Correcting for CBC model bias: a hybrid scanner data – conjoint model

Martin Natter, Markus Feurstein
2001 International Review of Retail Distribution & Consumer Research  
Choice-Based Conjoint (CBC) models are often used for pricing decisions, especially when scanner data models cannot be applied. Up to date, it is unclear how Choice-Based Conjoint (CBC) models perform in terms of forecasting real-world shop data. In this contribution, we measure the performance of a Latent Class CBC model not by means of an experimental holdout sample but via aggregate scanner data. We find that the CBC model does not accurately predict real-world market shares, thus leading to
more » ... es, thus leading to wrong pricing decisions. In order to improve its forecasting performance, we propose a correction scheme based on scanner data. Our empirical analysis shows that the hybrid method improves the performance measures considerably.
doi:10.1080/09593960110045413 fatcat:atzoug5uzvfrrhpthgkbdcyrdm