Everyone loves traveling, but everyone hates packing. For the other hassles of going on vacation—choosing a hotel, looking for restaurants, planning entertainment—artificial intelligence is being put to work on making our holidays more relaxing.
“Ideally you’ll get two trips in front of you and you can just choose and then everything will be planned and booked and actually you don’t need to think about it anymore,” says Gillian Tans, chairwoman for the Amsterdam-based Booking.com.
Tans was describing to the audience at the Fortune Global Tech Forum in Guangzhou what the world of travel will look like in 10 years time—at least in her ideal scenario. To get there, Booking.com is already embracing advances in technology that help the online travel agent personalize its services: namely machine learning, or A.I.
“Because Booking.com has always been so extremely data driven, the step into machine learning [has been ongoing] for many years. Every customer touches machine learning today,” Tans says.
Machine learning can personalize suggestions beyond the level most people experience today. For instance, based on customer data A.I. can select different hotel photos to show as preview snaps to different travelers viewing the same accommodation.
Even the customer reviews displayed at the bottom might be different based on what the algorithm knows about the customer. These personalization efforts are “extremely” important in converting a visit to Booking.com into a sale, Tans says.
Advanced algorithms already power Booking.com’s recommendation services—upselling customers who reserve hotels on entertainment or restaurant suggestions, for example.
Tans describes these sales pushes as building a “connected trip” rather than cross-selling. The two look the same to any layman but Tans makes a distinction in the amount of friction the two systems introduce to the checkout process.
“I think you realize yourself if you want to take a long trip it takes enormous time to even plan and get everything good and that’s actually where the friction that is still out there. We’re trying to reduce the time and make it much more efficient for consumers to do that,” Tans says.
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