This research proposes a decision aid based on a novel type of preference relaxation, which enables consumers to easily make quality choices in online multiattribute choice scenarios. In contrast to filtering and recommendation mechanisms that are a potential solution to this problem, our method combines decision theory with preference relaxation and enables consumers to consider high-quality alternatives they initially eliminated. We compare our approach with existing methods using a set of 2650 car advertisements gathered from a popular advertiser website. We discuss the potential impact of our method on decision quality and give an overview of implications for practitioners and researchers. Key words: Decision Theory, Recommender Systems, Preference Relaxation, eCommerce