Improving results in a Hotel Search App
This fall, I had the opportunity to work on a team with one other data scientist and two Sloan MBA students to develop a new algorithm for a travel-booking app. The firm we worked with has a strong history working in flight bookings, but recently created a new line of business in hotels.
For our project, the firm asked us to explore how to best order hotel search results in order to maximize the number of bookings made through the app. Currently, they use a simple but effective approach of getting the likelihood of a hotel being booked using a logistic regression and then ordering hotels from most to least probable. Their data science team gave us access to around eleven million rows of user data encapsulating search and booking behavior.