Customer Behavior Mining Framework (CBMF) Using Clustering and Classification Techniques

The present study proposes a Customer Behavior Mining Framework on the basis of data-mining techniques in a telecom company. This framework takes into account the customers' behavior patterns and predicts the way they may act in the future. First, a clustering technique is used to implement portfolio analysis and previous customers are divided based on socio-demographic features through a k-means algorithm. The second phase is devoted to mining the future behavior of the customers. Prediction of the level of attractiveness of newcomer customers as well as the churn behavior of these customers is done in the second phase. This framework effectively helps the telecom managers mine the behavior of their customers, and develop appropriate tactics accordingly. Improvement of managers' abilities in customer relationship management is one of the obtained results of the study.

Publication: 
Journal of Industrial Engineering International
Author: 
Farshid Abdi
Document Type: 
Research
Paywall: 
Free
Description: 
Find out how data mining techniques enable the telecom industry to create custom user segments, utilize predictive analysis, and more.
Meta Title: 
How Data Mining is Used in the Telecommunication Industry

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