Global Big Data Analytics in Tourism
Market Report
2025
Big Data Analytics in Tourism Market size is USD 222154.2 million in 2024 and will expand at a compound annual growth rate (CAGR) of 8.20% from 2024 to 2031.
The base year for the calculation is 2024. The historical will be 2021 to 2024. The year 2025 will be estimated one while the forecasted data will be from year 2025 to 2033. When we deliver the report that time we updated report data till the purchase date.
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According to Cognitive Market Research, the global big data analytics in tourism market size is USD 222154.2 million in 2024 and will expand at a compound annual growth rate (CAGR) of 8.20% from 2024 to 2031.
2024 | 2025 | 2032 | 2033 | CAGR | |
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Global Big Data Analytics in Tourism Market Sales Revenue | $ 222154 Million | 121212 | 121212 | 121212 | 8.2% |
North America Big Data Analytics in Tourism Market Sales Revenue | $ 88861.7 Million | 121212 | 121212 | 121212 | 6.4% |
Europe Big Data Analytics in Tourism Market Sales Revenue | $ 66646.3 Million | 121212 | 121212 | 121212 | 6.7% |
Asia Pacific Big Data Analytics in Tourism Market Sales Revenue | $ 51095.5 Million | 121212 | 121212 | 121212 | 10.2% |
South America Big Data Analytics in Tourism Market Sales Revenue | $ 11107.7 Million | 121212 | 121212 | 121212 | 7.6% |
Middle East and Africa Big Data Analytics in Tourism Market Sales Revenue | $ 4443.08 Million | 121212 | 121212 | 121212 | 7.9% |
Base Year | 2024 |
Historical Data Time Period | 2021-2024 |
Forecast Period | 2025-2033 |
Market Split by Type |
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Market Split by Application |
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Market Split by Product |
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Market Split by End-Use |
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Market Split by Deployment |
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List of Competitors |
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Regional Analysis |
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Country Analysis |
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Big Data Analytics in Tourism Market is Segmented as below. Particular segment of your interest can be provided without any additional cost. Download the Sample Pages!
Tourism organizations can now collect and analyze enormous volumes of customer data, including demographics, behaviors, and preferences, due to big data analytics. Businesses are able to provide customized trip packages, individualized recommendations, and focused marketing campaigns thanks to this priceless information. Increased client loyalty and happiness are the outcomes. Numerous important factors are driving the expansion of big data analytics in the tourism sector. Large volumes of data have been produced by the growing use of digital technologies in the travel and tourism sector, necessitating the use of sophisticated analytics tools to extract useful information. Additionally, data-driven tactics for targeted marketing and customer engagement are becoming more and more important due to the growing desire from customers for individualized travel experiences. Furthermore, the tourist industry is adopting big data analytics solutions due to the expansion of data available for analysis brought about by developments in data collection technologies like social media monitoring and Internet of Things devices.
Travel agencies and tour operators can comprehend market performance with the use of big data techniques. Understanding the market's supply and demand for services, projecting future supply and demand, comparing competitors, conducting segment analysis, and supply chain optimization are all beneficial. Additionally, it facilitates government agencies' comprehension of the country's tourism flow and helps them plan where to invest in a nation's tourism sector. Hotel chains employ data research to design their marketing strategies and gain a better understanding of customer preferences. Based on historical data or travel trends, the tools assist in generating pertinent packages and offers. The technologies facilitate the analysis of frequent users of the service, which benefits the customer loyalty program as well. Therefore, all of the tourism industry's verticals are more efficient due to big data techniques.
One of the main factors propelling the expansion of big data analytics in tourism sector is the growing customer desire for personalized travel experiences. Travelers of today look for experiences that are customized to meet their interests, travel preferences, and travel goals rather than merely generic vacation packages. Due to this change in customer behavior, travel agencies have had to make investments in technologies that allow them to gather, process, and use enormous volumes of data in order to provide incredibly customized services and experiences. Additionally, big data analytics is essential in fulfilling this need since it enables businesses to obtain information from a variety of sources, including online. Through the analysis of this heterogeneous data, companies may discern individual inclinations, behavioral patterns, and industry trends, which empowers them to craft personalized travel experiences that appeal to every passenger.
