Customer Segmentation using RFM model

Abstract

The purpose of this thesis is to deliver corporate intelligence by analysing client purchase habits using a clustering algorithm and the RFM (recency, frequency, monetary) model. RFM is used for marketing analysis to identify a customer who is valuable/profitable to business and accordingly develop promotion marketing strategies for specific target customers. We will compare different clustering algorithms based on their accuracy and consuming time. We will also analyse real-time data that is stretched over a specific time period to provide an effective result and business intelligence across several regions. The cluster will be validated using the silhouette coefficient. We are using RFM to segment customers so that the company can target them more effectively.