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Intelligent data analysis approaches to churn as a business problem: a survey
García Gómez, David; Nebot Castells, M. Àngela; Vellido Alcacena, Alfredo
Universitat Politècnica de Catalunya. Departament de Ciències de la Computació; Universitat Politècnica de Catalunya. SOCO - Soft Computing
Globalization processes and market deregulation policies are rapidly changing the competitive environments of many economic sectors. The appearance of new competitors and technologies leads to an increase in competition and, with it, a growing preoccupation among service-providing companies with creating stronger customer bonds. In this context, anticipating the customer’s intention to abandon the provider, a phenomenon known as churn, becomes a competitive advantage. Such anticipation can be the result of the correct application of information-based knowledge extraction in the form of business analytics. In particular, the use of intelligent data analysis, or data mining, for the analysis of market surveyed information can be of great assistance to churn management. In this paper, we provide a detailed survey of recent applications of business analytics to churn, with a focus on computational intelligence methods. This is preceded by an in-depth discussion of churn within the context of customer continuity management. The survey is structured according to the stages identified as basic for the building of the predictive models of churn, as well as according to the different types of predictive methods employed and the business areas of their application.
Peer Reviewed
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial
Computational intelligence
Data mining
Churn analysis
Intelligent data analysis
Customer continuity management
Literature survey
Intel·ligència computacional
Mineria de dades
info:eu-repo/semantics/submittedVersion
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