سال انتشار: ۱۳۹۱

محل انتشار: سومین همایش ملی مهندسی صنایع و سیستم

تعداد صفحات: ۴

نویسنده(ها):

Elham Familian – Post graduate student, School of Industrial engineering, IslamicAzad University, South Tehran Branch
Sadigh Raissi – Associate Professor, School of Industrial engineering, Islamic Azad University, South Tehran Branch
Farshid Abdi – Assistant Professor, School of Industrial engineering, Islamic Azad University, South Tehran Branch

چکیده:

Data mining is a powerful new technique to help organizations mining the patterns andtrends in their customers data, then to drive improved customer relationships, and it is oneof well-known tools given to customer relationship management (CRM). This paperprovides a framework for segmenting customers in homogenous segments. Firstly, a cluster analysisis proposed to categorize the huge amount of data into several groups based on sixattributes: Deposit average, Rate of purchase with credit card, Bad cheque amount, number of bad cheque and the use of internet and telephone banking services. Then classifyingeach customer segment by Decision Tree (DT) under Analytical Hierarchy Process (AHP)technique based on expert people idea. Regression technique is used to implement the customer financial behavior model. The developed methodology has been implemented forprivate bank in Iran.