Application of Data Mining Techniques to Support Customer Relationship Management! (Crm) at Ethiopian Telecommunicate Tion Corporation (Etc
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Date
2004-06
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Addis Ababa University
Abstract
The value of relevant and reliable information in this globalized. competitive and
dynamic business environment is 100 high as it allows optimal decision making in all
respects. Especially, in customer-oriented businesses like in the telecom industry,
adequate in((ml1ation regarding Customers is villa so that appropriate customer
relationships that maximize mutual benefit can be established)
Behavioral based customer segmentation, ,which is one of the core applications of
Customer Relationship Management (CRM). provides useful insights for designing
and implementing an appropriate CHM strategies and programs that remit in
success. To this end. data mining has strong potential in exploring natural
segmentation schemes that lies within customers' data This study is an attempt to explore the customers' data to find underlying customer
segments that may be use/ill Jar marketing decision making. The research followed
the CRISP data mining process model.
First the business problem was analyzed and a corresponding data mining tool,
techniques and algorithms were selected. Besides, relevant data was collected,
analyzed and prepared. Then, an automatic cluster detection models were bull to choose the best attributes
for the final segmentation. Next, the final automatic cluster detection model was
generated, analyzed and evaluated together with domain experts with different
parameters. Finally, a decision tree model, selling cluster index as dependent
variable, was built Corresponding rules to the decision tree were also generated.
The results obtained were encouraging and can be further refined .for possible
deployment
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Keywords
Information Science