New Conjoint Approaches to Scaling Brand Equity and Optimising share of Preference Prediction

Ratings-based conjoint analysis suffers two problems: the distortion raised by consumer perceptions of brand equity, and the lack of efficiency of probabilistic models for estimating preference shares. This article proposes two new approaches to scale customer-based brand equity using repeated measures and structural equation modeling and to estimate the share of preferences on the basis of a randomized first choice. The outcome is a new tool to predict accurate preference shares, taking into account product utilities (estimated by rating-based conjoint analysis) and the brand equity related to product attributes (estimated as a latent variable with structural equation modeling). An example with three products illustrates this new approach.