As per newly released data by Future Market Insights (FMI), the global tourism industry and big data analytics market is estimated at USD 225.4 billion in 2023 and is projected to reach USD 486.6 billion by 2033, at a CAGR of 8% from 2023 to 2033.
Big data analytics empowers tourism businesses to gather and analyze vast amounts of customer data, encompassing preferences, behaviors, and demographics. This invaluable information enables businesses to offer personalized recommendations, tailored travel packages and targeted marketing campaigns. The result is heightened customer satisfaction and loyalty.
Big data analytics facilitates precise demand forecasting by analyzing historical booking data, seasonal patterns, events, and other relevant factors. This foresight empowers tourism businesses to optimize pricing strategies, maximizing revenue during peak seasons and minimizing the risk of under-booking during periods of low demand.
The tourism industry heavily relies on social media platforms and online review sites for customer engagement. Big data analytics allows businesses to monitor these channels, gauge customer sentiment, identify emerging trends, and promptly address customer complaints. Companies can better understand customer feedback and adapt their marketing and service strategies by conducting sentiment analysis.
Big data analytics assists destination management organizations and tourism boards in identifying popular attractions, understanding visitor flows, and optimizing marketing efforts to attract more tourists to their regions. By leveraging data-driven insights, destinations can effectively promote their unique offerings and enhance overall tourism experiences.
| Attribute | Details |
|---|---|
| Historical Value (2022) | USD 220 billion |
| Current Year Value (2023) | USD 225.4 billion |
| Expected Forecast Value (2033) | USD 486.6 billion |
| Projected CAGR (2023 to 2033) | 8% |
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| Historical CAGR (2018 to 2022) | 6.5% |
|---|---|
| Forecasted CAGR (2023 to 2033) | 8% |
Over the last few years the advanced tools and technologies has evolved the tourism industry. The data analysis in tourism industry has made easy to understand the opportunity of markets, weaknesses of the company, consumer perception, preferences and better mode of connectivity among all the verticals of the market. Earlier it was difficult to conduct data analysis due to the massive and time consuming data collection process. The advanced tools have made it convenient due to the networking of the online platform.
In the modern era many travelers and organizations are making use of modern devices, software for a convenient and smooth journey. The data analytic tools use this online to understand the market current scenario and develop a strategy accordingly. The technologies such as Hadoop and cloud provide ample amount of space for data storage and offer wide range of data sources for analysis in a structured manner. In the modern era of technology and advancement big data analysis act as a prime factor for tourism industry.
Big data tools allow tour operator companies or travel agencies to understand the market performance. It helps to understand the demand and supply of service in the market, to estimate the demand and supply of service in near future, the competitor comparison, segment analysis, to optimize supply chain. Furthermore, it helps government agencies to understand the flow of tourism in the country and strategies the area of investment in tourism industry of a country.
Hotel chain use data analysis to understand the consumer preference and plan marketing strategy to attract more number of customers. The tools help to create relevant packages and offers based on the historic data or on travel patterns. It also aids the customer loyalty program as the tools help to analyze the frequent travelers using the service. Hence, the big data tools help to rise the efficiency of all the verticals of tourism industry.
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The big data technology helps to improve the tourism industry is various ways. Big data helps to analyze and manage the revenue. The revenue management refers to investment of right amount to a specific part of business to maximize the financial outcomes.
The feature enables travel agencies to analyze the right price for the service based on the expenses of the company, competitor prices comparison, past and current occupancy rates in the market, etc. It also helps to analyze which service can be merged with other services such as tour packages which includes hotel bookings with flight travel and likewise. It helps agencies to save the optimum cost and brings opportunity for diversity in business.
| Regions | 2022 Value Share in Global Market |
|---|---|
| North America | 23% |
| Europe | 19.7% |
The tourism industry in North America has been at the forefront of utilizing big data analytics. Prominent players, including travel agencies, hotels, and airlines, have made substantial investments in cutting-edge data analytics technologies. Their goal is to enhance customer satisfaction, personalize marketing efforts, and optimize their operations with data-driven precision.
