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Customer-Segmentation-using-RFM-Model-KMean-Algorithm

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

In here we have applied RFM model and KMean algorithm to cosmetic dataset which was extracted from an online store. https://www.kaggle.com/mkechinov/ecommerce-events-history-in-cosmetics-shop

As the features for KMean algorithm we have used calculated Recency, Frequency, and Monetary values.

4 clusters are ientifyied and named as follows.

cluster 0 - Hibernating - low level of all R,F,M cluster 1 - Recent Customers - high R, middle F and low M cluster 2 - Potential Loyalist - middle level of all R,F,M cluster 3 - At Risk Customers - low R, high F,M

There are a high number of Hibernating customers and a low number of Potential loyalist customers.

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Use of RFM Model and KMean Algorithm on Customer segmentation process.

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