Data Mining Techniques in CRM: Inside Customer Segmentation
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.
Antonios Chorianopoulos, Greek Ministry of Economy and Finance, Data Analysis Unit, MIS Service, Greece.
"This is an excellent book for any data miner or anybody involved in CRM. The text is clear and pictures are well done and funny which is rare enough to be mentioned. From basic to advanced topics, the book is a very pleasant journey inside data mining with a clear focus on customer segmentation. Really advised if you're not a fan of formulas." (Data Mining Research, 18 March 2011)"Many marketers hear that data mining is a valuable tool, but may not know where to start or how to apply it to their business. This book bridges the gap between the technology and its use in high-value marketing applications. Not only are the techniques of data mining explained (in ways accessible to mere mortals, not just PhD statisticians), Chorianopoulos and Tsiptsis guide marketers in banking, retail, and telecommunications through the steps of assembling the right data, analyzing it to identify actionable segments, and using this insight to drive successful marketing activities. The book is packed with guidance and tips that will ‘jump start’ marketing applications – a great benefit to any company looking to move its marketing to the next level."
—Colin Shearer, Senior Vice President Strategic Analytics, SPSS, an IBM Company
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