The global tourism big data analytics market (2025 USD 18.4 billion) is projected to double in size to USD 41.9 billion by 2035, growing at a CAGR of 8.6%. Tourism stakeholders are moving away from post-trip surveys or guesswork. Instead, they are leveraging real-time analytics to gain insights into travelerbehavior, streamline operations and create hyper-personalized experiences.

Country-wise Visitor Data Integration Projects

Global Tourism Market size was worth around $11.39 trillion in 2023 and is predicted to grow to around $18.44 trillion by 2032 with a CAGR of 5.5%.

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.

US Travel Check-Ins - Analysis

In-Depth Study of Location, Date, Temperature, USIndex, and Crime Rates

By [source]

About this dataset

This comprehensive dataset offers an in-depth exploration into US travel check-ins from Instagram. It includes detailed data scraped from Instagram, such as the location of each check-in, the USIndex for each state, average temperature for each state per month, and crime rate per state. In addition to location and time information, this dataset also provides latitude and longitude coordinates for every entry. This extensive collection of data is invaluable for those interested in studying various aspects of movement within the United States. With detailed insights on factors like climate conditions and economic health of a region at a given point in time, this dataset can help uncover fascinating trends regarding how travelers choose their destinations and how they experience their journeys around the country

More Datasets

For more datasets, click here.

Featured Notebooks

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How to use the dataset

This Kaggle dataset - US Travel Check-Ins Analysis - provides valuable insights for travel researchers, marketers and businesses in the travel industry. It contains check-in location, USIndex rating (economic health of each state), average temperature, and crime rate per state. Latitude and longitude of each check-ins are also provided with added geographic context to help you visualize the data.

This guide will show you how to use this dataset for your research or business venture.

Step 1: Prepare your data First and foremost, it is important to cleanse your data before you can analyze it. Depending on what sort of analysis needs to be conducted (e.g., time series analysis) you will need to select the applicable columns from the dataset that match your needs best and exclude any unnecessary columns such as dates or season related data points as they are not relevant here. Furthermore, variable formatting should be consistent across all instances in a variable/column category as well (elevation is a good example here). You can always double check that everything is formatted correctly by running a quick summary on selected columns using conditional queries like df['var'].describe() command in Python for descriptive results about an entire column’s statistical makeup including mean values, quartile ranges etc..

Step 2: Explore & Analyze Your Data Graphically Once the data has been prepped properly you can start visualizing it in order to gain better insights into any trends or patterns that may be present within it when compared with other datasets or information sources simultaneously such as weather forecasts or nationwide trend indicators etc.. Grafana dashboards are feasible solutions when multiple dataset need to be compared but depending on what type of graphs/charts being used Excel worksheet formats can offer great customization options flexiblity along with various export file types (.csv; .jpegs; .pdfs). Plotting markers onto map applications like Google Maps API offers more geographical awareness that could useful when analyzing location dependent variables too which means we have one advantage over manual inspection tasks just by leveraging existing software applications alongside publicly available APIs!

Step 3: Interpretation & Hypothesis Testing
After generating informative graphical interpretation from exploratory visualizations the next step would involve testing out various hypotheses based on established correlations between different variables derived from overall quantitative estimates vizualizations regarding distribution trends across different regions tends towards geographical areas where certain logistical processes could yeild higher success ratios giving potential customers greater satisfaction than

Research Ideas

• Travel trends analysis: Using this dataset, researchers could track which areas of the US are popular destinations based on travel check-ins and spot any interesting trends or correlations in terms of geography, seasonal changes, economic health or crime rates.
• Predictive Modeling: By using various features from this dataset such as average temperature, US Index and crime rate, predictors could be developed to suggest how safe an area would feel to a tourist based on their current location and other predetermined variables they choose to input into the model.
• Trip Planning Tool: The dataset can also be used to develop a tool that quickly allows travelers to plan trips according to their preferences in terms of duration and budget as well a...

Title: India Travel Recommender System Dataset

Description

Context
Travel is a diverse and vibrant industry, and India, with its rich cultural heritage and varied landscapes, offers a myriad of experiences for travelers. The India Travel Recommender System Dataset is designed to facilitate the development of personalized travel recommendation systems. This dataset provides an extensive compilation of travel destinations across India, along with user profiles, reviews, and historical travel data. It's an invaluable resource for anyone looking to create AI-powered travel applications focused on the Indian subcontinent.

