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The authors propose a new incentive-aligned upgrading method for eliciting attribute preferences in complex products, which combines the merits of a self-explicated approach and conjoint analysis. The upgrading method first endows a participant with a product profile and then allows him or her to upgrade it, one attribute at a time, to a more desirable product configuration. During the process, the participant states his or her willingness to pay for each potential upgrade he or she is interested in, and a BDM (Becker–DeGroot–Marschak) procedure ensures that it is in the best interest of the participant to state truthfully his or her willingness to pay. Each participant receives the upgraded product at the end of the study. The authors empirically implement this procedure in a Web-based study with digital cameras. This procedure significantly improves predictive performance over the benchmark (self-explicated) approach.