100+ datasets found
  1. Hotels Dataset

    • brightdata.com
    .json, .csv, .xlsx
    Updated May 7, 2024
    + more versions
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    Bright Data (2024). Hotels Dataset [Dataset]. https://brightdata.com/products/datasets/travel/hotels
    Explore at:
    .json, .csv, .xlsxAvailable download formats
    Dataset updated
    May 7, 2024
    Dataset authored and provided by
    Bright Datahttps://brightdata.com/
    License

    https://brightdata.com/licensehttps://brightdata.com/license

    Area covered
    Worldwide
    Description

    We will create a customized hotels 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 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.

  2. P

    Hotel Dataset

    • paperswithcode.com
    Updated Jul 22, 2022
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    Ashkan Farhangi; Arthur Huang; Zhishan Guo (2022). Hotel Dataset [Dataset]. https://paperswithcode.com/dataset/hotel-sales
    Explore at:
    Dataset updated
    Jul 22, 2022
    Authors
    Ashkan Farhangi; Arthur Huang; Zhishan Guo
    Description

    The dataset contains the hotel demand and revenue of 8 major tourist destinations in the US (e.g., Los Angeles, Orlando ...). The dataset contains sales, daily occupancy, demand, and revenue of the upper-middle class hotels.

    We also gathered dynamic exogenous variables such as the state’s closure/open policy to enrich our dataset. Specifically, we gathered numerious static features such as the number of hospitals, GPD, and population.

  3. c

    USA hotels dataset from booking

    • crawlfeeds.com
    csv, zip
    Updated Jun 15, 2025
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    Crawl Feeds (2025). USA hotels dataset from booking [Dataset]. https://crawlfeeds.com/datasets/usa-hotels-dataset-from-booking
    Explore at:
    csv, zipAvailable download formats
    Dataset updated
    Jun 15, 2025
    Dataset authored and provided by
    Crawl Feeds
    License

    https://crawlfeeds.com/privacy_policyhttps://crawlfeeds.com/privacy_policy

    Area covered
    United States
    Description

    The USA Hotels Dataset from Booking.com is a rich collection of data related to hotels across the United States, extracted from Booking.com. This dataset includes essential information about hotel listings, such as hotel names, locations, prices, star ratings, customer reviews, and amenities offered. It's an ideal resource for researchers, data analysts, and businesses looking to explore the hospitality industry, analyze customer preferences, and understand pricing patterns in the U.S. hotel market.

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

    Key Features:

    • Hotel Information: Includes hotel names, addresses, star ratings, and descriptions.
    • Pricing Data: Nightly rates, discounts, and price variations by room type and season.
    • Customer Reviews: Aggregated ratings and detailed user feedback from verified guests.
    • Amenities: Detailed list of amenities provided by each hotel (e.g., Wi-Fi, parking, spa, swimming pool).
    • Geographical Information: Hotel locations including city, state, and proximity to major landmarks.

    Use Cases:

    • Sentiment Analysis: Analyze customer reviews to gauge hotel service quality and guest satisfaction.
    • Price Analysis: Compare pricing across different hotels, locations, and time periods to identify trends.
    • Recommendation Systems: Build recommendation engines based on customer ratings, reviews, and preferences.
    • Tourism and Hospitality Research: Understand patterns in hotel demand and services across various U.S. cities.

  4. o

    Data from: Hotel statistics

    • data.ontario.ca
    web, xlsx
    Updated Jun 27, 2025
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    Heritage, Sport, Tourism and Culture Industries (2025). Hotel statistics [Dataset]. https://data.ontario.ca/dataset/hotel-statistics
    Explore at:
    xlsx(32676), xlsx(32627), xlsx(33800), xlsx(33570), xlsx(33578), xlsx(33430), xlsx(33448), xlsx(32661), web(None), xlsx(32887), xlsx(32623), xlsx(32565), xlsx(32563), xlsx(32843), xlsx(33158), xlsx(32853), xlsx(33370), xlsx(34518), xlsx(34238), xlsx(33539), xlsx(33680), xlsx(33706), xlsx(196033), xlsx(33774), xlsx(33855), xlsx(33672), xlsx(33625), xlsx(33537), xlsx(33662), xlsx(33551), xlsx(33636), xlsx(33436), xlsx(33654), xlsx(33691), xlsx(33514), xlsx(33418), xlsx(32411), xlsx(33649), xlsx(33627), xlsx(32448), xlsx(32546), xlsx(32540), xlsx(32377), xlsx(32810), xlsx(32652), xlsx(32896), xlsx(32660), xlsx(32909), xlsx(32573), xlsx(32827), xlsx(32802), xlsx(196474), xlsx(33759), xlsx(203385), xlsx(33924), xlsx(202316), xlsx(33556), xlsx(32477)Available download formats
    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Heritage, Sport, Tourism and Culture Industries
    License

