Customer segmentation using RFM analysis

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This paper is a research on the segmentation of customers. The clustering of customers is done based on the variables recency, frequency and monetary value. Such a clustering is called an RFM-model. The clustering is done using the K-means clustering method. To find the optimal number of clusters the following performance metrics are used: Elbow method, Silhouette Analysis, and Davies-Bouldin Index. The RFM-model is extended by introducing the loyalty variable. This model is called an RFML-model. Lastly, further clustering is done within one of the clusters.