This study analyzes customer behavior on three most visited e-commerce platforms in Indonesia (Shopee, Tokopedia, and Lazada) using the RFM (Recency, Frequency, Monetary) model and K-Means clustering techniques. Amidst the digital transformation and rapid growth of e-commerce, significant changes in customer behavior highlight the importance of accurate and relevant customer segmentation. The study integrates demographic, psychographic, and purchasing behavior analysis, employing stratified random sampling to collect data over 6 months from 100 respondents on each e-commerce platform. The results revealed six customer clusters, each with distinct characteristics. These clusters were further analyzed to develop specific and effective marketing strategies tailored to customer behavior and preferences on each e-commerce platform.