Customer Segmentation Using K-Means Clustering Algorithm and RFM Model

The key points in customer segmentation are determining target groups and satisfying their needs. Recency-Frequency-Monetary (RFM) analysis K-Means clustering algorithm the popular methods for when analyzing behavior. In our study, we adapt K-means to RFM model by extracting features that represent aspects of home appliances. Customers with similar RFM-oriented assigned same clusters, while customers non-similar different clusters. experiments, achieved determined threshold Silhouette Score. resulting clusters were ranked named Customer Lifetime Value (CLV) metric, which measures how valuable a is business.