Customer retention via data mining

Kian Sing Ng, Huan Liu

Research output: Contribution to journalArticle

56 Scopus citations

Abstract

"Customer Retention" is an increasingly pressing issue in today's ever-competitive commercial arena. This is especially relevant and important for sales and services related industries. Motivated by a real-world problem faced by a large company, we proposed a solution that integrates various techniques of data mining, such as feature selection via induction, deviation analysis, and mining multiple concept-level association rules to form an intuitive and novel approach to gauging customer loyalty and predicting their likelihood of defection. Immediate action triggered by these "early-warnings" resulting from data mining is often the key to eventual customer retention.

Original languageEnglish (US)
Pages (from-to)569-590
Number of pages22
JournalArtificial Intelligence Review
Volume14
Issue number6
DOIs
StatePublished - Dec 2000
Externally publishedYes

Keywords

  • Customer retention
  • Data mining
  • Deviation analysis
  • Feature selection
  • Multiple level association rules

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language
  • Artificial Intelligence

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