Loyalty Improvement of Indonesian Local Brand Fashion Customer Based on Customer Lifetime Value (CLV) Segmentation

Abstract

There has been a significant growth of internet users over the past decade in Indonesia. The growth of internet users is followed by the growth of digital buyers. Most digital buyers in Indonesia make some transactions to purchase clothing which explains the phenomenon of e-commerce fashion growth. This study aims to identify the loyalty level of an electronic customer based on Customer Lifetime Value (CLV) of the customer segmentation and design the CLV improvement. Customer segmentation performed using the K-means algorithm and RFM analysis. This paper used 3 transaction datasets from 3 different local brand fashion e-commerce in Indonesia. This study found five customer segmentations according to CLV ratings as the best, valuable, potentially valuable, average, and potentially invaluable customer. Maintaining customer convenience while doing the transaction and improving service quality and customer trust are the keys to retaining potentially valuable, average, and potentially invaluable customers.