While there are many commercial systems designed to help people browse and compare products, these interfaces are typically product centric. To help users more efficiently identify products that match their needs, we instead focus on building a task centric interface and system. With this approach, users initially answer questions about the types of situations in which they expect to use the product. The interface reveals the types of products that match their needs and exposes high-level product features related to the kinds of tasks in which they have expressed an interest. As users explore the interface, they can reveal how those high-level features are linked to actual product data, including customer reviews and product specifications. We developed semi-automatic methods to extract the high-level features used by the system from online product data. These methods identify and group product features, mine and summarize opinions about those features, and identify product uses. User studies verified our focus on high-level features for browsing and low-level features and specifications for comparison.