We call it Preference-Driven Air Shopping. This tool, which we’ve covered in other applications, was created by the Sabre Research team to deliver a consistent and repeatable experience for travelers. Rather than having to search by the standard time/date criteria, the app makes it possible for a variety of factors to be weighted in a particular search. An algorithm allows for these various weightings and then delivers a curated collection of search results related to the user’s self-directed preferences.
For business travelers, this can prove especially fruitful. As most frequent fliers know exactly what they want (for example, which seat on which particular aircraft), this makes travel search much more efficient for those who travel often.
For companies managing travelers, there is also an added benefit: travel policy rules can be integrated as preferences, and adjusting each weighting allows for more granular control of what’s being booked. This not only empowers the traveler to make his or her own travel decisions but also gives that traveler the right information related to what’s also best for the company.
We spoke with team lead Rajeev Bellubbi about the latest application of Preference-Driven Air Shopping — within the GetThere corporate travel booking tool.
For those who are unfamiliar, what is PDAS?
Preference Driven Air Shopping (PDAS) is a display algorithm to optimize the screen real estate and display the best itineraries based on a user’s preferences, either explicitly specified by the user or implicitly “learned’ by user behavior and trip purpose. It is an algorithm that employs a multi-dimensional sort that replaces the filter and single attribute sort of a typical air shopping display.
So for example: A shopper wants a cheap, nonstop flight departing between 9:00am and 11:00am. If an ideal flight is not available during the preferred time window (9:00 – 11:00am), but exists at 8:50 am, this itinerary would not be filtered out and displayed as a highly desirable itinerary to the user. This is particularly useful in mobile displays where screen display area is limited and we want to show the user his/her top choices.
How does this application work, specifically in the case of the business traveler using GetThere?
In addition to the typical flight attributes, such as fare, flight time, departure/arrival times, connections, we can model the company’s corporate travel compliance rules as preferences. So, instead of using corporate compliance as a hard filter, we can provide every choice with a degree of corporate compliance based on an importance weight. This weight can be varied based on the importance of travel or traveler.
What this means, is that the booking tool can be molded to fit each organization. Each company has its own priorities when it comes to travel policy. Perhaps there are some truly inviolable rules, or perhaps there is a blend of in-policy and out-of-policy that works best. This tool makes it possible for that nuanced view to exist within the corporate travel booking portal.
Why is this an improvement on the traditional way that a business traveler searches for airfare?
In the traditional business travel scenario, corporate compliance is used as a hard filter. In PDAS for business travel, we have replaced this hard filter with degrees of compliance, which work together with the traveler type (road warrior, infrequent traveler, executive, etc.) and travel importance to quickly provide the ideal itinerary. The preference and attribute weights can be defined and specified at a corporation level by the company’s travel department.
Looking ahead, how will preferences be folded into the overall travel search experience?
Going forward we envision that most of the preferences can be used from the user profile(s) and trip purpose. We also think that this would be a continuously learning process where the preference profiles would be modified based on traveler behavior and used to provide the ideal shopping experience.