Many markets evolve through a constant stream of innovations that allow firms to improve the quality of existing goods or produce entirely new products. How much consumers gain from these new products, however, depends on the extent to which consumers are aware of these products and consider them before making a purchase. I propose an empirical framework that allows researchers to study the demand for new goods in markets where consumers might be imperfectly informed. Using this framework, I study new products in the U.S. hard drive market, a textbook example of a market with ample product innovation. I measure consumer information using unique browsing data that describes which hard drives consumers browse before making a purchase. To ease the computational burden of estimation, I develop and implement a novel Bayesian estimation method that efficiently handles consumer heterogeneity and scales to large numbers of products, thus allowing to accommodate massive product assortments commonly observed in modern online markets. The estimation results suggest that information frictions play an important role in shaping demand for new products. Limited adoption of new products can be mostly attributed to limited search and awareness rather than consumer preferences. These results emphasize the importance of economic policies and marketing strategies that aim to disseminate information about new products, thus helping consumers to reap all potential benefits from new product introductions.