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Measuring the impact of data mining on churn management

Bibliographic Data

ID12420561
AuthorsMiguel A Lejeune (0000-0001-6952-7212, Rutgers, the State University of New Jersey, corresponding author), Miguel A P M Lejeune
Year2001
Volume11
Issue5
Pages375-387
Publication date2001-12-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueInternet Research (JOURNAL)
Journal identifiersISSN: 1066-2243 • E-ISSN: 2054-5657
PublisherEmerald Publishing Limited (PUBLISHER • GB)
DOI10.1108/10662240110410183
OpenAlexW2171921035
LanguageEN
Citations received3
References cited21

Churn management is a fundamental concern for businesses and the emergence of the digital economy has made the problem even more acute. Companies’ initiatives to handle churn and customers’ profitability issues have been directed to more customer‐oriented strategies. In this paper, we present a customer relationship management framework based on the integration of the electronic channel. This framework is constituted of four tools that should provide an appropriate collection, treatment and analysis of data. From this perspective, we pay special attention to some of the latest data mining developments which, we believe, are destined to play a central role in churn management. Relying on sensitivity analysis, we propose an analysis framework able to prefigure the possible impact induced by the ongoing data mining enhancements on churn management and on the decision‐making process

Business · Customer Relationship Management · Data science · Database · Knowledge management · Perspective (graphical · Process (computing · Process management · Profitability index · Computer Science · Consumer Retail Behavior Studies · Customer churn and segmentation · Customer Service Quality and Loyalty · Finance

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Unique citing works3
Citations per year0,14
Citation span2004 - 2021 (18)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 3

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