Retrieving unobserved consideration sets from household panel data

We propose a new model to describe consideration, consisting of a multivariate probit model component for consideration and a multinomial probit model component for choice, given consideration. The approach allows one to analyze stated consideration set data, revealed consideration set (choice) data or both, while at the same time it allows for unobserved dependence in consideration among brands. In addition, the model accommodates different effects of the marketing mix on consideration and choice, an error process that is correlated over time, and unobserved consumer heterogeneity in both processes. We attempt to establish the validity of existing practice to infer consideration sets from observed choices in panel data. To this end, we collect data in an on-line choice experiment involving interactive supermarket shelves and post-choice questionnaires to measure the choice protocol and stated consideration levels. We show with these experimental data that underlying consideration sets can be reliably retrieved from choice data alone. Next, we estimate the model on IRI panel data. We have two main results. First, compared with the single-stage multinomial probit model, promotion effects are larger when they are included in the consideration stage of the two-stage model. Second, we find that consideration of brands does not covary greatly across brands once we account for observed effects.