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Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining
book

Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining

by Glenn J. Myatt
November 2006
Beginner to intermediate
292 pages
7h 26m
English
Wiley-Interscience
Content preview from Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining

2.6 CASE STUDY

2.6.1 Overview

The following is a hypothetical case study involving a financial company's credit card division that wishes to reduce the number of customers switching services. To achieve this, marketing management decides to initiate a data mining project to help predict which customers are likely to switch services. These customers will be targeted with an aggressive direct marketing campaign. The following is a summarized plan for accomplishing this objective.

2.6.2 Problem

The credit card division would like to increase revenues by $2,000,000 per year by retaining more customers. This goal could be achieved if the division could predict with a 70% accuracy rate which customers are going to change services. The 70% accuracy number is based on a financial model described in a separate report. In addition, factors that are likely to lead to customers changing service will be useful in formulating future marketing plans.

To accomplish this business objective, a data mining project is established to solve the following problems:

  1. Create a prediction model to forecast which customers are likely to change credit cards.
  2. Find hidden facts, relationships, and patterns that customers exhibit prior to switching credit cards.

The target population is all credit card customers.

2.6.3 Deliverables

There will be two deliverables:

  1. Software to predict customers likely to change credit cards.
  2. A report describing factors that contribute to customers changing credit cards.

The ...

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Publisher Resources

ISBN: 9780470074718Purchase book