Research Article

Model to Predict the Behavior of Customers Churn at the Industry

by  Keyvan Vahidy Rodpysh
journal cover
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 49 - Issue 15
Published: July 2012
Authors: Keyvan Vahidy Rodpysh
10.5120/7702-1059
PDF

Keyvan Vahidy Rodpysh . Model to Predict the Behavior of Customers Churn at the Industry. International Journal of Computer Applications. 49, 15 (July 2012), 12-16. DOI=10.5120/7702-1059

                        @article{ 10.5120/7702-1059,
                        author  = { Keyvan Vahidy Rodpysh },
                        title   = { Model to Predict the Behavior of Customers Churn at the Industry },
                        journal = { International Journal of Computer Applications },
                        year    = { 2012 },
                        volume  = { 49 },
                        number  = { 15 },
                        pages   = { 12-16 },
                        doi     = { 10.5120/7702-1059 },
                        publisher = { Foundation of Computer Science (FCS), NY, USA }
                        }
                        %0 Journal Article
                        %D 2012
                        %A Keyvan Vahidy Rodpysh
                        %T Model to Predict the Behavior of Customers Churn at the Industry%T 
                        %J International Journal of Computer Applications
                        %V 49
                        %N 15
                        %P 12-16
                        %R 10.5120/7702-1059
                        %I Foundation of Computer Science (FCS), NY, USA
Abstract

In order to continue life-sustaining competitive advantage, many organizations focus on maximizing the marketing relationship with their customer lifetime value and customer churn management. In fact, more organizations are realizing that their most valuable resource is their current customer base. In the present study are to go through a database collected from 300 customers, including an insurance company in Iran has been used. In order to check the model presented with a desire to review a decision tree classification methods (C5. 0, CART, CHAID, and Quest), Bayesian networks and neural networks will be paid with respect to sample. Survey results can help managers, marketers in this arena is in various industries. Reduction strategies appropriate to offer in this field. The entire paper must be in A4 size and "Moderate" margin

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Index Terms
Computer Science
Information Sciences
No index terms available.
Keywords

Data Mining Classification method Decision tree Customer churn Insurance

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