The consideration of preference heterogeneity in consumer choice behavior has become state of the art. In addition, the identification of consumer segments remains essential for marketing managers. For disaggregate consumer choice data representing the basis of segmentation, the latent class multinomial logit (MNL) model is currently the most popular approach for estimating segment-specific preferences. After addressing the theoretical background of the latent class MNL model, we use an empirical choice-based conjoint data set to illustrate model estimation and validation, as well as how the estimation results should be interpreted. A particular focus lies on the model selection process, i.e. the determination of an appropriate number of segments. We further work out interpretation pitfalls when the existing preference heterogeneity of consumers is ignored. This will ultimately provide a guide for applying the latent class MNL model regarding model selection, estimation, validation, and interpretation of results both from a statistical and managerial perspective.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.