In the context of big data analytics in the tourism business, protecting the security and privacy of sensitive traveler information is essential. There is a chance that personal information, including financial data and travel preferences, will be revealed due to the volume of data gathered from numerous sources, including reservations for hotels, activities, and travel. Strict criteria for handling personal data are mandated by regulatory organizations, such as the GDPR in Europe or similar regulations abroad, and non-compliance carries heavy fines. Furthermore, using this data has important ethical ramifications. Travelers anticipate that their information will be treated with integrity and responsibility and that its use and protection will be transparent. Moreover, the global aspect of tourism intensifies the intricacy of adhering to privacy and security rules, given that different locations may have disparate laws, requiring flexible systems and procedures. Thus, the complexity of privacy laws, moral dilemmas, and security standards makes it difficult to use big data analytics in the travel industry, which is a major barrier to its expansion.
The Big Data Analytics in the Tourism Market was greatly affected by the COVID-19 outbreak. The tourism industry saw a sharp decline due to travel restrictions, lockdowns, and safety concerns, which resulted in a decline in the amount of data produced by travel-related activities. The accuracy and applicability of analytics insights were impacted by this reduction in data availability, which made it difficult for organizations to make wise judgments. The epidemic did, however, also emphasize the value of data analytics in anticipating future trends and adjusting to changing conditions. As a result, there is now more emphasis on using big data to inform recovery plans and improve operational effectiveness in the travel and tourist industry.
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Major businesses use big data analytics extensively to sift through the vast amount of data created by the sector and derive useful insights. To better understand consumer behavior, boost marketing campaigns, streamline operations, and enhance overall customer experiences, these players make use of cutting-edge analytics tools and technologies. They hope to make data-driven decisions, spot trends and patterns, and spur innovation in the travel and tourism industry by utilizing the power of data analytics.
In September 2022: Zartico obtained Series A investment totaling $20 million. The investment is intended to introduce Version 3.0 and data analytics to the travel and tourist sector. Zartico makes use of analytics, infographics, and data intelligence. They support data-driven decision-making for destination tourism companies. Arthur Ventures led the fundraising round.
In February 2020: The first-ever travel industry technology combining AI, ML, and Big Data to boost hotel distribution wholesaler conversion was released by Spanish start-up Mind Analytics. The company specializes in data analytics to optimize decision-making in the tourist business. In order to optimize distribution, identify mistakes and patterns in behavior, and customize offers for your clients, the Travel Intelligence Engine (Travel/ie) solution gathers, processes, and evaluates data in real time.
Top Companies Market Share in Big Data Analytics in Tourism Industry: (In no particular order of Rank)
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According to Cognitive Market Research, North America dominated the market in 2024 and accounted for around 40% of the global revenue. The North American tourism sector has pioneered the application of big data analytics. Leading companies have invested heavily in state-of-the-art data analytics systems, including hotels, airlines, and travel agents. Improving client satisfaction, tailoring marketing campaigns, and precisely optimizing company operations using data are their three main objectives.
Asia-Pacific stands out as the fastest-growing region in big data analytics in tourism market. With record numbers of foreign visitors in recent years, Asia Pacific has seen a continuous increase in incoming tourism. Asia Pacific's tourist sector significantly boosts the region's national economy. Additionally, companies are using technology to boost operational effectiveness and improve the visitor experience. The Asia Pacific tourism business has experienced significant changes as a result of big data analytics.
