Examining the purchasing habits of customers and segmenting according to these habits.

This repository is for data and codes for paper @JAMA-IM 2022 Receny of Online Physician Ratings

Hypothesizes that customers who have made a purchase recently, make regular or frequent purchases with you and spend a large amount with you, are more likely to respond positively to future engagement and product offers. This might seem intuitively obvious to those of us who have experience in sales – but what the RFM model brings to the table i…

🔷 Customer Segmentation Using RFM Analysis 🔷 This project applies RFM (Recency, Frequency, Monetary) analysis to segment customers based on their purchasing behavior. Using Python (Pandas, Seaborn, Matplotlib), we calculated RFM scores and grouped customers into segments like Champions, Loyal, At Risk, and Hibernating.

Segmenting Customer into clusters based on their interaction with Business

Segmenting store customers based on RFM (Recency, Frequency & Monetary)

- Dimensional reduction was applied by applying PCA - Rescale mean and standard deviation with StandardScaler - Log transformation is performed for even distribution between individual clusters

Customer Segmentation using RFM modelling

RFM analysis on CDNOW data

This is the repository for the website of CEPHIA, the Consortium for the Evaluation and Performance of HIV Incidence Assays.

📊 Analyze customer behavior with RFM segmentation to drive targeted marketing strategies and boost retention in retail and e-commerce.