Implementation of RFMB model in banking customer segmentation and rule based approach

Abstract

Background - Customer segmentation with Recency Frequency Monetary + Balance (RFM+B) is an analysis
method that focuses on customer behavior. R indicates the last transaction, F is the number of transactions, M
indicates the amount of expenditure, and Balance (B) is the customer balance used for the customer
segmentation process. and assist in marketing strategy. This model is implemented for data segmentation, branch
company customers around 65 thousand data, transactions in the first semester of 2017 around 147 thousand
data including: cash payments, cash deposits, overbooking, and transactions via ATM. Apart from RFM+B,
customers will also be separated based on rules, thereby producing more accurate data. Based on the average
customer receipt, the highest is in cluster 0, the highest frequency is in cluster 2, the highest monetary is in cluster
3, and the largest balance is in cluster 1 and will be named according to the rule based results.Purpose - Customer Segmentation with RFMB modelsmethodology - RFM+B Model
Findings - Customer Segmentation in Banking Customers
Originality - Development RFM Models