Customer Clustering Based on Cooking Tendency Features Using ID-POS Data

Abstract

In this presentation, we use ID-POS data of food retail stores to create features that lead to prediction of cooking tendencies, and based on these features, we analyze the characteristics and preferences of customers in each group through clustering. In particular, we discuss the purchasing tendencies and characteristics of customers who are expected to cook for themselves and those who are expected to rarely cook for themselves.