This paper analyzes search frictions in online markets using novel data on the web browsing and purchasing behavior of a large panel of consumers. This dataset is unique in that consumer search behavior prior to a transaction is observed. Although recent models have shown that large price dispersion persists in various markets, and this dispersion is directly related to the magnitude of consumer search costs, little attention has been given to quantifying these costs. I use data on consumers shopping for books online to link prices and consumer search patterns at different bookstores to estimate consumer search costs in the context of an equilibrium search model. The search patterns indicate that consumers visit relatively few firms and exhibit a strong search preference for prominent retailers. I control for search intensities at different retailers during consumers’ search process and find that search cost estimates are lower than when assuming consumers sample equally among alternatives. Accounting for unequal consumer search reduces search cost estimates in half from $1.8 to $0.9 per search. I examined the search cost heterogeneity by using a rich set of consumer characteristics and relating them to search patterns and search costs estimates. I use a flexible random effects model in which the number and order of firms visited by the consumer is her optimal ordered choices, allowing search cost cutoffs to depend on regressors. The estimates indicate that consumer search costs are related to their observable characteristics, such as income, where individuals with income greater than $100,000 incur relatively higher search costs.