Europe has witnessed remarkable growth in the adoption of big data analytics in the tourism sector. Countries like the United Kingdom, Germany, France, and Spain have wholeheartedly embraced data-driven approaches to bolster destination management, elevate tourist experiences, and execute highly effective marketing campaigns tailored to individual preferences.
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| Countries | Value CAGR (2023 to 2033) |
|---|---|
| United Kingdom | 4.7% |
| China | 6% |
| India | 5.1% |
Big Data Analytics is Shaping Responsible Tourism in the United Kingdom
The United Kingdom tourism industry big data analytics market is experiencing significant growth and presents numerous opportunities for businesses in the country. The United Kingdom tourism industry has undergone a digital transformation driven by the increasing use of mobile devices, online bookings, and digital marketing channels. Cities like London, Edinburgh, and Manchester attract a significant number of tourists.
The United Kingdom's scenic landscapes, national parks, and outdoor recreational activities attract nature and adventure tourists. Big data analytics can help identify popular destinations, track visitor activities, and analyze feedback, facilitating the development of sustainable and engaging experiences for travelers.
The tourism industry plays a crucial role in the United Kingdom's economy. According to the World Travel and Tourism Council (WTTC), the total contribution of travel and tourism to the country's GDP was USD 233.14 billion in 2022, accounting for 8.9% of the total GDP.
There is a growing emphasis on sustainable tourism practices in the United Kingdom. Big data analytics can help organizations track and analyze data related to environmental impact, resource consumption, and carbon emissions. As a result, they are better equipped to decide how to lessen their ecological imprint.
Big Data Analytics is Redefining & Shaping the Future of China's Tourism Industry
The China tourism industry has experienced impressive growth in recent years. With a burgeoning middle class and improved infrastructure, domestic tourism has been on the rise in China. In 2022, the total contribution of travel and tourism to China's GDP was approximately 11.5%.
The GDP contribution of China's travel and tourism industry is anticipated to increase by more than 150% this year, according to the World Travel & Tourism Council's (WTTC) 2023 Economic Impact Research (EIR).
Travelers from China have become a significant force in global tourism. Outbound tourism from China has grown consistently, driven by rising incomes, easing travel restrictions, and a growing appetite for international experiences. The application of big data analytics in the China tourism market has been transformative.
Big data enables businesses to optimize their offerings, marketing strategies, and operational efficiency. Hence, the future outlook for the China tourism industry big data analytics market looks promising, with continued growth, advanced analytics adoption, and a focus on sustainability and personalization.
Big Data Analytic To Boost The India Tourism Industry
Traveler from all over the world travel India for various reason. One of the thing that travelers like to experience the most is Indian Railways. Indian Railways is one of the tourist attraction. Everyday millions of commuters travel in Indian railways. According to India Brand Equity Foundation (IBEF) report India has the fourth largest railway network with 22593 trains and approximately 24 million passengers travel in Indian railways every day.
It is recognized as one of the largest railway system in the world. In 2014, The India Railways government of India launched IRCTC e-ticketing application for ease and convenience of ticket booking. There are millions of user accounts available consisting all the information of travelers. The data consist of traveler’s demographics, along with the information about other travelers traveling with him, travel preference, etc. To channelize and track this information the railway ministry makes use of oracle database.
The oracle server management help to store the data, track the data and analyze the data which help railways to make strategic decision and development of new packages and services for better services for its people. Meanwhile there are various other travel agencies and tour aggregators like Veena World, Kesari Tours, Yatra, others make use of big data analytics for smooth functioning and create better opportunity in market. This attracts other players in the market to generate demand for big data analytics in tourism industry.
| Countries | 2022 Value Share in Global Market |
|---|---|
| United States | 4% |
| Germany | 5% |
| Japan | 4.8% |
The Big Data Analytics Use By Travel Agencies Drives The Tourism Industry In United States
Travelers travel United States throughout the year. People travel United States for job opportunities’, tourism, education. In United States traveler make use of online applications extensively. As many travelers travel United States across the world, there is a huge demand for airlines in United States. As United States Airline serves a huge audience they generate a massive amount of data. Hence, they use big data analytics extensively.