    https://www.ontario.ca/page/terms-usehttps://www.ontario.ca/page/terms-use

    Area covered
    Ontario
    Description

    Data includes occupancy rates, average daily rates, and revenue per available room.

  5. Hotel Reservation dataset

    • kaggle.com
    Updated Jul 7, 2023
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    Vanthanadevi s (2023). Hotel Reservation dataset [Dataset]. https://www.kaggle.com/datasets/vanthanadevi08/hotel-reservation-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jul 7, 2023
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Vanthanadevi s
    Description

    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

  6. Change in monthly number of hotel bookings worldwide 2020-2023

    • statista.com
    • ai-chatbox.pro
    Updated Jun 27, 2025
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    Statista (2025). Change in monthly number of hotel bookings worldwide 2020-2023 [Dataset]. https://www.statista.com/statistics/1339573/change-in-monthly-number-of-hotel-bookings-worldwide/
    Explore at:
    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2020 - Nov 2023
    Area covered
    Worldwide
    Description

    The year-over-year monthly change in the number of hotel bookings worldwide dropped to *** 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 ** percent.

  7. Online Hotel Booking in the US - Market Research Report (2015-2030)

    • ibisworld.com
    Updated May 15, 2025
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    IBISWorld (2025). Online Hotel Booking in the US - Market Research Report (2015-2030) [Dataset]. https://www.ibisworld.com/united-states/market-research-reports/online-hotel-booking-industry/
    Explore at:
    Dataset updated
    May 15, 2025
    Dataset authored and provided by
    IBISWorld
    License

    https://www.ibisworld.com/about/termsofuse/https://www.ibisworld.com/about/termsofuse/

    Time period covered
    2015 - 2030
    Area covered
    United States
    Description

    The Online Hotel Booking industry comprises establishments primarily providing hotel booking services via online platforms. These websites are third-party platforms for customers to research and make hotel reservations. Consequently, this industry excludes hotels that offer direct bookings on their websites and brick-and-mortar travel agencies. Over the past five years, more individuals willing to make online reservations have benefited the industry. However, rising inflation and consumer uncertainty since 2022 have collectively reduced travel demand. Therefore, over the five years to 2025, industry revenue is expected to grow at an annualized rate of 19.5% to $55.8 billion, including a 4.7% growth in 2025 alone. The surge in growth rate is due to the low pandemic base year when industry revenue suffered from travel restrictions. Traditionally, travelers could book hotel hotels directly on websites or via travel agencies. However, the introduction of online hotel booking services enables customers to search and browse hotels according to their desired criteria, compare rooms at different hotels, and finally make a reservation from the comfort of their homes. Consequently, the industry has grown due to its added convenience compared with its direct substitutes. The industry has grown strongly due to the consistent rises in the number of trips made by US travelers and inbound trips by non-US residents. Industry revenue will continue to grow over the next five years as the economy improves from the record-high inflation. As consumer confidence recovers, individuals will feel more financially comfortable traveling. However, the industry contends with higher competition from direct hotel websites as some customers still make reservations directly with hotels. Nonetheless, industry revenue is projected to increase at an annualized rate of 2.5% to $63.1 billion over the five years to 2030.

