The web may have commoditized tourism and travel, but data-driven decision-making is now adding significant value as travel companies understand more about their customers.
Until the web came along, travel and tourism consisted of travel reps doing the legwork to find the most appropriate travel options for their customers. The advent of online bookings disintermediated the travel booking process, enabling customers to do it for themselves. But something was lost in that transition.
Online booking enabled customers to search for their own trips and craft their own itineraries, but it removed the personalization and expertise traditionally offered by travel reps. This new process made it more difficult to delight customers with added value. Utilizing big data can bring the personal touch back to the travel industry, providing a competitive edge to innovative companies that embrace it.
Expedia, now the world’s biggest travel agency, came from a technology background—it was founded by Microsoft in 1996. The company is a good example of how travel firms can use data-driven decision-making to boost both the customer experience and their own sales, creating a tangible competitive edge.
With the help of data, Expedia can offer a wide range of different products—from hotels and air flights to structured tours—and create a plethora of potential packages for customers when booking a flight. Combinations of different options can range into the trillions from just a simple origin-and-destination data pair.
Big data can also assist travelers in other ways, particularly when it comes to safety. Prescient is a travel company that began in the federal sector, gathering thousands of structured and unstructured data feeds and distilling them into real-time information that helps advise travelers on emerging safety issues in their destination locations.
Expedia mines its data to understand implicit things about its customers. Are they families with children? How price conscious are they? Where have they traveled before? What have others with similar profiles enjoyed when traveling to these destinations?
Originally, the company used a traditional data warehouse, populating it with the extraction, transformation, and loading of structured data. Over time, Expedia realized it could derive more value from the mountains of data it collects from transactions and other nonstructured data sources.
Expedia wanted to put data analytics at the center of its business, which meant cataloging and analyzing more of it. To do this, it needed to expand from a traditional relational data warehouse. So they added in Apache Hadoop for the streaming of broader enterprise data into a data repository. The company also applied machine learning models and other big data analytics tools to help mine the repository for new insights in real time. The precision and timeliness of this data can help close sales.
The rapid surfacing of information is particularly important in the mobile space. Every minute, 200 or more Expedia mobile phone apps are downloaded around the world. The company has noticed that customers using the mobile app often need to book travel quickly—for example, they may be more location-focused, booking an emergency hotel near their area.
Expedia uses big data to find the most appropriate special offers and surface them instantly to mobile users in real time. It also uses its data lake to create smart itineraries in the mobile app with information that changes dynamically to reflect the latest travel conditions.
As the technology develops, you can expect to use big data more effectively in your travel business. The World Travel and Tourism Council (WTTC) identified several scenarios in which travel companies could use data-driven decision-making to their advantage.
For instance, travel reps could expand their role into data analysis, using a mixture of online behavior and travel history to better understand customer needs, and craft a more personalized travel experience. This extends into the trip itself, where an airline uses multiple data sources, including historical information and current travel plans, to seat the most appropriate airline passengers next to each other, facilitating new conversations and friendships. We may even see other innovations, such as the invention of new travel and tourism packages within a single season, based on emerging patterns in travel habits.
Travel companies are perfectly positioned to embrace big data analytics because of the huge amounts of information they already harvest from customer transactions. They can also take advantage of other available data sets that cover everything from the weather to flight information and even social media posts. By using big data analytics for data-driven decision-making, travel companies can become far more than simple booking and fulfillment services. They can transform themselves into trusted travel partners, ready to advise and assist customers when and where they need it most. What better way to create loyalty—and increase revenue—in a highly cost-sensitive industry?
Learn more about Expedia’s successes with the help of big data and see how you can follow in its footsteps.