Segmentation and Formation of Customer Regression Model Based on Recency, Frequency and Monetary Analysis

During this pandemic, the number of customers a securities company has increased quite high. This requires companies to conduct analysis related security customer data against transaction so that can find out segmentation registered and also predict patterns in company. In processing data, RFM (Recency, Frequency, Monetary) model be used as way group according their business values. After doing modeling using RFM, is clustered K-Means algorithm each group. The been will produce segments based on linear regression process carried where segment analyzed predicted variables such recency, monetary frequency. results grouping, predictions with one company's references make decision. From attributes, prediction value existing recency generated frequency known fairly good error rate.