Building a Conceptual Preference Model Based on Personal Purchase Records for Retail Service Improvement.

Retailers need to understand customer preferences precisely in order to improve customer satisfaction. This research aims to correct retailers’ conceptual misunderstandings of preference based on actual purchase behavior. To this end, a novel conceptual preference model is introduced. This model can be defined by persons on the basis of their own knowledge and is updated utilizing actual data of purchase behavior. Typical patterns of misunderstanding are classified into three types: incorrect relationship, weak relationship, and unexpected relationship. A novel method has been developed for evaluating the model to extract these patterns of misunderstanding and validated by conducting an experiment comprised of a cafeteria analysis. The conceptual model includes 11 preference types defined on the basis of retailers’ knowledge and was evaluated utilizing ID-POS data. Results showed that the three patterns of misunderstanding could successfully be extracted. It was confirmed that this method is helpful for retailers to understand the appropriate preference model and that a model built by using the proposed method can help improve the business processes in a retail setting.