Customer Segmentation for Online Retailers with K-Means Clustering

This project implements K-Means clustering to segment customers of an online retail store based on browsing and purchasing behavior. The clustering algorithm groups customers based on factors like product preferences, frequency of visits, and average transaction value. The segmentation results help online retailers target specific customer groups with personalized marketing campaigns.