A method (200) of eliciting customer preference from purchasing behavior surveys clusters (210) survey respondents into two or more clusters according to a data pattern identified in a dataset (330) of responses to survey questions that include a question regarding a product purchasing decision, and questions regarding respondent attributes (such as behavioral questions) and product attributes. Clustering (210) may be performed based on responses to behavioral questions that are not endogenously linked to any control variables. A model for each cluster, relating purchasing decision responses to product attribute responses, is produced (220), and each model is used to generate (230) projected purchasing decision responses for each cluster by replacing a value relating to a response to a selected product attribute question, which may be a control variable, with an alternative value. The dataset is transformed (240) by replacing purchasing decision responses with the projected responses. Survey respondents are then re-clustered (250), and duster shift is analyzed (260).