Retail Sales Analysis with Customer Segmentation is a Python project that combines sales data cleaning with K-Means clustering to uncover distinct customer groups. The pipeline automatically cleans raw retail data (handling duplicates, missing values, and date formatting), aggregates transactions to the customer level, and applies RFM analysis (Recency, Frequency, Monetary) to quantify purchasing behavior. From there, K-Means clustering groups customers into segments based on behavior, demographics, and engagement patterns turning messy raw sales data into targeted business strategies for each customer group.