The current report Scope analyzes Big Data Analytics in Tourism Market on 5 major region Split (In case you wish to acquire a specific region edition (more granular data) or any country Edition data then please write us on info@cognitivemarketresearch.com
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According to Cognitive Market Research, the global big data analytics in tourism market size was estimated at USD 222154.2 Million out of which North America held the major market of more than 40% of the global revenue with a market size of USD 88861.68 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.4% from 2024 to 2031.
According to Cognitive Market Research, the global big data analytics in tourism market size was estimated at USD 222154.2 Million out of which Europe held the market of more than 30% of the global revenue with a market size of USD 66646.26 million in 2024 and will grow at a compound annual growth rate (CAGR) of 6.4% from 2024 to 2031.
According to Cognitive Market Research, the global big data analytics in tourism market size was estimated at USD 222154.2 Million out of which Asia Pacific held the market of around 23% of the global revenue with a market size of USD 51095.47 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.2% from 2024 to 2031.
According to Cognitive Market Research, the global big data analytics in tourism market size was estimated at USD 222154.2 Million out of which Latin America market of more than 5% of the global revenue with a market size of USD 11107.71 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.6% from 2024 to 2031.
According to Cognitive Market Research, the global big data analytics in tourism market size was estimated at USD 222154.2 Million out of which Middle East and Africa held the major market of around 2% of the global revenue with a market size of USD 4443.08 million in 2024 and will grow at a compound annual growth rate (CAGR) of 7.9% from 2024 to 2031.
Global Big Data Analytics in Tourism Market Report 2025 Edition talks about crucial market insights with the help of segments and sub-segments analysis. In this section, we reveal an in-depth analysis of the key factors influencing Big Data Analytics in Tourism Industry growth. Big Data Analytics in Tourism market has been segmented with the help of its Type, Application Product, and others. Big Data Analytics in Tourism market analysis helps to understand key industry segments, and their global, regional, and country-level insights. Furthermore, this analysis also provides information pertaining to segments that are going to be most lucrative in the near future and their expected growth rate and future market opportunities. The report also provides detailed insights into factors responsible for the positive or negative growth of each industry segment.
According to Cognitive Market Research, the structured category stands out as the dominating category. Businesses can use it to study and comprehend a range of topics, including consumer preferences, travel trends, booking patterns, and the attractiveness of particular destinations. Businesses can use this structured data to improve overall customer satisfaction, personalize experiences, optimize pricing tactics, and make well-informed decisions.
Unstructured category emerges as the fastest-growing category in the big data analytics in tourism market because of the enormous volume of data supplied by sources such as reviews, social media, and customer feedback. Businesses may better target their marketing efforts, provide more individualized experiences for their customers, and increase customer happiness by analyzing this unstructured data better to understand customer preferences, trends, and mood.
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According to Cognitive Market Research, the dominating category is large enterprises. These businesses use data to understand their target audience's tastes better, tailor their advertising, enhance user experiences, and increase operational effectiveness. Enterprises may make data-driven decisions to stay competitive and improve customer satisfaction by using big data analytics to analyze the massive amounts of data created by online bookings, social media interactions, and mobile usage.
The fastest-growing category in the big data analytics in tourism market is SMEs. Smaller firms are using big data tools to improve customer experiences, streamline operations, and target marketing campaigns as more companies come to understand the importance of data-driven decision-making. The advent of more reasonably priced analytics solutions that are suited to SMEs' demands and allow them to compete with bigger companies in the market is driving this trend.
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According to Cognitive Market Research, the descriptive analysis category dominated the market in 2024. Descriptive data analysis aids in the creation of strategies based on historical and current data, predictive analytics aids in the forecasting and long-term strategy development for travel agencies, and perspective analytics aids in the comprehension of the market and consumer attitudes toward the sector.
The fastest-growing category in the big data analytics in tourism market is predictive analysis. Predictive analytics helps businesses anticipate trends, customize offers, optimize pricing, and improve customer experiences by using the massive volumes of data created by travelers, such as booking habits, preferences, and behavior. As a result, decision-making has become more effective, and industrial competition has intensified.
