Clustering Customers Loyalty in the Mellat Bank Customers' Club, Based on Demographic Information Using Data Mining Method

Keimasi, Masoud; Esfidani, Mohammadrahim; Esmailiyan, Amirbahman

doi:10.22108/nmrj.2016.20653

Clustering Customers Loyalty in the Mellat Bank Customers' Club, Based on Demographic Information Using Data Mining Method

Authors

University of Tehran

10.22108/nmrj.2016.20653

Abstract

Some activities such as long-term planning and marketing can be designed and performed through having enough information from various groups of customers and then clustering and classifying them, till the organization reach its efficiency to the possible extent. The aim of this research is to cluster the customers of Mellat Bank Customer’s Club into two groups of loyal and disloyal. Data were collected using the information of about 10300 members of this club. This data consists of two main parts including demographic information and information related to the used services by the club members. Furthermore, this research is descriptive-survey in terms of method. In addition, data were analyzed using data mining technique (C5.0, Interactive CHAID algorithms) and some other techniques.The obtained results and patterns can be used toward predicting new customers' loyalty as well as the needs of each groups of customers based on the obtained groups using their demographic information.

Keywords