Data mining case studies in customer profiling

Jussi Ahola, Esa Rinta-Runsala

Research output: Book/ReportReport

Abstract

The purpose of this document is to report the results of applying some data mining methods that were reviewed in the earlier customer profiling report, to real world problems. The cases in question concern customer data from a bank and a book club. Two separate approaches are taken in the problem solving. First, an explorative analysis is applied to both cases. The goal of the analysis, as can be expected, is to give insight of the data in order to reveal or extract the relevant structure of and patterns in the data. The specific tasks include clustering of the banking data and sequence mining of the book club transactions. Subsequently, a predictive analysis of the cases is performed. Unlike the explorative analysis, the prediction involves a target variable to be considered. The general aim of the analysis is to generate a model using examples of the past in order to predict the outcome in the future. The concrete tasks performed are to predict the profitability of the book club members with logistic
Original languageEnglish
Place of PublicationEspoo
PublisherVTT Technical Research Centre of Finland
Number of pages25
Publication statusPublished - 2001
MoE publication typeD4 Published development or research report or study

Publication series

SeriesVTT Research Report
NumberTTE1-2001-29

Keywords

  • data mining
  • customer profiling
  • clustering
  • sequence analysis
  • logistic regression
  • decision trees

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