  8. Hotel / private accommodation online bookings by brand in the U.S. 2025

    • statista.com
    • ai-chatbox.pro
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    Statista, Hotel / private accommodation online bookings by brand in the U.S. 2025 [Dataset]. https://www.statista.com/forecasts/997168/hotel-private-accommodation-online-bookings-by-brand-in-the-us
    Explore at:
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 2024 - Jun 2025
    Area covered
    United States
    Description

    We asked U.S. consumers about "Hotel / private accommodation online bookings by brand" and found that "Booking.com" takes the top spot, while "HotelsCombined" is at the other end of the ranking.These results are based on a representative online survey conducted in 2025 among ***** consumers in the United States. Seeking valuable insights about users of various accommodation platforms worldwide? Check out our reports about accommodation portals. These reports provide readers with a detailed understanding into users of various accommodation portals, highlighting their demographics, preferences, opinions, and ways to engage with them effectively.

  9. h

    hotel_reviews

    • huggingface.co
    Updated Jun 24, 2023
    + more versions
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    Coeus Learning (2023). hotel_reviews [Dataset]. https://huggingface.co/datasets/coeuslearning/hotel_reviews
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jun 24, 2023
    Authors
    Coeus Learning
    License

    https://choosealicense.com/licenses/openrail/https://choosealicense.com/licenses/openrail/

    Description

    Dataset Card for "hotel_reviews"

    More Information needed

  10. D

    Hotel Reservation Software Market Report | Global Forecast From 2025 To 2033...

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
    + more versions
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    Dataintelo (2025). Hotel Reservation Software Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-hotel-reservation-software-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Jan 7, 2025
    Authors
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Hotel Reservation Software Market Outlook



    The global hotel reservation software market size was valued at approximately USD 5.6 billion in 2023 and is projected to reach USD 12.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 9.3% during the forecast period. This substantial growth is primarily driven by the increasing digitalization of the hospitality industry, which is pushing hotels to adopt innovative software solutions to streamline operations and enhance guest experiences. As hotels strive to offer seamless and personalized services to meet the evolving expectations of travelers, the demand for advanced reservation software is anticipated to rise steadily.



    One of the key growth factors in the hotel reservation software market is the surging trend of online booking channels. With a significant shift in consumer behavior towards online platforms, hotels are increasingly adopting reservation software that integrates seamlessly with online travel agencies (OTAs) and global distribution systems (GDS). This integration not only helps in maximizing room occupancy rates but also offers customers a convenient booking experience. Furthermore, the proliferation of mobile applications is driving hotels to provide mobile-friendly booking solutions, thus broadening their reach and enhancing customer satisfaction. The convenience and accessibility offered by mobile booking platforms are anticipated to further propel market growth.



    Another significant factor contributing to the growth of the hotel reservation software market is the rising importance of data analytics and automation in the hospitality sector. TodayÂ’s competitive market demands that hotels harness the power of data to make informed decisions and optimize their operations. Advanced reservation software equipped with analytics capabilities allows hoteliers to analyze trends, forecast demand, and implement dynamic pricing strategies to maximize revenue. Additionally, automation in reservation processes reduces manual errors, enhances operational efficiency, and improves overall guest experiences. The increasing reliance on data-driven decision-making processes is thus expected to fuel the adoption of hotel reservation software globally.



    Moreover, the focus on enhancing guest experiences is a crucial driver for the growth of the hotel reservation software market. Hotels are increasingly investing in technology to personalize guest experiences, as it plays a pivotal role in customer satisfaction and retention. Reservation software with integrated customer relationship management (CRM) systems enables hotels to collect and analyze guest preferences, allowing them to tailor services and offers accordingly. Furthermore, features like automated communication, personalized recommendations, and loyalty programs integrated with reservation systems are becoming essential tools for hotels seeking to differentiate themselves in the competitive landscape. This emphasis on elevating guest experiences is likely to significantly boost the market's growth trajectory.



    In the realm of hospitality, Travel Software plays an integral role in enhancing the overall guest experience and operational efficiency. This software encompasses a wide range of applications that assist hotels in managing travel-related services, such as booking flights, arranging transportation, and planning itineraries for guests. By integrating Travel Software with hotel reservation systems, establishments can offer a seamless and comprehensive service to their guests, ensuring that all aspects of their travel are taken care of. This not only improves guest satisfaction but also helps hotels in building long-term relationships with their clientele. As the demand for personalized travel experiences continues to grow, the adoption of Travel Software is expected to rise, further driving the growth of the hotel reservation software market.



