For the past few years, the travel industry has been exploring innovative ways to utilize artificial intelligence (AI), in an effort to unlock the promise of more efficient communications and greater customer service between travelers and service provides.
So far, most of that potential has remained largely untapped, despite significant advances in both travel and AI sectors. WayBlazer however, is building an extremely powerful travel recommendation engine, and it’s doing it with a little help from AI.
WayBlazer’s Travel Graph uses artificial intelligence to learn about tens of millions of travel products and thousands of global destinations. It ingests and extracts useful from descriptions, reviews, blogs, images, and videos to develop a frame of travel intelligence that’s used to power the most relevant recommendations for today’s travelers.
By using machine learning models, their travel graph gets smarter with every user search. The result is a recommendation engine that understands travel like an expert, factoring both context and search intent.
“Studies show that travelers on average search 140 travel sites 45 days before booking. And that’s not just bad for travelers. Hotels, vacation-packaging groups and other travel-industry companies are losing potential customers due to an unengaging digital experience that doesn’t convert.” Terry Jones, chairman of WayBlazer Inc.
Adding artificial intelligence – or AI – to that search, and things change, says Jones, who also founded Travelocity. Artificial intelligence is essentially a computer system that can perform tasks that normally would require a human, such as voice recognition, visual perception, and decision making.
HOW AI IS TRANSFORMING TRAVEL PLANNING
Machines can learn. Over time machine learning detects patterns in the data it collects and makes adjustments in its “knowledge.” So every time a traveler searches, the WayBlazer system gets a little smarter. “The result,” Jones says, “is a recommendation engine that understands travel like an expert, factoring in both context and search intent to the results a traveler gets.”
Travelers on average search 140 travel sites 45 days before booking.
Relevant images and reviews. Machine vision can “look” at a photograph and match it to what you’re searching for. For example, a traveler searching for an anniversary trip should be seeing images and reviews of romance: whether its couples on the beach or enjoying a candlelight dinner. Showing the right evidence dramatically improves engagement and user experience.
AI is conversational. Online searches typically involve keywords that need to match words on websites. However, with natural language searches, travelers don’t have to type the exact right words to get their desired results. Natural language search, especially when searching for multi-faceted trip experiences, gives travelers much more flexibility when searching for a brand’s products. And travel agents are also able to rely on AI to give their customers better service and do it faster.
“A lot of brands are figuring out that customers want a better digital experience in the planning stage – and the vacation-inspiration stage – and they can help travelers,” he says. “If they can do that, and provide a more personalized experience every step of the way, then those customers are going to be loyal to that brand.”