Customer Segmentation Based on Mobile Banking User's Behavior

This study was conducted to integrate data mining and modeling of customer behavior in the RFMT model for working with mobile banking customers in private banks in Iran. The internet has overgrown and has become the need of the public in doing activities in various fields. One of them is the pecuniary segment or bank. Banks must provide customer satisfaction in delivering quality services. They expanded this segmentation model to know customer groups according to transaction record, regency, frequency, monetary, and time background. Mobile banking customers are classified into six clusters. This research showed that recognizing customers using behavioral scores facilitates the determination of marketing strategy.