According to Cognitive Market Research, the travel agencies category dominated the market in 2024. The majority of travel firms are multimodal aggregators that handle different verticals or service categories, like reservations for hotels, trains, and airplanes, among others. Due to the increased number of services they provide, businesses produce enormous amounts of data. With the aid of big data analytics, they can store data in cloud databases for analysis and obtain valuable insights that aid in formulating corporate strategy.
The fastest-growing category in the big data analytics in tourism market is transport. Utilizing massive volumes of data from social media, booking platforms, transportation providers, and customer reviews, businesses may enhance customer happiness and efficiency by better understanding passenger preferences, personalizing experiences, and optimizing timetables and routes.
According to Cognitive Market Research, the cloud-warehouse category dominated the market in 2024. In order to obtain important insights into consumer preferences, behavior patterns, and market trends, it helps organizations to effectively store, process, and analyze enormous volumes of data from numerous sources, including booking platforms, customer reviews, and social media. This makes it possible for travel agencies to improve client experiences, optimize marketing plans, make data-driven decisions, and ultimately spur industry growth and competition.
The fastest-growing category in the big data analytics in tourism market is on-premise. Some businesses may choose on-premise solutions because they have more control over their data and because they are concerned about data security and compliance. Furthermore, in comparison to cloud-based solutions, on-premise solutions might provide greater flexibility and scalability choices for enterprises with high data volumes or particular performance requirements.
Research associate at Cognitive Market Research
Swasti Dharmadhikari, an agile and achievement-focused market researcher with an innate ardor for deciphering the intricacies of the Service & Software sector. Backed by a profound insight into technology trends and consumer dynamics, she has committed herself to meticulously navigating the ever-evolving terrain of digital Services and software solutions.
Swasti an agile and achievement-focused market researcher with an innate ardor for deciphering the intricacies of the Service & Software sector. Backed by a profound insight into technology trends and consumer dynamics, she has committed herself to meticulously navigating the ever-evolving terrain of digital Services and software solutions.
In her current role, Swasti manages research for service and software category, leading initiatives to uncover market opportunities and enhance competitive positioning. Her strong analytical skills and ability to provide clear, impactful findings have been crucial to her team’s success. With an expertise in market research analysis, She is adept at dissecting complex problems, extracting meaningful insights, and translating them into actionable recommendations, Swasti remains an invaluable asset in the dynamic landscape of market research.
Please note, we have not disclose, all the sources consulted/referred during a market study due to confidentiality and paid service concern. However, rest assured that upon purchasing the service or paid report version, we will release the comprehensive list of sources along with the complete report and we also provide the data support where you can intract with the team of analysts who worked on the report.
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Type | Structured, Semi-Structured, Unstructured |
Application | SMEs, Large Enterprises |
Product | Descriptive Analytics, Predictive Analytics, Perspective Analytics |
End-Use | Transport, Accommodation, Travel Agencies, Others |
Deployment | Cloud Warehouse, On-premise |
List of Competitors | TIBCO, Hewlett Packard Enterprise, Hitachi, SAP, Accenture, Oracle, IBM, Tableau, Amazon, Microsoft, Google |
This chapter will help you gain GLOBAL Market Analysis of Big Data Analytics in Tourism. Further deep in this chapter, you will be able to review Global Big Data Analytics in Tourism Market Split by various segments and Geographical Split.
Chapter 1 Global Market Analysis
Global Market has been segmented on the basis 5 major regions such as North America, Europe, Asia-Pacific, Middle East & Africa, and Latin America.
You can purchase only the Executive Summary of Global Market (2019 vs 2024 vs 2031)
Global Market Dynamics, Trends, Drivers, Restraints, Opportunities, Only Pointers will be deliverable
This chapter will help you gain North America Market Analysis of Big Data Analytics in Tourism. Further deep in this chapter, you will be able to review North America Big Data Analytics in Tourism Market Split by various segments and Country Split.
