eye-tracking product recommenders' usage
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 alternatives, recommenders definitely provide users with new opportunities in their decision process. More specifically, users actively click and gaze at products recommended to them, up to 40\% of the time. In addition, recommendation areas are highly attractive, drawing users to add 50\% more items to their baskets as a traditional tool does. Observing that users consult the recommendation area more as they are close to the end of their search process, it seems that recommenders enhance users' decision confidence by satisfying their need for diversity. Based on these results, we derive several interaction design guidelines that can significantly improve users' satisfaction and perception of product recommenders.
user studies attention usage patterns decision theory time-dependent model of diversity