Content
The dataset is divided into four primary components:

1. Destinations: Information about various travel destinations in India, including details like type of destination (beach, mountain, historical site, etc.), popularity, and best time to visit.

2. Users: Profiles of users including their preferences and demographic information. This dataset has been enriched with gender diversity and includes details on the number of adults and children for travel.

3. Reviews: User-generated reviews and ratings for the different destinations, offering insights into visitor experiences and satisfaction.

4. User History: Records of users' past travel experiences, including destinations visited and ratings provided.

Each of these components is presented in a separate CSV file, allowing for easy integration and manipulation in data processing and machine learning workflows.

Acknowledgements
This dataset was generated for educational and research purposes and is intended to be used in hackathons, academic projects, and by AI enthusiasts aiming to enhance the travel experience through technology.

Inspiration
The dataset is perfect for exploring a variety of questions and tasks, such as: - Building a recommendation engine to suggest travel destinations based on user preferences. - Analyzing travel trends in India. - Understanding the relationship between user demographics and travel preferences. - Sentiment analysis of travel destination reviews. - Forecasting the popularity of travel destinations based on historical data.

We encourage Kaggle users to explore this dataset to uncover unique insights and develop innovative solutions in the realm of travel technology. Whether you're a data scientist, a student, or a travel tech enthusiast, this dataset offers a wealth of opportunities for exploration and creativity.

Usage

This dataset is free to use for non-commercial purposes. For commercial use, please contact the dataset provider. Remember to cite the source when using this dataset in your projects.

License

CC0: Public Domain - The dataset is in the public domain and can be used without restrictions.

The digital transformation of the travel and tourism industry is experiencing robust growth, driven by increasing smartphone penetration, the rise of online travel agencies (OTAs), and a growing preference for personalized travel experiences. The market, estimated at $500 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching approximately $1.5 trillion by 2033. This expansion is fueled by several key factors: the adoption of Artificial Intelligence (AI) for personalized recommendations and chatbots, the integration of Big Data analytics for improved operational efficiency and targeted marketing, and the widespread use of mobile applications for booking, planning, and managing travel itineraries. Furthermore, the increasing demand for seamless and contactless travel experiences, accelerated by the recent pandemic, is pushing innovation in areas such as mobile check-in, digital payments, and virtual tours. This digital shift empowers travelers with greater control and convenience, while enabling businesses to optimize their operations, enhance customer engagement, and unlock new revenue streams. However, challenges remain. Data security and privacy concerns are paramount, requiring robust cybersecurity measures to build trust and safeguard sensitive customer information. The need for effective digital literacy training among travel professionals and the integration of legacy systems with modern technologies pose significant hurdles for some businesses. Furthermore, the uneven distribution of digital infrastructure across different regions presents a barrier to inclusive growth, demanding strategic investments in connectivity and digital skills development. Despite these challenges, the long-term outlook for the digital transformation of the travel and tourism industry remains exceptionally positive, with continued growth anticipated across all segments and geographic regions. Companies like Booking Holdings, Expedia, and Google are at the forefront of this evolution, actively shaping the future of travel through technological innovation and strategic acquisitions.

This dataset offers a comprehensive view of global tourism, focusing on accommodation and transportation metrics, derived from the United Nations World Tourism Organization (UNWTO) data. The UNWTO is a specialized agency of the United Nations that serves as a global forum for tourism policy issues and a practical source of tourism know-how.

Introduction

The English Travel Chat Dataset is a comprehensive collection of over 12,000 text-based conversations between customers and call center agents. Focused on real-life travel and tourism interactions, this dataset captures the language, tone, and service dynamics essential for building robust conversational AI, chatbots, and NLP solutions for the travel industry in English-speaking markets.

Participant & Chat Overview

Topic Diversity

The dataset encompasses a wide range of travel and tourism use cases across both customer-initiated and agent-initiated conversations:

This variety ensures wide applicability in both sales enablement and customer support automation.

