Classification models have implicitly assumed that the nature of the representation that emerges from encoding will determine the type of classification strategy that will be used. These experiments, however, demonstrate that differences in classification performance can occur even when different transfer strategies operate on identical representations. Specifically, a series of examples was presented under incidental concept learning conditions. When the encoding task was completed, subjects were induced to make transfer decisions by analogy to stored information or to search for and apply rules. Across four experiments, an analogical transfer mode was found to be more effective than a rule-based transfer mode for preserving co-occurring features in classification decisions. This result held across a variety of category structures and stimulus materials. It was difficult for subjects who adopted an analytic transfer strategy to test hypotheses and identify regularities that were embedded in stored instances. Alternatively, subjects who adopted an analogical strategy preserved feature covariations as an indirect result of similarity-based retrieval and comparison processes.