Published Paper Details:

This project delves into the application of RFM (Recency, Frequency, Monetary) analysis for customer segmentation, utilizing Python as the primary analytical tool. Beginning with a theoretical overview, it highlights RFM's significance in modern marketing, emphasizing its role in understanding customer behavior. Through Python's data analysis capabilities, the project demonstrates the extraction of insights from transaction data, ensuring accuracy through meticulous cleaning procedures. By computing RFM scores, it enables the segmentation of customers, facilitating targeted marketing and resource allocation. Visualization techniques are explored to represent segmentation results intuitively. Practical implications are discussed, showcasing how businesses can enhance customer-centric strategies through RFM analysis and Python programming. Ultimately, the project underscores the transformative potential of these tools in reshaping customer relationship management paradigms, empowering businesses to navigate the complexities of the digital age effectively.