Language Diversity & Realism

Conversations are crafted to reflect the everyday language and nuances of English-speaking travelers:

These linguistic and cultural cues enable the development of context-aware, natural-sounding AI systems.

Conversational Structure & Flow

The dataset captures a variety of interaction types, including:

Snapshot img

Travel Market Size 2024-2028

The travel market size is forecast to increase by USD 2860.2 billion, at a CAGR of 11.1% between 2023 and 2028.

The market is experiencing significant growth, fueled by the increasing popularity of experiential travel and the surge in international tourist footfall. This trend is driven by consumers' shifting preferences towards unique and immersive travel experiences, offering opportunities for companies to differentiate their offerings and cater to this demand. However, the market faces challenges, including the growing threat from terrorism, which can deter travelers and negatively impact the industry. Companies must navigate these challenges by implementing robust security measures and fostering transparency to reassure customers. To capitalize on market opportunities, businesses should focus on delivering personalized, authentic experiences that cater to the evolving needs of travelers. By staying attuned to these trends and addressing the challenges, companies can effectively position themselves in the competitive the market landscape.

What will be the Size of the Travel Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2018-2022 and forecasts 2024-2028 - in the full report.
Request Free SampleIn the ever-evolving the market, various sectors continue to adapt and innovate to meet the changing needs and preferences of consumers. Business travelers seek convenience and efficiency with portable chargers, travel adaptors, and carry-on luggage, while solo travelers prioritize safety with GPS trackers and TSA locks. Sustainable tourism gains traction as eco-friendly options such as biodegradable products, carbon offsetting, and sustainable packaging become more prevalent. Medical tourism and food tourism cater to specific niches, offering unique experiences and specialized services. Travel data analytics and online booking platforms streamline the planning process, while tour guides and local experts provide valuable insights into destinations. Travel writing and journals allow travelers to document their experiences and share them with others. Luxury travel and adventure travel cater to diverse markets, with wheeled luggage, travel pillows, and hiking boots providing comfort and functionality. The marketing and social media platforms connect travelers with new experiences and destinations. Travel influencers and customer loyalty programs offer incentives and personalized recommendations. Tourism management and responsible travel initiatives prioritize the well-being of communities and the environment. Cultural tourism and destination marketing foster appreciation and understanding of diverse cultures. Rental cars and community tourism provide opportunities for authentic experiences and exploration. The market remains dynamic, with ongoing developments and trends shaping the industry. From travel accessories to travel technology, the market continues to evolve, offering new possibilities and experiences for travelers.

How is this Travel Industry segmented?

The travel industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments. SectorTransportationHotelTravel activitiesTypeLeisureBusinessTourCustomized & Private VacationsSafari & AdventureCruises, Yachting & Small Ship ExpeditionsCelebration JourneysCulinary Travel & ShoppingLuxury TrainsCustomized & Private VacationsSafari & AdventureCruises, Yachting & Small Ship ExpeditionsCelebration JourneysCulinary Travel & ShoppingLuxury TrainsAge21-30 Years31-40 Years41-60 Years60 And Above21-30 Years31-40 Years41-60 Years60 And AboveGeographyNorth AmericaUSEuropeFranceUKAPACChinaJapanRest of World (ROW)

By Sector Insights

The transportation segment is estimated to witness significant growth during the forecast period.In the thriving business travel sector, various offerings cater to the diverse needs of modern tourists. First-aid kits and biodegradable products have become essential travel accessories, reflecting a growing emphasis on health and sustainability. Travel insurance policies ensure peace of mind for business travelers, while ear plugs, eye masks, and portable chargers enhance comfort during long flights. Passport holders and sustainable packaging promote organization and eco-consciousness. Carbon offsetting and packing cubes streamline the process of planning and packing for trips. Food tourism and insect repellent cater to the adventurous palate and the need for outdoor exploration. Group travel and duffel bags offer cost savings, while hiking boots and travel data analytics facilitate efficient and enjoyable exploration. Medical tourism and travel safety services ensure well-being during international journeys. Travel adaptors, tour guides,

In 2020, executives in the global travel and hospitality industry were surveyed on the importance of customer data analytics to the business success of their company. The majority of respondents, ** percent, stated that customer data analytics were very important to the business success of their company. Meanwhile, only *** percent of respondents stated that customer data analytics were not important at all.

