Data Mining Techniques in CRM Inside Customer Segmentation

by Tsiptsis, Konstantinos K.; Chorianopoulos, Antonios

• ISBN13: 9780470743973
• ISBN10: 0470743972
• Edition: 1st
• Format: Hardcover
• Copyright: 2010-03-01
• Publisher: Wiley

Summary

This is an applied handbook for the application of data mining techniques in the CRM framework. It combines a technical and a business perspective to cover the needs of business users who are looking for a practical guide on data mining. It focuses on Customer Segmentation and presents guidelines for the development of actionable segmentation schemes.By using non-technical language it guides readers through all the phases of the data mining process Methodological and technical issues are covered in detail but also in a simple way for users with no relevant experience. It proposes mining data marts and 'actual' input fields / KPIs for all major industries. Real-world segmentation examples from Banking, Telecommunications and Retailing are presented in detail and step by step preparing users for designing and implementing similar projects on their own. It provides deployment recommendations for the effective use of the data mining results in marketing.

Author Biography

Konstantinos Tsiptsis, CRM and Customer Intelligence Manager, Eurobank, EFM, Greece

Antonios Chorianopoulos, Greek Ministry of Economy and Finance, Data Analysis Unit, MIS Service, Greece.

Table of Contents

Data Mining In Crm

The CRM Strategy

What Can Data Mining Do?

The Data Mining Methodology

Data Mining and Business Domain Expertise

Summary

An Overview Of Data Mining Techniques

Supervised Modeling

Unsupervised Modeling Techniques

Machine Learning/Artificial Intelligence vs. Statistical Techniques

Summary

Data Mining Techniques For Segmentation

Segmenting Customers with Data Mining Techniques

Principal Components Analysis

Clustering Techniques

Examining and Evaluating the Cluster Solution

Understanding the Clusters through Profiling

Selecting the Optimal Cluster Solution

Cluster Profiling and Scoring with Supervised Models

An Introduction to Decision Tree Models

Summary

The Mining Data Mart

Designing the Mining Data Mart

The Time Frame Covered by the Mining Data Mart

The Mining Data Mart for Retail Banking

The Mining Data Mart for Mobile Telephony Consumer (Residential) Customers

The Mining Data Mart for Retailers

Summary

Customer Segmentation

An Introduction to Customer Segmentation

Segmentation Types in Consumer Markets

Segmentation in Business Markets

A Guide for Behavioral Segmentation

Segmentation Management Strategy

A Guide for Value-Based Segmentation

Designing Differentiated Strategies for the Value Segments

Summary

Segmentation Applications In Banking

Segmentation for Credit Card Holders

Segmentation in Retail Banking

Segmentation Applications In Telecommunications

Mobile Telephony

The Fixed Telephony Case

Summary

Segmentation For Retailers

Segmentation in the Retail Industry

The RFM Analysis

Grouping Customers According to the Products They Buy

Summary

Index

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