Landing Page Personalization at Expedia Group

Recommender systems have become critical tools for e-commerce businesses in recent years and online travel platforms such as Expedia Group have made heavy use of them in production. Contemporary travel platforms benefit greatly from the use of recommender systems as very often the space of products (trips) is quite large and shopping cycles often stretch into the weeks. Expedia Group has successfully trained and deployed multiple types of recommender systems in order to help our travelers find the perfect destination and property for them. In recommender systems literature, much attention is paid to the mathematical aspects of the field but here we focus on best practices in applying recommender systems in large-scale e-commerce for the improvement of browsing and shopping experiences. In this paper, we describe how we personalize the user experience on a number of our core pages by exploiting existing internal recommender systems and relevant recommender system literature. Additionally we note several critical lessons learned about the importance of a robust machine learning platform, the need to apply engineering best practices and how best to integrate and test recommender systems in production.