BEHAVIORAL SEGMENTATION OF CUSTOMERS: RFM MODEL AND K-MEANS APPLICATION

The demand for building sustainable customer-company relationships within the context of fierce competition is increasing, in which lingerie is no exception. Segmentation is one of the methods to help businesses build long-term relationships with customers. The main goal of this study is to propose a customer segmentation approach based on RFM (recency, frequency, and monetary) model and K-means algorithm, and then use the one-way ANOVA test to explore the difference in recency, frequency, and monetary attributes in customers of different ages. Data was collected from transactions of 5,280 customers at a lingerie brand store in Vietnam. The results showed that customers are classified into three clusters: loyal customers, irregular low-end customers, and potentially loyal customers. Older customers spend the highest sums of money on lingerie products and the longest time since their last interaction with a company while young customers have the highest purchase frequency. This article contributes to the lingerie industry by providing possible explanations for the behavior of customers from different age groups. It also contributes to the establishment of a suitable method for customer segmentation.