Customer Segmentation_FMF_Analysis

This project applies RFM (Recency, Frequency, Monetary) analysis to customer transaction data from an online retail dataset.

It segments customers into actionable groups such as loyal, high-value, and at-risk customers.

The analysis leverages Python (Pandas, NumPy, Matplotlib, Seaborn) in Jupyter Notebook to clean data, compute RFM scores, and visualize customer segments.

The insights can be used to design targeted marketing strategies, improve customer retention, and maximize business value.