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E-pismo dla elektryków i elektroników
AUTOMATYKA, ELEKTRYKA, ZAKŁÓCENIA

Vol. 8, nr 3 (29) 2017

Publ. 30 września 2017

Artificial Neural Network in Forecasting the Churn Phenomena Among Costumers of IT and Power Supply Services

Artificial Neural Network in Forecasting the Churn Phenomena Among Costumers of IT and Power Supply Services

mgr inż. Przemysław WOJDA, dr inż. Krzysztof NOWICKI

s. 34-41 DOI: 10.17274/AEZ.2017.29.03

Abstract

This paper presents an attempt to use an artificial neural network to investigate the churn phenomenon among the customers of a telecommunications operator. An attempt was made to create a data model based on the customer lifetime value (CLV) rather than on activity alone. A multilayered artificial neural network was used for the experiments. The results yielded a 99% successful identification rate for customers in no danger of leaving, while only 57% of those identified as in danger of leaving actually did so and stopped using the company's services.

Streszczenie

This paper presents an attempt to use an artificial neural network to investigate the churn phenomenon among the customers of a telecommunications operator. An attempt was made to create a data model based on the customer lifetime value (CLV) rather than on activity alone. A multilayered artificial neural network was used for the experiments. The results yielded a 99% successful identification rate for customers in no danger of leaving, while only 57% of those identified as in danger of leaving actually did so and stopped using the company's services.

Keywords

churn, ANN, CLV

Słowa kluczowe

churn, ANN, CLV

Rys. / Fig.

Bibliografia / Bilbiography

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