DocumentCode
3145470
Title
The customer lifetime value prediction in mobile telecommunications
Author
Wang, Yi ; Sanguansintukul, Siripun ; Lursinsap, Chidchanok
Author_Institution
Dept. of Math., Chulalongkorn Univ., Bangkok
fYear
2008
fDate
21-24 Sept. 2008
Firstpage
565
Lastpage
569
Abstract
How to treat the customer relationship is a crucial problem in the telecommunications industry. Therefore, how to measure and manage customer lifetime value (CLV) for determining the likely future profit from the customer is very important because the customer is always looking for better and cheaper products and services. The CLV value not only combines with the churn management but also considers the cross-selling and up-selling to allure customer. Earning, not just buying, customerspsila loyalty is now mandatory. Analysis and prediction of customer lifetime value (CLV) methods by using Artificial neural network (ANN) is proposed here. In this paper Multi-Layer Perceptron (MLP) network with Levenberg-Marquardt algorithm is used to predict the CLV, the strategic and operational decisions to retain a customer Lifetime Value in the Mobile Telecommunications industry.
Keywords
customer relationship management; mobile communication; multilayer perceptrons; telecommunication industry; Levenberg-Marquardt algorithm; artificial neural network; customer lifetime value; customer lifetime value prediction; customer relationship; mobile telecommunications industry; multi-layer perceptron; telecommunications industry; Artificial neural networks; Communication industry; Companies; Customer relationship management; Industrial relations; Mathematics; Mobile computing; Multilayer perceptrons; Profitability; Telecommunication computing; ANN; Artificial Neural Network; CLV; Customer lifetime value; MLP; Multi-Layer Perceptron;
fLanguage
English
Publisher
ieee
Conference_Titel
Management of Innovation and Technology, 2008. ICMIT 2008. 4th IEEE International Conference on
Conference_Location
Bangkok
Print_ISBN
978-1-4244-2329-3
Electronic_ISBN
978-1-4244-2330-9
Type
conf
DOI
10.1109/ICMIT.2008.4654427
Filename
4654427
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