer exclusive deals and personalized packages to attract and retain customers. The ability to manage bookings efficiently, optimize pricing strategies, and access valuable customer data for targeted marketing campaigns has made booking engines an indispensable tool for hoteliers. Moreover, the rising trend of direct bookings, which eliminates the need for intermediaries and reduces commission costs, further propels the market's expansion.

From a regional perspective, North America dominates the hotel booking engine market due to its well-established hospitality sector and high internet penetration rates. The presence of major market players and the rapid adoption of advanced technologies in this region also contribute to its leading position. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. The burgeoning middle class, increasing disposable incomes, and the rapid growth of the tourism industry in countries like China and India are key factors driving the market in this region.

Deployment Type Analysis

The hotel booking engine market can be segmented by deployment type into cloud-based and on-premises solutions. Cloud-based booking engines have gained significant traction in recent years due to their flexibility, scalability, and cost-effectiveness. These solutions allow hotels to access their booking systems from anywhere with an internet connection, making it easier to manage reservations and update availability in real-time. Additionally, cloud-based systems often come with lower upfront costs and require less maintenance, which is particularly beneficial for small to medium-sized hotels with limited IT resources.

On the other hand, on-premises booking engines are still preferred by some larger hotel chains and establishments with specific security and customization requirements. These systems are installed directly on the hotel's servers, providing greater control over data and system configurations. While on-premises solutions typically involve higher initial investments and ongoing maintenance costs, they offer enhanced data security and the ability to tailor the system to the hotel's unique needs. This segment continues to hold a significant share of the market, particularly among luxury and high-end hotels that prioritize data privacy and bespoke functionality.

The growing preference for cloud-based solutions is also driven by the increasing adoption of Software-as-a-Service (SaaS) models in the hospitality industry. SaaS-based booking engines offer a subscription-based pricing struct

Hotel Booking Market size was valued at USD 14.63 Billion in 2024 and is projected to reach USD 526.40 Billion by 2031, growing at a CAGR of 15.25% during the forecast period 2024-2031.Global Hotel Booking Market DriversIncreased Travel and Tourism: The demand for unique travel experiences, growing disposable incomes, and the growth of low-cost airlines have all contributed to an increase in both domestic and international travel, which has greatly increased hotel reservations across the globe.Growth of Online Travel Agencies (OTAs): Customers can now compare prices, read reviews, and book hotels online more easily thanks to the rise of OTAs like Booking.com, Expedia, and Airbnb. This ease of use is a key factor in the market's expansion.Mobile and Digital Adoption: The way passengers look for and reserve hotels has changed as a result of the growing usage of smartphones and mobile apps. Market expansion is being driven by consumers' increasing preference for mobile bookings, which is bolstered by user-friendly interfaces and safe payment channels.Personalization and AI Technology: By combining machine learning and artificial intelligence with hotel booking platforms, users can receive tailored recommendations based on their prior actions and preferences, which improves user experience and increases bookings.Growing Business Travel: Major cities and business centers see a large increase in hotel reservations due to the growth of multinational corporations and globalization, which has led to a rise in business travel.Expansion of Hospitality Networks: More reservations have been made due to the availability of more hotel rooms as a result of hotel networks' global expansion and the construction of new facilities in developing nations.Middle-Class Growth and Emerging Markets: As the middle class grows in emerging markets, especially in Asia-Pacific, there is a corresponding surge in travel and hotel reservations.

The global travel and tourism market is one of the worst hit by the coronavirus (COVID-19) pandemic. As a result, companies such as Booking.com are now coping with the virus' damaging effects. In the first week of 2020, there were ***** percent more Booking.com short-term rental reservations than in the previous year. By week two, the company saw this figure rise to ** percent more year-over-year reservations. However, this growth didn't continue and in week ** of 2020, short-term rental bookings on the Booking.com platform saw a ** percent drop over the previous year as a result of the coronavirus pandemic.

Hotel Internet Booking Engine Market Outlook

The global hotel internet booking engine market size was valued at approximately USD 2.5 billion in 2023 and is projected to reach USD 4.8 billion by 2032, growing at a CAGR of 7.5% during the forecast period. A significant growth factor propelling this market is the increasing preference for direct online bookings by consumers, driven by the rapid adoption of digital platforms and mobile applications in the hospitality industry. The market is witnessing robust growth due to technological advancements, which have enhanced the efficiency and user-friendliness of internet booking engines, thus making them a preferred choice for hotels aiming to streamline operations and improve customer experience.