This dataset is about books. It has 1 row and is filtered where the book is Welcome! : English for the travel and tourism industry. It features 7 columns including author, publication date, language, and book publisher.

Many people enjoy traveling. When comparing the long distance train ticket users in selected countries worldwide, the highest share can be found in India, where 51 percent of consumers fall into this category. Finland ranks second with 42 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 2,000,000 interviews.

--- DATASET OVERVIEW --- This dataset captures detailed information about each vacation rental property listing across multiple OTAs. This report provides performance metrics and ranking insights that help users benchmark their rental properties and key in on performance drivers across all global vacation markets Key Data has to offer.

--- KEY DATA ELEMENTS --- Our dataset includes the following core performance metrics for each property: - Property Identifiers: Unique identifiers for each property with OTA-specific IDs - Historic Performance Metrics: Revenue, ADR, guest occupancy and more over the last 12 months. - Forward Looking Performance Metrics: Revenue, ADR, guest occupancy and more over the next 6 months. - Performance Tiering and Percentile Ranking amongst peer listings within the specified performance ranking groups. --How Listings Are Grouped: Listing Source (e.g., Airbnb vs. Vrbo) Market (identified by uuid) - Market type = vacation areas Property Type (house, apartment, unique stays, etc.) Number of Bedrooms (0, 1, 2, 3, 4, 5, 6, 7, 8+)

--- USE CASES --- Market Research and Competitive Analysis: VR professionals and market analysts can use this dataset to conduct detailed analyses of vacation rental supply across different markets. The data enables identification of property distribution patterns, amenity trends, pricing strategies, and host behaviors. This information provides critical insights for understanding market dynamics, competitive positioning, and emerging trends in the short-term rental sector.

Property Management Optimization: Property managers can leverage this dataset to benchmark their properties against competitors in the same geographic area. By analyzing listing characteristics, amenity offerings and guest reviews of similar properties, managers can identify optimization opportunities for their own portfolio. The dataset helps identify competitive advantages, potential service gaps, and management optimization strategies to improve property performance.

Investment Decision Support: Real estate investors focused on the vacation rental sector can utilize this dataset to identify investment opportunities in specific markets. The property-level data provides insights into high-performing property types, optimal locations, and amenity configurations that drive guest satisfaction and revenue. This information enables data-driven investment decisions based on actual market performance rather than anecdotal evidence.

Academic and Policy Research: Researchers studying the impact of short-term rentals on housing markets, urban development, and tourism trends can use this dataset to conduct quantitative analyses. The comprehensive data supports research on property distribution patterns and the relationship between short-term rentals and housing affordability in different markets.

Travel Industry Analysis: Travel industry analysts can leverage this dataset to understand accommodation trends, property traits, and supply and demand across different destinations. This information provides context for broader tourism analysis and helps identify connections between vacation rental supply and destination popularity.

--- ADDITIONAL DATASET INFORMATION --- Delivery Details: • Delivery Frequency: monthly | quarterly | annually • Delivery Method: scheduled file loads • File Formats: csv | parquet • Large File Format: partitioned parquet • Delivery Channels: Google Cloud | Amazon S3 | Azure Blob • Data Refreshes: monthly

Dataset Options: • Coverage: Global (most countries) • Historic Data: Last 12 months performance • Future Looking Data: Next 6 months performance • Point-in-Time: N/A

Contact us to learn about all options.

--- DATA QUALITY AND PROCESSING --- Our data collection and processing methodology ensures high-quality data with comprehensive coverage of the vacation rental market. Regular quality assurance processes verify data accuracy, completeness, and consistency.

The dataset undergoes continuous enhancement through advanced data enrichment techniques, including property categorization, geographic normalization, and time series alignment. This processing ensures that users receive clean, structured data ready for immediate analysis without extensive preprocessing requirements.

Snapshot img

Business Travel Market Size 2025-2029

The business travel market size is forecast to increase by USD 4867.6 billion, at a CAGR of 38.3% between 2024 and 2029.

