Augmented Reality (AR) based applications have existed for some time; however, their true potential in digital marketing remains unexploited. To bridge this gap we create a novel consumer targeting system. First, we analyze consumer interactions on AR-based retail apps to identify her preferred purchase viewpoint during the session. We then target the consumer through a personalized catalog, created by embedding recommended products in her viewpoint visual. The color and style of the embedded product are matched with the viewpoint to create recommendations, and personalized text content is created using visual cues from the AR data. Evaluation with user studies show that our system is able to identify the viewpoint, our recommendations are better than tag-based recommendations, and targeting using the viewpoint is better than that of usual product catalogs.