Recommender Systems for Personalized User Experience: Lessons learned at Booking.com

ABSTRACT Booking.com is the world’s leading online travel platform where users make many decisions supported by our recommendations, such as destinations, travel dates, facilities, etc. This leads to a complex User Interface (UI) containing many widgets of different relevance for different users. We address the problem of constructing an optimal UI, a non-trivial problem, mainly due to user preferences evolving over time and multiple independent teams collaboratively building the UI. Our goal is to provide a personalized User Experience (UX) which adapts to changes in the environment and ensures governable, collaborative product development. The solution relies on a Multi Armed Bandits (MAB) framework currently allowing product teams to collaborate on the construction of UIs and serving millions of users every day. We present examples of our solution and lessons learned during their implementation.