The travel industry processes unprecedented volumes of data from each and every traveller.

Smartphone apps, online ticketing, social media feedback, real-time price comparison – the digital revolution has affected the travel industry more than any other.

Advances in technology over the past decade have revolutionised the travel business and customer behaviour even more heavily than most other consumer industries.

Online innovations such as travel portals, apps for recommendations and bookings, GPS tracking and many others have hastened unprecedented growth in the industry. Technological advances mean that customers are more engaged. This in turn means that they are better aware and informed which, inevitably, leads to them being more demanding in terms of their expectations.

Thus, service providers are challenged with making as much use of technological innovation in the travel industry as their customers in order to keep ahead of the game, meet customer expectations and retain market share in an era of new market entrants and negligible customer switching costs.

Big Data Analytics is one such innovation that travel companies need to embrace in order to meet 21st century challenges in customer satisfaction, business efficiency and competitive advantage.

What Is Big Data Analytics?

Big data analytics is the evaluation of large data sets to identify underlying trends, patterns, correlations, customer behaviours, etc. to gain vital data insights.

Data insights can be a valuable tool in market analysis, leading to new marketing opportunities, improvements and innovations in customer service, optimised operational efficiency and numerous other benefits.

The mechanics of big data analytics involve data scientists, predictive modellers and other analytics professionals analysing the large volumes of transaction data that are being generated every day, and also other forms of data that might be available but is untapped by conventional business intelligence activities. These might include server logs, social media content, clickstream data and numerous others.

Applying big data analytics to the travel industry

There is certainly no shortage of data within the travel industry. Enquiries, reservations, price comparisons, booking, check-ins and feedback for travel, accommodation, dining and leisure activities – every step from every traveller leaves a long stream of data.

This makes the travel industry an ideal environment for big data analytics to bring real business insights in the following areas and more.

Customer Service

Analysing data collected from online fora, call centre exchanges, social media platforms and other sources gives valuable information on overall consumer behaviour. This leads to a better understanding of buying patterns and customer likes and dislikes, which can in turn inspire new service offerings.


Personal data from social media platforms and other sources can tailor and focus the service offering around each individual’s needs and preferences, all delivered through the medium or device of their choice. This personalised level of customer service can bring customer relationships to a new level, leading to greater customer loyalty.

Pricing Strategy

While much has changed in recent years, price remains the main deciding factor when customers are making travel plans. Better and more detailed analysis of fare data and competitor pricing activities can revolutionize pricing strategies, bringing significant competitive advantage.

Targeted Marketing

Advanced data analysis provides insights that enable travel companies to offer the services that customers need at the time they are needed.

Revolutionizing Travel

There is no doubt that big data analytics can change the face of the travel industry. The advances seen over the past ten years are set to continue, and it is up to service providers to keep pace with their customers in order to remain relevant and competitive.


  1. Reply

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  2. alifaakter


    Awesome post. It is very informative and it is really interesting to increase our conversation rate. Thanks for sharing, it will be useful to everyone.

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