In many online markets, platforms engage in platform design by choosing product recom-
mendation systems and selectively emphasizing certain product characteristics. I analyze the
welfare effects of personalized recommendations in the context of the online market for hotel
rooms using clickstream data from Expedia Group. This paper highlights a tradeoff between
match quality and price competition. Personalized recommendations can improve consumer
welfare through the “long-tail effect,” where consumers find products that better match their
tastes. However, sellers, facing demand from better-matched consumers, may be incentivized to
increase prices. To understand the welfare effects of personalized recommendations, I develop
a structural model of consumer demand, product recommendation systems, and hotel pricing
behavior. The structural model accounts for the fact that prices impact demand directly through
consumers’ disutility of price and indirectly through positioning by the recommendation system.
I find that ignoring seller price adjustments would cause considerable differences in the estimated
impact of personalization. Without price adjustments, personalization would increase consumer
surplus by 2.3% of total booking revenue (∼$0.9 billion). However, once sellers update prices,
personalization would lead to a welfare loss, with consumer surplus decreasing by 5% of booking
revenue (∼$2 billion).