Development and Testing of a Model of Consideration Set Composition

Abstract

The authors develop a model of consideration set composition. The approach taken is to compare the marginal expected benefits of including an additional brand in the consideration set with its associated costs of consideration. From an expression of the utility that a brand needs to gain membership in an existing consideration set, the authors derive an expression for set composition and optimal set size. They develop a measurement method to test the model at the individual level and apply it to the ready-to-eat cereal market. The model is tested in two ways. First, the utility function is calibrated at the individual level and the model is used to predict consideration of existing brands. The calibrated model also is used to forecast individual consideration of three new product concepts. Second, the predictive ability of a two-stage model of consideration and choice is tested against a traditional one-stage choice model. The authors conclude with a discussion of management implications of the model in terms of auditing currently available brands and new product management.