One of the primary growth drivers of the hotel internet booking engine market is the escalating demand for convenience and immediacy in the hotel booking process. With the proliferation of smartphones and improved internet access across the globe, consumers are increasingly leaning towards digital solutions that offer them the flexibility to book accommodations from anywhere and at any time. This shift in consumer behavior has prompted hotels to integrate internet booking engines into their systems to provide seamless and instantaneous booking experiences. Moreover, the ability of these engines to offer personalized services through data-driven insights is further encouraging their adoption among hoteliers seeking to enhance customer satisfaction and loyalty.

Another key factor contributing to the market's expansion is the cost-effectiveness and operational efficiency that internet booking engines offer to hotel operators. By channeling bookings through these engines, hotels can reduce dependency on third-party platforms, which often charge high commission fees, thereby improving their profit margins. Additionally, these engines provide hotels with valuable data analytics that enable better inventory management and pricing strategies, optimizing overall operational performance. As a result, more hotels, including independent establishments and large chains, are investing in advanced booking engine technologies to gain a competitive edge in the market.

The integration of artificial intelligence (AI) and machine learning (ML) technologies into hotel internet booking engines is also acting as a catalyst for market growth. AI and ML are transforming online booking platforms by enabling predictive analytics, enhancing personalization, and offering intelligent recommendations to customers. These technological advancements help hotels anticipate customer preferences and tailor their offerings accordingly, thereby increasing booking rates and customer satisfaction. The continuous evolution of these technologies suggests an ongoing trend towards more sophisticated and intuitive booking solutions, further driving the market forward.

Regionally, the market is witnessing diverse growth trends, with Asia Pacific emerging as a significant growth area due to the rise in tourism and the growing number of internet users. The region's booming middle class, coupled with the expansion of both leisure and business travel, is driving demand for online hotel booking solutions. Similarly, North America and Europe are experiencing steady growth, largely driven by technological advancements and a high concentration of hotel chains that are adopting these engines to enhance their direct booking capabilities. Meanwhile, emerging markets in Latin America and the Middle East & Africa are showing potential for growth, as improvements in digital infrastructure and increasing internet penetration rates open new opportunities for market expansion.

Component Analysis

Within the hotel internet booking engine market, the component segment is bifurcated into software and services. The software component is at the forefront of this market, encompassing the core technology that drives the functionality and efficiency of booking engines. This segment is experiencing growth due to continuous innovations aimed at enhancing user interfaces, integrating payment gateways, and improving security features. The software's capability to manage large volumes of bookings, while providing real-time updates and analytics to hoteliers, makes it an invaluable asset. Consequently, software development is seen as a pivotal area, with companies consistently investing in R&D to offer more robust, flexible, and scalable solutions that meet the evolving needs of the hotel industry.

The services component, comprising installation, maintenance, and support services, i

Homestay Booking Software Market Outlook

The global homestay booking software market size is projected to grow from USD 1.2 billion in 2023 to USD 2.9 billion by 2032, at a CAGR of 10.1% during the forecast period. The growth of this market is driven by the increasing popularity of homestays as an alternative to traditional hotel accommodation, fuelled by the rising demand for personalized travel experiences and the growing use of digital platforms for travel bookings. The proliferation of smartphones and internet penetration has made it easier for travelers to find and book homestays, contributing to market growth.

The growth factors of the homestay booking software market are multifaceted. One of the primary drivers is the shift in consumer preference towards experiencing local culture and living like a local, which has made homestays an attractive alternative to hotels. Travelers are increasingly seeking unique and authentic experiences, and homestays provide just that. This shift is particularly pronounced among millennial and Gen Z travelers, who prioritize experiences over material possessions. The rise of social media influencers and travel bloggers showcasing homestay experiences has further fueled this trend, leading to increased demand for homestay booking software.

Another significant growth factor is the technological advancements in the travel and tourism industry. The integration of artificial intelligence (AI) and machine learning (ML) in homestay booking software has revolutionized the user experience. These technologies enable personalized recommendations, automated booking processes, and enhanced customer service, thereby improving the overall efficiency and satisfaction of both hosts and guests. Additionally, the adoption of secure payment gateways and blockchain technology ensures safe and transparent transactions, building trust among users and driving market growth.