Chapter 2 North America Market Analysis
This chapter will help you gain Europe Market Analysis of Big Data Analytics in Tourism. Further deep in this chapter, you will be able to review Europe Big Data Analytics in Tourism Market Split by various segments and Country Split.
Chapter 3 Europe Market Analysis
This chapter will help you gain Asia Pacific Market Analysis of Big Data Analytics in Tourism. Further deep in this chapter, you will be able to review Asia Pacific Big Data Analytics in Tourism Market Split by various segments and Country Split.
Chapter 4 Asia Pacific Market Analysis
This chapter will help you gain South America Market Analysis of Big Data Analytics in Tourism. Further deep in this chapter, you will be able to review South America Big Data Analytics in Tourism Market Split by various segments and Country Split.
Chapter 5 South America Market Analysis
This chapter will help you gain Middle East Market Analysis of Big Data Analytics in Tourism. Further deep in this chapter, you will be able to review Middle East Big Data Analytics in Tourism Market Split by various segments and Country Split.
Chapter 6 Middle East Market Analysis
This chapter will help you gain Middle East Market Analysis of Big Data Analytics in Tourism. Further deep in this chapter, you will be able to review Middle East Big Data Analytics in Tourism Market Split by various segments and Country Split.
Chapter 7 Africa Market Analysis
This chapter provides an in-depth analysis of the market share among key competitors of Big Data Analytics in Tourism. The analysis highlights each competitor's position in the market, growth trends, and financial performance, offering insights into competitive dynamics, and emerging players.
Chapter 8 Competitor Analysis (Subject to Data Availability (Private Players))
(Subject to Data Availability (Private Players))
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
Data Subject to Availability as we consider Top competitors and their market share will be delivered.
This chapter would comprehensively cover market drivers, trends, restraints, opportunities, and various in-depth analyses like industrial chain, PESTEL, Porter’s Five Forces, and ESG, among others. It would also include product life cycle, technological advancements, and patent insights.
Chapter 9 Qualitative Analysis (Subject to Data Availability)
Segmentation Type Analysis 2019 -2031, will provide market size split by Type. This Information is provided at Global Level, Regional Level and Top Countries Level The report with the segmentation perspective mentioned under this chapters will be delivered to you On Demand. So please let us know if you would like to receive this additional data as well. No additional cost will be applicable for the same.
Chapter 10 Market Split by Type Analysis 2021 - 2033
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Chapter 11 Market Split by Application Analysis 2021 - 2033
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Chapter 12 Market Split by Product Analysis 2021 - 2033
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Chapter 13 Market Split by End-Use Analysis 2021 - 2033
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Chapter 14 Market Split by Deployment Analysis 2021 - 2033
This chapter helps you understand the Key Takeaways and Analyst Point of View of the global Big Data Analytics in Tourism market
Chapter 15 Research Findings
Here the analyst will summarize the content of entire report and will share his view point on the current industry scenario and how the market is expected to perform in the near future. The points shared by the analyst are based on his/her detailed in-depth understanding of the market during the course of this report study. You will be provided exclusive rights to interact with the concerned analyst for unlimited time pre purchase as well as post purchase of the report.
Chapter 16 Research Methodology and Sources
Why Structured have a significant impact on Big Data Analytics in Tourism market? |
What are the key factors affecting the Structured and Semi-Structured of Big Data Analytics in Tourism Market? |
What is the CAGR/Growth Rate of SMEs during the forecast period? |
By type, which segment accounted for largest share of the global Big Data Analytics in Tourism Market? |
Which region is expected to dominate the global Big Data Analytics in Tourism Market within the forecast period? |
Segmentation Level Customization |
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Region level Data Customization |
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Country level Data Customization |
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Company Level |
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Additional Data Analysis |
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Additional Qualitative Data |
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Additional Quantitative Data |
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Service Level Customization |
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Report Format Alteration |
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