The big data analytics not only help them analyze the consumer data segment but it also helps them to analyze and perform various other task. For example, Southwest airline use big data analytics to enhance their service to its customer, but the data also help them for smarter maintenance.
The fuel efficiency report, airplane health management systems, the flight metrics data help them understand the defects in all the aircraft help to reduce repair cost and provide safe flight to its customers. Such big data analytics is used in all the different verticals in United States for better efficiency of their services.
Germany's Innovative Approach to Managing Tourist Hotspots with Big Data Analytics
The tourism industry in Germany is a vital contributor to the country's economy, generating substantial revenue and employment opportunities. The current Economic Impact report from the World Travel & Tourism Council projects a rise in the sector's GDP by 1.3% annually on average between 2022 and 2032.
This growth rate outpaces the overall economy's projected growth rate of 1.1% during the same period. The tourism sector's GDP is expected to reach over USD 429.15 billion, which accounts for 9.7% of the total GDP in Germany.
The Germany tourism industry big data analytics market is witnessing steady growth and is expected to expand further in the coming years. As more tourism businesses recognize the importance of data-driven decision-making, the demand for big data analytics solutions and services is projected to increase.
Germany has been at the forefront of leveraging big data to manage tourist destinations efficiently. From crowd monitoring to traffic management, big data analytics enables authorities to optimize resources, improve infrastructure, and provide a seamless experience for visitors.
Big Data Analytics Fuels Tourism Innovation in Japan, Reshaping Travel Experiences
The Japan tourism industry big data analytics market is poised for significant growth. Japan has witnessed a steady rise in inbound tourism, with a record number of international visitors in recent years. The tourism industry in Japan is a significant contributor to the country's economy.
According to the 2023 Economic Impact Research published by the World Travel & Tourism Council (WTTC), Japan's travel and tourism industry is expected to contribute USD 285.5 billion to the country's GDP this year. More than USD 257 billion, or 6.2% of the economy, was contributed to the GDP by the industry last year, an increase of 50.5%.
Japan is known for its technological advancements, and the tourism industry is no exception. Businesses are adopting technologies to enhance the tourist experience and improve operational efficiency. Big data analytics has had a profound impact on the tourism industry in Japan.
Tourism businesses in Japan are likely to collaborate and form partnerships with data analytics firms, technology providers, and government agencies to harness the full potential of big data. Such collaborations are likely to lead to innovative solutions and a more holistic approach to data-driven decision-making.
| Segment | 2022 Value Share in Global Market |
|---|---|
| Descriptive Analytics Product Type | 34% |
| Revenue Management Purpose | 19% |
Descriptive Analysis Is Used In Global Tourism Industry Big Data Analytics Market
The descriptive data analysis helps to develop strategies based on historical and real time data, predictive analytics help to forecast and develop long term strategies for the travel agencies and perspective analytics help to understand the market and customer perception towards the industry. Other analysis such as e-commerce data, user generated content, temporal spatial data, etc. help to understand and develop strategy based on various other aspects of the industry.
Descriptive analytics has been a fundamental and established approach to data analysis for a long time. Many tourism businesses have already incorporated basic descriptive analytics tools into their operations, making it easier for them to adopt more advanced solutions in this segment.
Descriptive analytics relies on historical data, and tourism businesses usually have vast amounts of historical data accumulated over time. This data is often readily available. This makes it easier to implement descriptive analytics tools without significant additional data collection efforts.
Descriptive analytics tools are generally easier to implement and use compared to more complex analytics methods like predictive or prescriptive analytics. This simplicity makes it more accessible to a wider range of tourism companies, including smaller businesses that may not have the resources or expertise to adopt more advanced analytics methods.
Global Tourism Industry Big Data Analytics Is Mainly Use to Analyze Revenue Management
Revenue management holds a dominant position in the tourism industry's big data analytics market due to its ability to optimize pricing and inventory strategies and maximize revenue. Revenue management is focused on optimizing pricing and inventory strategies to maximize revenue and profitability for tourism businesses. Big data analytics plays a crucial role in this process by providing insights into customer behavior, market trends, and demand patterns. By leveraging data analytics, companies can make informed decisions to set optimal prices, allocate resources effectively, and maximize their overall revenue potential.
