Recommender systems have emerged as an effective decision tool to help users more easily and quickly find products that they prefer, especially in e-commerce environments. However, few studies have tried to understand how this technology has influenced the way users search for products and make purchase decisions. Our current research aims at examining the impact of recommenders by understanding how recommendation tools integrate the classical economic schemes and how they modify product search patterns. We report our work in employing an eye tracking system and collecting users' interaction behaviors as they browsed and selected products to buy from an online product retail website offering over 3,500 items. This in-depth user study has enabled us to collect over 48,000 fixation data points and 7,720 areas of interest from eighteen users, each spending more than one hour on our site. Our study shows that while users still use traditional product search tools to examine alternati...