A Study of Situated Product Recommendations in Augmented Reality
Brandon Huynh, Adam Ibrahim, Yun Suk Chang, Tobias Höllerer, John O’Donovan · 2018
Augmented Reality interfaces increasingly utilize artificial intelligence systems to tailor content and experiences to the user. We explore the effects of one such system - a recommender system for online shopping - which allows customers to view personalized product recommendations in the physical spaces where they might be used. We describe results of a 2x3 condition exploratory study in which recommendation quality was varied across 3 user interface types. Our results highlight potential differences in user perception of the recommended objects in an AR environment. Specifically, users rate product recommendations significantly higher in AR and in a 3D browser interface, and show a significant increase in trust in the recommender system, compared to a web interface with 2D product images. Through semi-structured interviews, we gather participant feedback which suggests AR interfaces perform better due to their ability to view products within the physical context where they will be used.