This study was conducted using Python and libraries such as pandas, scikit-learn, and matplotlib. A limitation of the study lies in the moderate silhouette score, which indicates room for improvement ...

Use RFM analysis to identify your most valuable customers and create more targeted marketing campaigns.

RFM Analysis Dashboard Overview This project demonstrates the creation of an RFM (Recency, Frequency, Monetary) Analysis Dashboard using Python. The dashboard provides visual insights into customer ...

Installing universally necessary libraries such as pandas, numpy, seaborn, matplotlib. Also, openpyxl was installed to help read the Excel file better.

Stop wasting ad spend on the wrong audiences. Use RFM analysis to identify your most valuable customers and optimize your PPC campaigns.

The technique of examining the attributes of customers and creating groups based on some specific characteristics is known as customer segmentation. Customer segmentation is a methodology employed to ...

This RFM score tells you which segments of customers are the most valuable, and what kinds of messages these customers need the most. What Are the Benefits of an RFM Analysis? An RFM Analysis provides ...