Travelers nowadays have high expectations when it comes to personalized experiences. Big data analytics enable businesses to gather and analyze customer data, such as preferences, past behaviors, and feedback, to offer tailored products and services. By personalizing offers, recommendations, and interactions, tourism businesses can enhance the customer experience, increase customer satisfaction and loyalty, and ultimately drive revenue growth.
Tourism Industry Big Data Analytics Market is More Preferred by The Travel Agencies
In terms of end-use outlook, the tourism industry big data analytics is more preferred by travel agencies. Travel agencies are mostly multimodal aggregators managing various verticals or types of services such as air travelling, train bookings, hotel bookings, others. With more number of services, they offer they generate a massive amount of data. The big data analytics allow them to store data on cloud database to conduct analysis and gain insightful information that help to frame strategies for their business.
The leading players operating in the global market and are focusing on developing innovative systems that can help to measure their market impact, customer presentence, market opportunities and various other measure more effectively and efficiently.
For instance:
In June 2023, OTELZ emerged as a remarkable example of success by blending tourism and technology. OTELZ has a considerable 40% cost advantage because to the efficient use of Microsoft's Azure technologies. With continuous advancements in technologies such as artificial intelligence, big data, and the integration of the Internet of Things, OTELZ aims to offer services at a more sophisticated level.
In January 2022, Marriott revealed its partnership with IBM Cloud technology, and together, they aim to elevate Marriott's IT operations. This collaboration aims to enable Marriott to deliver quicker digital services to tech-savvy guests and gain valuable insights about this crucial group of travelers, benefiting over 4,000 properties worldwide.
In the year 2017, Southwest Airlines collaborated with EPAM to improve the in-airport customer experience. EPAM with the help of data analytics build a digital wayfinding system for trouble-free navigation at airport. This helped customers for easy navigation at airport resulted in increase in demand for Southwest Airlines.
The CAGR for the market is 8% until 2033.
From 2018 to 2022, the market expanded at a 6.5% CAGR.
The market is valued at USD 225.4 in 2023.
The market will reach USD 486.6 billion by 2033.
North America generated 23% revenue in 2022.
1. Executive Summary 2. Market Overview 3. Market Background 4. Global Market Analysis 2018 to 2022 and Forecast, 2023 to 2033 5. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Product Types 5.1. Descriptive Analytics 5.2. Predictive Analytics 5.3. Perspective Analytics 6. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By End-Use 6.1. Transport 6.2. Accommodation 6.3. Travel Agencies 6.4. Others 7. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Deployment 7.1. Cloud Warehouse 7.2. On-premise 8. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Enterprises 8.1. SME 8.2. Large Enterprises 9. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Purpose 9.1. Revenue Management 9.2. Reputation Management 9.3. Strategic Management 9.4. Customer Experience 9.5. Market Research 9.6. Target Marketing 9.7. Market Intelligence 10. Global Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Region 10.1. North America 10.2. Latin America 10.3. Western Europe 10.4. Eastern Europe 10.5. South Asia and Pacific 10.6. East Asia 10.7. Middle East and Africa 11. North America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 12. Latin America Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 13. Western Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 14. Eastern Europe Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 15. South Asia and Pacific Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 16. East Asia Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 17. Middle East and Africa Market Analysis 2018 to 2022 and Forecast 2023 to 2033, By Country 18. Key Countries Market Analysis 19. Market Structure Analysis 20. Competition Analysis 20.1. Microsoft 20.2. Google 20.3. AWS 20.4. IBM 20.5. Dell 20.6. Splunk 20.7. Micro Focus 20.8. SAP 20.9. Accenture 20.10. Informatica 20.11. Teradata 20.12. Oracle 20.13. Cloudera 20.14. Palantir 20.15. HPE 20.16. Cisco 20.17. SAS 20.18. Alteryx 20.19. Continuum Analytics 20.20. DataStax 21. Assumptions & Acronyms Used 22. Research Methodology
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Tourism Industry Big Data Analytics Market