The market is experiencing significant shifts, driven by the increasing adoption of advanced technologies and the evolving preferences of consumers. Technological innovations, such as online travel agencies and digital booking platforms, are revolutionizing the way businesses plan and manage their travel arrangements. This trend is further fueled by the growing popularity of online video conferencing platforms, enabling remote work and virtual meetings, thereby reducing the need for extensive business travel. Meanwhile, challenges persist in the form of data security concerns and complex travel policies. With the rise of digital booking platforms, ensuring secure transactions and protecting sensitive business data becomes paramount.
Additionally, managing complex travel policies across diverse teams and locations can be a daunting task, requiring robust solutions to streamline the process and maintain compliance. Companies seeking to capitalize on the opportunities presented by the evolving business travel landscape must focus on addressing these challenges effectively, while leveraging technology to enhance travel management efficiency and productivity.

What will be the Size of the Business Travel Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

The market continues to evolve, with dynamic market activities shaping the landscape across various sectors. Premium economy travel and loyalty programs are increasingly popular, offering enhanced comfort and rewards for frequent business travelers. Flight booking and travel procurement platforms streamline the process, while travel agent services provide expert assistance. Eco-friendly travel options gain traction, aligning with sustainability initiatives. Travel reporting and analytics enable effective business travel management, ensuring policy compliance and cost control. Business class travel, travel concierge services, and ground transportation options cater to the needs of corporate travelers.

Travel technology advances, integrating travel policy compliance, travel risk management, and expense management systems. Bleisure travel, frequent flyer programs, travel rewards, and travel technology further enrich the business travel experience. The ongoing unfolding of market activities underscores the importance of staying informed and adaptable in this ever-evolving landscape.

How is this Business Travel Industry segmented?

The business travel industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Application

  Marketing
  Internal meeting
  Trade show
  Product launch


Type

  Travel fare
  Lodging
  Dining
  Others


Service Type

  Transportation (Air, Rail, Car)
  Accommodation
  Meetings and Events


Booking Type

  Online Travel Agencies
  Direct Bookings
  Corporate Travel Management Companies


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Application Insights

The marketing segment is estimated to witness significant growth during the forecast period.

Business travel plays a pivotal role in the international marketing efforts of both small and large enterprises. This involves employees traveling to overseas markets to promote products and services, expand customer bases, and build brand reputation. Travel itinerary management and security are essential considerations to ensure the safety and productivity of business travelers. Duty of care and traveler tracking are crucial components of travel risk management, while travel insurance provides financial protection. Travel consolidators offer cost savings through bundled services, including flights, ground transportation, hotels, and car rentals. Carbon offsetting and eco-friendly travel options are increasingly important for companies committed to sustainability.

Travel data analytics enable businesses to make informed decisions on travel procurement and policy compliance. Premium economy travel and business class offerings cater to the needs of frequent travelers, while loyalty programs and travel rewards provide incentives. Travel technology, including travel booking platforms and expense management systems, streamline the travel process. Airport lounges and travel concierge services enhance the travel experience. First class travel and corporate travel policies cater to executives an

This dataset provides a comprehensive view of tourism consumer behavior, combining demographic, behavioral, and booking-related information. It captures how individuals plan and engage in travel activities across different preferences and spending levels. The data includes features such as age, gender, income, travel type, and duration. It also incorporates feedback and booking methods to reflect real consumer interactions in the tourism sector. This dataset is useful for identifying distinct patterns among different types of travelers. It can support applications in service personalization and targeted marketing in the travel industry.

Introduction

The Spanish Travel Chat Dataset is a comprehensive collection of over 10,000 text-based conversations between customers and call center agents. Focused on real-life travel and tourism interactions, this dataset captures the language, tone, and service dynamics essential for building robust conversational AI, chatbots, and NLP solutions for the travel industry in Spanish-speaking markets.

Participant & Chat Overview

Topic Diversity

The dataset encompasses a wide range of travel and tourism use cases across both customer-initiated and agent-initiated conversations:

This variety ensures wide applicability in both sales enablement and customer support automation.

Language Diversity & Realism

Conversations are crafted to reflect the everyday language and nuances of Spanish-speaking travelers:

These linguistic and cultural cues enable the development of context-aware, natural-sounding AI systems.

