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Churn Management in Telecommunications: Challenging the innovative Capability of Data Mining Tools

Author:

Artur Khalatyan

Information Systems and Innovation Group, Department of Management, London School of Economics and Political Science, GB
About Artur
Candidate for MSc Analysis, Design and Management of Information Systems
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Abstract

With growing competition in the telecommunications market, the mobile operators became “victims” of a structure inherited from happy monopoly times of a technologically centred nature, posing limitations that largely frame business values, functions and processes dealing with human behaviour. A good example are data-mining tools that use historical data generated by transactional, billing and contract management technologies for finding patterns of customer behaviour by applying various statistical techniques. This paper argues that a more reliable and sustainable way to reduce customer churn is to look at the reasons why customers churn, rather than which target group is prone to churning, as well as to make greater use of contextual data rather than historical transaction data. One of the ways to get closer to the implementation of such a visionary and complex task, associated with richness and constant emergence of contextual data analysis, is to fully separate the customer service function and break it into contextual groups, such as small firms, dealing with certain groups of customers. Following a discussion on two major problems with data mining tools and their inappropriateness to account for contextual data, the paper proposes a Value Network Analysis framework for the establishment of new market structures and business models for telecommunications operators, capable to cope with the uncertainty of customer intention to churn.

How to Cite: Khalatyan, A., 2010. Churn Management in Telecommunications: Challenging the innovative Capability of Data Mining Tools. iSCHANNEL, 5(1), pp.21–26.
Published on 01 Sep 2010.
Peer Reviewed

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