Four studies show that consumers have not one but two distinct learning processes that allow them to use brand names and other product features to predict consumption benefits. The first learning process is a relatively unfocused process in which all stimulus elements get cross-referenced for later retrieval. This process is backward looking and consistent with human associative memory (HAM) models. The second learning process requires that a benefit be the focus of prediction during learning. It assumes feature-benefit associations change only to the extent that the expected performance of the product does not match the experienced performance of the product. This process is forward looking and consistent with adaptive network models. The importance of this two-process theory is most apparent when a product has multiple features. During HAM learning, each featurebenefit association will develop independently. During adaptive learning, features will compete to predict benefits and, thus, feature-benefit associations will develop interdependently. We find adaptive learning of feature-benefit associations when consumers are motivated to learn to predict a benefit (e.g., because it is perceived to have hedonic relevance) but find HAM learning when consumers attend to an associate of lesser motivational significance.