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.
|Journal||IOP Conference Series: Materials Science and Engineering|
|Publication status||Published - 9 Sep 2019|
|Event||Joint Conference of the 6th Annual Conference of Industrial and System Engineering 2019, ACISE 2019 and 1st International Conference on Risk Management as an Interdisciplinary Approach 2019, ICRMIA 2019 - Semarang, Central Java, Indonesia|
Duration: 23 Apr 2019 → 24 Apr 2019