Data Mining Techniques in CRM: Inside Customer Segmentation / Edition 1by Konstantinos K. Tsiptsis, Antonios Chorianopoulos
Pub. Date: 03/08/2010
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
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.
- Publication date:
- Edition description:
- New Edition
- Product dimensions:
- 6.90(w) x 9.90(h) x 1.00(d)
Table of Contents
1. Data Mining in CRM.
The CRM Strategy.
What Can Data Mining Do?
The Data Mining Methodology.
Data Mining and Business Domain Expertise.
2. An Overview of Data Mining Techniques.
Unsupervised Modeling Techniques.
Machine Learning/Artificial Intelligence vs. Statistical Techniques.
3. Data Mining Techniques for Segmentation.
Segmenting Customers with Data Mining Techniques.
Principal Components Analysis.
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.
4. 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.
5. 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.
6. Segmentation Applications in Banking.
Segmentation for Credit Card Holders.
Segmentation in Retail Banking.
The Marketing Process.
Segmentation in Retail Banking; A Summary.
7. Segmentation Applications in Telecommunications.
The Fixed Telephony Case.
8. Segmentation for Retailers.
Segmentation in the Retail Industry.
The RFM Analysis.
Grouping Customers According to the Products They Buy.
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If you are looking for a comprehensive guide on data mining this is your book. A real hands-on approach, packed with guidelines and tips. It presents a robust and comprehensive data mining process model, supplemented with real world application examples. This is also the first book that deals with the crucial issue of what data to use and presents full lists of input fields for banking, telcos and retail.