The increasing globalization and ease of international travel have also played a crucial role in the expansion of the homestay booking software market. As more people travel across borders for leisure, work, or education, the demand for diverse accommodation options has surged. Homestays offer a cost-effective and culturally immersive alternative, making them a preferred choice for many travelers. Furthermore, governments in various countries are promoting tourism and encouraging the development of homestay accommodations, providing a conducive environment for the growth of homestay booking software.

Regionally, the homestay booking software market exhibits diverse growth patterns. North America and Europe are significant markets due to their well-established tourism industries and high internet penetration rates. The Asia Pacific region is expected to witness the fastest growth, driven by the increasing number of domestic and international travelers, burgeoning middle-class population, and rapid digitalization. Latin America and the Middle East & Africa are also emerging markets, with growing tourism activities and increasing adoption of digital booking platforms contributing to market growth.

Component Analysis

The homestay booking software market is segmented by components into software and services. The software segment includes platforms that facilitate the listing, searching, booking, and management of homestay properties. This segment is expected to hold the largest market share during the forecast period. The increasing demand for user-friendly and feature-rich booking platforms is driving the growth of this segment. Software solutions offer various functionalities such as property management, reservation systems, customer relationship management (CRM), and analytics, which are essential for the efficient operation of homestay businesses.

The services segment encompasses the various support and maintenance services provided by vendors to ensure the smooth functioning of the software solutions. This segment is anticipated to witness significant growth due to the increasing adoption of homestay booking software. Services include implementation, integration, consultation, and ongoing technical support, which are crucial for optimizing the performance of the software and addressing any issues that may arise. The demand for customization and personalized services tailored to the specific needs of homestay owners and travel agencies is also driving the growth of the services segment.

The integration of advanced technologies such as AI, ML, and big data analytics in homestay booking software is a key trend in the market. These technol

Booking Listings – Free Cancellation 🏨✈️

Booking Listings is a structured snapshot of accommodation offers worldwide as listed on Booking.com. This subset contains only properties that offer free cancellation, enabling analysts and data scientists to study flexible‑booking behaviour, derive pricing strategies, and build recommendation or revenue‑management systems.

Highlights

75 k hotels & apartments across 84 countries Rich pricing & availability metadata (final vs. original… See the full description on the dataset page: https://huggingface.co/datasets/BrightData/Booking.com-Listings.

Traffic analytics, rankings, and competitive metrics for booking.com as of June 2025

A complete list of live websites using the Booking technology, compiled through global website indexing conducted by WebTechSurvey.

The global hotel reservation service market is experiencing robust growth, driven by increasing online travel bookings, the rising popularity of mobile applications for travel planning, and the expanding reach of high-speed internet access globally. The market, estimated at $50 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This substantial growth is fueled by several key trends, including the proliferation of online travel agencies (OTAs) offering competitive pricing and bundled services, the increasing adoption of revenue management systems by hotels to optimize pricing strategies, and the growing preference for personalized travel experiences facilitated by advanced data analytics. The segmentation of the market into hourly room reservations and overnight stays, further categorized by international and domestic hotels, showcases the diversity of user needs and preferences within this dynamic landscape. The competitive landscape is highly fragmented, with major players including Booking Holdings Inc., Expedia Group, and other significant OTAs along with smaller specialized service providers competing to capture market share through technological innovation and strategic partnerships. The geographic distribution of the market shows strong growth across North America and Asia-Pacific regions due to higher internet penetration and a burgeoning middle class. The constraints facing the market include the volatility of travel demand influenced by macroeconomic factors such as economic recessions and global pandemics, as well as intense competition and the increasing costs associated with maintaining sophisticated technology platforms. However, the long-term outlook remains positive, driven by consistent growth in global tourism and the continuous innovation within the travel technology sector. This includes the development of artificial intelligence-powered chatbots for customer service, the implementation of blockchain technology for secure transactions, and the use of virtual and augmented reality for enhancing the online booking experience. These developments are poised to further propel the growth of the hotel reservation service market in the coming years, particularly in emerging markets with rapidly developing digital infrastructures.

In June 2025, the number of visits to the travel and tourism website booking.com totaled roughly *** million. That month, mobiles accounted for the most views, with over *** million visits coming from such devices. Over the period considered, booking.com's visits peaked at nearly *** million in July 2024, with mobile visits reaching *** million that month.