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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 todoi:10.1080/09593960110045413 fatcat:atzoug5uzvfrrhpthgkbdcyrdm