K-Means Clustering Approach for Intelligent Customer Segmentation Using Customer Purchase Behavior Data

E-commerce system has become more popular and implemented in almost all business areas. is a platform for marketing promoting the products to customer through online. Customer segmentation known as process of dividing customers into groups which shares similar characteristics. The purpose determine how deal with each category order increase profit business. Segmenting assist identify their profitable satisfy needs by optimizing services products. Therefore, helps promote right product intention profits. There are few types factors demographic psychographic, behavioral, geographic. In this study, behavioral factor been focused. Therefore users will be analyzed using clustering algorithm determining purchase behavior system. aim optimize experimental similarity within cluster maximize dissimilarity between clusters. study there relationship three clusters: event type, products, categories. research, proposed approach that share criteria help vendors focus on high segment least segment. This type analysis can play important role improving Grouping according sustain long-term profit. It also enables exposure e-offer gain attention potential customers. collected data customers, an learning used K-Means clustering. solve problems.