Recency Frequency and Monetary RFM segmentation enables marketers to target specific groups of consumers with communications that are far more relevant to their individual behaviours, resulting in much greater response rates, as well as improved loyalty and customer lifetime value. RFM segmentation, like other segmentation approaches, is an effective tool to identify groups of consumers who should be treated differently. RFM stands for recency, frequency, and monetary There are several approaches to segmentation. However, I chose RFM Model for the following reasons: It employs objective numerical scales to produce a high-level picture of consumers that is both succinct and instructive. It's simple enough that marketers can utilize it without expensive tools. It's simple - the segmentation method's output is simple to comprehend and analyze.

#For this project, I will be building an RFM (Recency Frequency Monetary) model using E-commerce data sets I downloaded on Kaggle just for the sake of this project( I know someone must have put it out there for free use, a big thank you to the anonymous). I am sure there are countless free data sets you can get on Kaggle for practice as well. The purpose of this project is to build an RFM model that segments customers into sections listed below: Can't Loose Them' Champions Loyal/Commited Requires Attention Potential  Promising Demands Activation