The authors propose a new approach to obtaining stockkeeping-unit (SKU)-level preferences and response sensitivities. The authors distinguish an attribute-level model, in which the unit of analysis is the market share for an alternative created by aggregation (e.g., Colgate toothpaste), from a truly disaggregate SKU-level model, and they establish an analytical relationship between parameters that they obtain from the two models. The authors show that SKU-level parameters can be recovered by calculation from estimated attribute-level parameters, circumventing the need for direct estimation of the more complex SKU-level model. They calibrate the store data market share model using 98 weeks of data for ten brands and 168 SKUs of toothpaste. Rather than estimate 168 preference parameters (when there is an “outside” alternative in addition to the 168 “inside” ones), it is only necessary to estimate ten brand-preference parameters from which the 168 parameters can be computed, as long as share and marketing-mix data are available at the SKU level. Covariate effects, such as marketing-mix response parameters, can be recovered in a similar fashion. Holdout tests demonstrate superior predictive performance, and the authors discuss implications for the derivation of elasticities for new SKU introductions.
Consumer Brand Preference: An Empirical Study of Car Buying in Nepal