    Regionally, the hotel reservation software market is witnessing substantial growth across various geographies due to the rising number of international and domestic travelers. North America holds a prominent share in the market, driven by the presence of a robust hospitality infrastructure and high adoption rates of advanced technologies. Europe follows closely, with countries like the UK, France, and Germany leading the way in technology adoption within the hospitality industry. In the Asia Pacific region, rapid digitization and growing tourism activities are expected to drive the market significantly. The burgeoning middle-class population and increasing disposab

  11. S

    Hotel

    • data.sanjoseca.gov
    • gisdata-csj.opendata.arcgis.com
    Updated Apr 28, 2025
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    Enterprise GIS (2025). Hotel [Dataset]. https://data.sanjoseca.gov/dataset/hotel
    Explore at:
    arcgis geoservices rest api, kml, geojson, csv, html, zipAvailable download formats
    Dataset updated
    Apr 28, 2025
    Dataset provided by
    City of San José
    Authors
    Enterprise GIS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Representations of hotels in San Jose, CA.

    Data is published on Mondays on a weekly basis.

  12. c

    Booking hotel reviews large dataset

    • crawlfeeds.com
    csv, zip
    Updated Jun 17, 2025
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    Crawl Feeds (2025). Booking hotel reviews large dataset [Dataset]. https://crawlfeeds.com/datasets/booking-hotel-reviews-large-dataset
    Explore at:
    zip, csvAvailable download formats
    Dataset updated
    Jun 17, 2025
    Dataset authored and provided by
    Crawl Feeds
    License

    https://crawlfeeds.com/privacy_policyhttps://crawlfeeds.com/privacy_policy

    Description

    Explore our extensive Booking Hotel Reviews Large Dataset, featuring over 20.8 million records of detailed customer feedback from hotels worldwide. Whether you're conducting sentiment analysis, market research, or competitive benchmarking, this dataset provides invaluable insights into customer experiences and preferences.

    The dataset includes crucial information such as reviews, ratings, comments, and more, all sourced from travellers who booked through Booking.com. It's an ideal resource for businesses aiming to understand guest sentiments, improve service quality, or refine marketing strategies within the hospitality sector.

    With this hotel reviews dataset, you can dive deep into trends and patterns that reveal what customers truly value during their stays. Whether you're analyzing reviews for sentiment analysis or studying traveller feedback from specific regions, this dataset delivers the insights you need.

    Ready to get started? Download the complete hotel review dataset or connect with the Crawl Feeds team to request records tailored to specific countries or regions. Unlock the power of data and take your hospitality analysis to the next level!

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

  13. h

    filtered-hotel-dataset

    • huggingface.co
    Updated Oct 8, 2024
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    DvorakInnovation (2024). filtered-hotel-dataset [Dataset]. https://huggingface.co/datasets/DvorakInnovationAI/filtered-hotel-dataset
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 8, 2024
    Dataset authored and provided by
    DvorakInnovation
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    DvorakInnovationAI/filtered-hotel-dataset dataset hosted on Hugging Face and contributed by the HF Datasets community

  14. Global hotel check-in/out tech preferences worldwide 2020

    • statista.com
    • ai-chatbox.pro
    Updated Jun 27, 2025
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    Statista (2025). Global hotel check-in/out tech preferences worldwide 2020 [Dataset]. https://www.statista.com/statistics/1189903/hotel-check-in-out-tech-preferences-worldwide/
    Explore at:
    Dataset updated
    Jun 27, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jul 2020 - Aug 2020
    Area covered
    Worldwide
    Description

    During the coronavirus (COVID-19) pandemic, a worldwide survey was conducted from July to August 2020 to determine which contactless options hotel guests preferred to use for check-in and check-out, as opposed to the traditional reception desk procedure. The contactless options given were hotel apps, webpages, and public kiosks. The results of the survey indicated that most respondents, ** percent, preferred to check in and check-out using a hotel app. Meanwhile, ** percent preferred to use a website, leaving only * percent of respondents who preferred to use a public kiosk.

