CUSTOMER SEGMENTATION ANALYSIS BASED ON THE CUSTOMER LIFETIME VALUE METHOD

Abstract

Companies need to understand the customers’ data better in all aspects. Detecting similarities and differences among customers, predicting their behaviors, proposing better options and opportunities tocustomers became very important for customer-company engagement. Companies need a database of customer that contains customer information in detail, one of which is data about the potential value of each customer.Customer Lifetime Value (CLV) measures the potential value of each customer from the perspective of a service or product provider.This study aims to analyze Customer Lifetime Value (CLV) of the customer and clustering it into customer segmentation using the K-means cluster method.The results showed the highest average CLV value with is Rp 19,170,991,- and the lowest average value is -Rp 112,566,-. The customer clustering produced in this study isfour segmentswith the majority of customers at cluster 3 segment low with 51 unit population.