Yapta is putting in the hands of travel buyers the point-of-sale data and rate-tracking data on which it has long based its reshopping prowess. It now feeds the data into an analytics platform powered by business intelligence company Tableau and hosted on Amazon cloud data warehouse Redshift. Travel buyers can use the analytics to target supplier negotiations and benchmark their rate competitiveness. "This is highly actionable pricing intelligence that can help companies move towards dynamic pricing technology, rather than negotiating every supplier contract through an RFP," said president and CEO James Filsinger.
Chief marketing officer Michael Smith told BTN the tool, called TravelAI, will launch as an add-on to the RoomIQ tool and will be available for use with FareIQ, Yapta's airfare reshopping tool, in the future. Early adopters are using it now, and Yapta plans to make it available to all clients in the fourth quarter.
Yapta's M.O. is to capture the rate a client's traveler books and monitor the global distribution system for better rates until the time of the trip. It offers the option of automatic rebooking for airfares and, Smith said, plans to enable the option for hotels in the future as clients optimize reshopping strategies with their travel agencies. Yapta also collects information on contracted rates from the traveler's company and sources clients' rates directly from the GDS and thus knows what rates were available to the traveler at the point of sale.
That data, which Yapta has until now maintained for its own purposes, can reveal spend trends and negotiated rate performance by hotel brand family, region, city and property for the travel buyer. "The first thing it does is it helps you target the right suppliers. We're going to look at your actual itinerary spend data and identify which are your top [for] spend by brand or by property so you can focus your RFP process on that—and which ones do you not need to worry about," Smith said. "The second thing we're going to do is do benchmarking on rate competitiveness. A lot of times people will negotiate a contracted rate but they don't know: Was that rate available, and if it was, was it the best rate I could have possibly gotten at the time the itinerary was booked?"
The analytics tool also can yield insight into traveler behavior and policy. "What did the traveler actually book? They may have chosen to book a more expensive room because it had different amenities," Smith said. "You want to know that so you can try to understand the question: Well, why would they do that? Was there a reason? Was my travel policy not effective for that particular traveler or that particular property?"
TravelAI uses both Amazon Web Services' stat-based data-digging tools and its machine learning capability, but Smith said it'll take a while for enough data to feed the machine learning side.