  15. m

    Luxury Hotel Market Size & Trends - Industry Statistics

    • mordorintelligence.com
    pdf,excel,csv,ppt
    Updated Jun 20, 2025
    + more versions
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    Mordor Intelligence (2025). Luxury Hotel Market Size & Trends - Industry Statistics [Dataset]. https://www.mordorintelligence.com/industry-reports/luxury-hotel-market
    Explore at:
    pdf,excel,csv,pptAvailable download formats
    Dataset updated
    Jun 20, 2025
    Dataset authored and provided by
    Mordor Intelligence
    License

    https://www.mordorintelligence.com/privacy-policyhttps://www.mordorintelligence.com/privacy-policy

    Time period covered
    2020 - 2030
    Area covered
    Global
    Description

    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).

  16. H

    Hotels

    • opendata.hawaii.gov
    • geoportal.hawaii.gov
    • +3more
    Updated Oct 4, 2022
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    Office of Planning (2022). Hotels [Dataset]. https://opendata.hawaii.gov/dataset/hotels1
    Explore at:
    pdf, arcgis geoservices rest api, zip, csv, geojson, html, ogc wfs, ogc wms, kmlAvailable download formats
    Dataset updated
    Oct 4, 2022
    Dataset provided by
    Hawaii Statewide GIS Program
    Authors
    Office of Planning
    Description

    [Metadata] Locations of the Visitor Plant Inventory (VPI) in the State of Hawaii (updated December, 2021). Source: Hawaii Tourism Authority, September 2022. This inventory includes apartment hotels, bed and breakfasts (B&Bs), condominium hotels, hostels, hotels, individual vacation units, timeshares, and other types of visitor accommodations.


    For additional information, please refer to complete metadata at https://files.hawaii.gov/dbedt/op/gis/data/hotels.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; Phone: (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

  17. D

    Online Hotel Booking Software Market Report | Global Forecast From 2025 To...

    • dataintelo.com
    csv, pdf, pptx
    Updated Dec 3, 2024
    + more versions
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    Dataintelo (2024). Online Hotel Booking Software Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-online-hotel-booking-software-market
    Explore at:
    csv, pptx, pdfAvailable download formats
    Dataset updated
    Dec 3, 2024
    Authors
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Online Hotel Booking Software Market Outlook



    The global online hotel booking software market has witnessed significant growth, with the market size valued at USD 3.46 billion in 2023 and projected to reach USD 8.82 billion by 2032, growing at a compound annual growth rate (CAGR) of 11.1% during the forecast period. This growth is driven by the increasing reliance on digital platforms for hotel reservation services owing to the shift in consumer habits towards more convenience and efficiency in travel planning. The advent of advanced technologies such as artificial intelligence and cloud computing has further augmented the market growth by enhancing the user experience and operational efficiency for businesses.



    One of the primary growth drivers for the online hotel booking software market is the proliferation of smartphones and the increased penetration of the internet worldwide. As more consumers gain access to these technologies, there is a heightened demand for seamless, user-friendly hotel booking experiences, especially through mobile applications. The convenience of booking, modifying, or canceling reservations at any time and from any location has been a significant factor in the adoption of online booking platforms. Moreover, as consumers become more tech-savvy, their expectations for hotel booking experiences are evolving, leading to increased demand for cutting-edge software solutions that offer personalization, quick processing, and comprehensive customer support.



    Another critical factor contributing to the market's growth is the increasing trend of digitalization in the travel and tourism industry. Hotels and travel agencies are increasingly adopting digital strategies to enhance customer engagement and loyalty. This shift is largely driven by the need to remain competitive in a market where consumers have numerous options at their fingertips. Digital tools, including online hotel booking software, are being leveraged to streamline operations, reduce overhead costs, and provide valuable data analytics for better decision-making. Furthermore, the integration of AI and machine learning into these platforms offers enhanced capabilities such as predictive analytics, which can significantly improve customer targeting and personalization.



    The rise in global tourism and business travel also serves as a substantial growth factor for the market. As economies recover and international borders open, there has been a resurgence in travel activities, both for leisure and corporate purposes. This resurgence has led to a spike in demand for online hotel booking systems that can efficiently handle an increased volume of bookings while offering features like dynamic pricing, inventory management, and multi-channel distribution. Furthermore, the emphasis on enhancing customer experience through improved software functionalities is expected to sustain market growth over the coming years.



