E-Commerce Sales And Customer Behavior Analysis

This paper proposes an integrated data analytics framework for e-commerce sales and customer behavior analysis using open-source tools. It combines exploratory data analysis, RFM-based customer segmentation, K-means clustering, churn prediction, sales forecasting, and market basket analysis to generate actionable business insights. An interactive Streamlit dashboard is developed to support data-driven decision-making, helping e-commerce businesses improve customer retention, marketing effectiveness, and profitability.