Then there is personalisation. Could a machine learning algorithm learn your preferences and travel habits over time and cut steps out of the buying process?
Fleischman says that the business is running experiments with personalisation. "Personally," he sighs, "it is something we need to look into but it is not necessarily something we know is the right thing as people just want to browse. So we think more about customisation and detailed acknowledgement of where you are in your thinking."
Put another way, where you are in the buying process is more important to Expedia than whether you like an aisle seat, at least at this point.
Nurturing machine learning talent
When it comes to hiring data scientists, Expedia puts a premium on problem solving skills.
"The trick with machine learning is the people not the code, the important bit is to understand the consumer problem," Fleischman says.
This chimes with the perspective of Nuno Castro, director of data science at Expedia, who recently told Computerworld UK: "People who can understand the organisation from a commercial perspective, and who create relevant relationships in the organisation will be more successful."
Expedia works in agile teams, typically made up of a technologist, a product manager, a user experience designer, and according to Fleischman, machine learning experts are part of these core problem solving teams. Expedia doesn't dictate which tools they use or how they approach the problem.
And as Castro told us previously: "You and your team will typically be set a high level objective for which you need to determine the best cause of action. Unlike other areas, there is no one recipe for data science. Often you are not trying to find the right answer to a question, you're trying to find the right questions to ask in the first place."
Sign up for CIO Asia eNewsletters.