Building Models for Marketing Decisions

This book is about marketing models and the process of model building. Our primary focus is on models that can be used by managers to support marketing decisions. It has long been known that simple models usually outperform judgments in predicting outcomes in a wide variety of contexts. For example, models of judgments tend to provide better forecasts of the outcomes than the judgments themselves (because the model eliminates the noise in judgments). And since judgments never fully reflect the complexities of the many forces that influence outcomes, it is easy to see why models of actual outcomes should be very attractive to (marketing) decision makers. Thus, appropriately constructed models can provide insights about structural relations between marketing variables. Since models explicate the relations, both the process of model building and the model that ultimately results can improve the quality of marketing decisions. Managers often use rules of thumb for decisions. For example, a brand manager will have defined a specific set of alternative brands as the competitive set within a product category. Usually this set is based on perceived similarities in brand characteristics, advertising messages, etc. If a new marketing initiative occurs for one of the other brands, the brand manager will have a strong inclination to react. The reaction is partly based on the manager's desire to maintain some competitive parity in the mar keting variables.

1 Introduction. - 2 Classifying marketing models according to degree of explicitness. - 3 Benefits from using marketing models. - 4 A typology of marketing models. - 5 Elements of model building. - 6 Marketing dynamics. - 7 Implementation criteria with respect to model structure. - 8 Specifying models according to intended use. - 9 Specifying models according to level of demand. - 10 Specifying models according to amount of behavioral detail. - 11 Modeling competition. - 12 Stochastic consumer behavior models. - 13 Multiproduct models. - 14 Model specification issues. - 15 Organizing Data. - 16 Estimation and testing. - 17 Special topics in model specification and estimation. - 18 Validation. - 19 Determinants of model implementation. - 20 Cost-benefit considerations in model building and use. - 21 Models for marketing decisions in the future. - Author Index.