Mobile recommendation agents (MRA) are a new class of decision support systems that provide consumers with product information during purchase situations in stores. They allow merging of local information with global information provided by online content sources. Currently design criteria for MRA are missing. Studies on purchase decision support systems indicate the importance of price, single product quality, and attitude on buying intentions. It is assumed that purchase decision tasks on price bundles increase utility effects of MRA. We present an empirical study that investigates the impact of cues on price, bundle quality, and discount provided by MRA on consumer’s buying intentions in comparison with interpersonal sales communication between consumer and sales personnel. Our results show that MRA can be used to inform consumers about bundle qualities under best-value strategy conditions, which will be used for future MRA designs.