    Regionally, North America currently holds a significant share of the market, driven by the presence of leading market players and widespread adoption of advanced technologies. However, the Asia Pacific region is anticipated to exhibit the highest growth rate during the forecast period. Factors such as increasing internet penetration, rising disposable incomes, and a burgeoning middle class are contributing to this rapid growth. Additionally, the region's vibrant tourism sector, with countries like China, India, and Japan emerging as key travel destinations, further fuels the demand for efficient and robust hotel booking solutions. Europe and Latin America also present promising growth prospects, supported by digital transformation initiatives and a growing emphasis on enhancing the tourism infrastructure.



    Deployment Type Analysis



    In terms of deployment type, the online hotel booking software market is segmented into cloud-based and on-premises solutions. Cloud-based deployment is gaining traction due to its scalability, cost-effectiveness, and ease of access. Hotels and travel agencies are increasingly favoring cloud solutions as they offer real-time data access, seamless updates, and integration with other systems, which is essential for maintaining a competitive edge in the fast-paced hospitality industry. The ability to manage operations remotely and the advantage of reduced IT infrastructure costs are compelling reasons for the shift towards cloud-based solutions.



    Cloud-based solutions also provide an added layer of security with regular updates and backups, which are crucial for protecting sensitive customer data. This deployment type supports scalability, allowing business

  18. Monthly average hotel daily rate worldwide 2018-2020, by region

    • statista.com
    Updated Jul 10, 2025
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    Statista (2025). Monthly average hotel daily rate worldwide 2018-2020, by region [Dataset]. https://www.statista.com/statistics/206840/average-daily-rate-of-hotels-by-region/
    Explore at:
    Dataset updated
    Jul 10, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2018 - May 2020
    Area covered
    Worldwide
    Description

    As a result of the coronavirus (COVID-19) pandemic the hotel industry has taken a hit in 2020. In May 2020, the average daily rate (ADR) of hotels in Europe was ***** U.S. dollars. Daily hotel prices were lowest in the Asia Pacific region during the same month.

    Hotel rate changes worldwide

    In each region, corporate average daily hotel rates are forecast to increase by 2020. Asia’s rates are predicted to be higher than the global average, increasing by about ***** percent. Latin America should see a smaller rise of about *** percent, due to the more modest growth in demand within this region. However, these rates were forecast prior to the coronavirus (COVID-19) pandemic therefore will be subject to change.

    Hotel occupancy rate

    Average daily rates in the hotel industry tend to change throughout the year as they are closely linked to hotel occupancy rates. Specific regions are visited more frequently during certain times of year. For instance, hotel rooms in the Americas were rented more frequently during the summer months, compared to the colder winter months in 2019.

  19. i

    Hotel review dataset

    • ieee-dataport.org
    Updated Oct 18, 2019
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    Qiang Lu (2019). Hotel review dataset [Dataset]. https://ieee-dataport.org/documents/hotel-review-dataset
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    Dataset updated
    Oct 18, 2019
    Authors
    Qiang Lu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Chinese Hotel Review Dataset

  20. m

    Hotel Booking Market Size, Share & Industry Analysis 2033

    • marketresearchintellect.com
    Updated Jul 3, 2025
    + more versions
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    Market Research Intellect (2025). Hotel Booking Market Size, Share & Industry Analysis 2033 [Dataset]. https://www.marketresearchintellect.com/product/global-hotel-booking-market-size-forecast/
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    Dataset updated
    Jul 3, 2025
    Dataset authored and provided by
    Market Research Intellect
    License

    https://www.marketresearchintellect.com/privacy-policyhttps://www.marketresearchintellect.com/privacy-policy

    Area covered
    Global
    Description

    Discover the latest insights from Market Research Intellect's Hotel Booking Market Report, valued at USD 100 billion in 2024, with significant growth projected to USD 150 billion by 2033 at a CAGR of 5.9% (2026-2033).

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Bright Data (2024). Hotels Dataset [Dataset]. https://brightdata.com/products/datasets/travel/hotels
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Hotels Dataset

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.json, .csv, .xlsxAvailable download formats
Dataset updated
May 7, 2024
Dataset authored and provided by
Bright Datahttps://brightdata.com/
License

https://brightdata.com/licensehttps://brightdata.com/license

Area covered
Worldwide
Description

We will create a customized hotels 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 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.

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