I study how the information a search intermediary has about consumer preferences impacts the market. Consumers participate in costly search among different sellers’ products, relying on the rankings order provided by the intermediary based on their preferences. Better product targeting affects consumer search and purchases, which, in turn, changes the seller pricing incentives. I considered these aspects by modeling both sides of the market under various ranking algorithms used by the intermediary. On the demand side, I developed a joint model of consumer costly search and purchase. On the supply side, I considered the sellers’ pricing competition. To estimate the demand and supply models, I utilized a rich dataset provided by Expedia, which includes consumer search and purchase data and information on the hotels and prices they charge. I find that if the intermediary uses data on consumers’ preferences to provide them personalized rankings of products, consumers, on average, experience a 3.6% ($4.9) utility decrease due to increased transaction prices, a 0.8% ($1.1) utility gain due to a reduction in search spending, and 0.5% ($0.7) utility gain due to finding a better-fitted hotel.