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RFM_Model_with_Python

Please refer to RFM_Model.ipynb to see my code.

During my internship at XROUND Inc., I was asked to help arrange customers data and conduct customer segmentation. Hence, I proposed to implement RFM Model to evaluate customer values and cluster customers. As a result, the company was abler to target their valued customers and better achieve precise marketing.

The datasets used here are very small because I made up them by myself and did not use real commercial data due to company privacy. However, I believe it is enough to demonstrate how this program works.

What Is Recency, Frequency, Monetary Value (RFM)?

Recency, frequency, monetary value is a marketing analysis tool used to identify a company's or an organization's best customers by using certain measures. The RFM model is based on three quantitative factors:

Recency: How recently a customer has made a purchase

Frequency: How often a customer makes a purchase

Monetary Value: How much money a customer spends on purchases RFM analysis numerically ranks a customer in each of these three categories, generally on a scale of 1 to 5 (the higher the number, the better the result). The "best" customer would receive a top score in every category.

For further information, please refer to https://www.investopedia.com/terms/r/rfm-recency-frequency-monetary-value.asp

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