Conversational Structure & Flow

The dataset captures a variety of interaction types, including:

The tourism industry is confronted with an incredible abundance of information, which has the potential to completely transform the sector, as long as it is wisely, efficiently, and correctly analyzed and used.
Big Data solutions can help the tourism industry in various ways, such as:
• Increase the efficiency of internal operations;
• Travel, revenue, and investment management;
• Boost financial performance;
• Improve distribution management;
• Offer more personalized and tailored products and services;
• Target the right customers with the right offers and marketing campaigns;
• Help in the decision-making process;
• Improve quality of services and products; and
• Price dynamics, especially in the air travel sector and metasearch engines. Read More

Key Travel App StatisticsTop Travel AppsTravel App Market LandscapeTravel App RevenueTravel Revenue By AppTravel App UsersTravel App Market Share United StatesTravel App DownloadsThe online travel...

Adults in the United States were surveyed about the tourist attractions that they viewed most positively as of the third quarter of 2024. The Grand Canyon National Park ranked first on the list with a popularity score amounting to 81 percent. Meanwhile, the Statue of Liberty and Niagra Falls ranked second and third, respectively.

This dataset contains TripAdvisor guest reviews for major hotels in Salalah, Oman, collected through web scraping. It provides insights into guest satisfaction, sentiment, and ratings, making it a valuable resource for marketing, hospitality and tourism research, sentiment analysis, and tourism marketing studies.

𝐇𝐨𝐭𝐞𝐥𝐬 𝐈𝐧𝐜𝐥𝐮𝐝𝐞𝐝 𝐢𝐧 𝐭𝐡𝐞 𝐃𝐚𝐭𝐚𝐬𝐞𝐭 The dataset features guest reviews from the following hotels in Salalah:

• Al Baleed Resort Salalah by Anantara • Belad Bont Resort • Crowne Plaza Resort Salalah • Fanar Hotel and Residences • Hilton Salalah Resort • Juweira Boutique Hotel • Millennium Resort Salalah • Salalah Gardens Hotel • Salalah Rotana Resort

𝐓𝐢𝐦𝐞 𝐂𝐨𝐯𝐞𝐫𝐚𝐠𝐞 The dataset captures all available guest reviews from the beginning of each hotel's presence on TripAdvisor up until February 2025.

𝐑𝐞𝐥𝐞𝐯𝐚𝐧𝐜𝐞 𝐭𝐨 𝐊𝐡𝐚𝐫𝐞𝐞𝐟 𝐓𝐨𝐮𝐫𝐢𝐬𝐦 𝐎𝐦𝐚𝐧 𝐕𝐢𝐬𝐢𝐨𝐧 2040 This dataset is particularly beneficial for the following government agencies: • Ministry of Heritage and Tourism - Oman • Oman Chamber of Commerce & Industry (OCCI) • Dhofar Municipality and Dhofar Tourism Department • National Centre for Statistics and Information (NCSI) • Oman Vision 2040 Implementation Follow-up Unit • Ministry of Commerce, Industry, and Investment Promotion • Oman Tourism Development Company (OMRAN) • Ministry of Transport, Communications, and Information Technology (MTCIT) • Dhofar Governorate Office • Ministry of Environment and Climate Affairs

It also serves as a valuable resource for researchers, policymakers, and marketing, hospitality & tourism professionals to enhance Salalah’s tourism sector, improve guest satisfaction, and support Oman’s long-term vision for a thriving and sustainable tourism industry.

Salalah experiences a surge in visitors during the Khareef season (monsoon season), a critical period for the hospitality industry. This dataset can help analyze guest experiences, identify service gaps, and optimize offerings during this peak tourism period.

Oman Vision 2040 Goals The dataset aligns with Oman’s Vision 2040, which prioritizes tourism sector growth, economic diversification, and enhanced customer experiences. By leveraging sentiment analysis and guest insights, policymakers and hotel managers can develop data-driven strategies to improve hospitality services, attract more visitors, and enhance Salalah’s reputation as a premier travel destination.

Potential Use Cases Sentiment Analysis: Understanding guest satisfaction trends over time Tourism & Hospitality Research: Evaluating service quality and hotel performance across different years Marketing Insights: Identifying key drivers of positive and negative reviews for strategic decision-making Machine Learning & NLP: Training models for text classification, sentiment prediction, and recommendation systems