Data Mining Techniques in CRM (eBook)
372 Seiten
John Wiley & Sons (Verlag)
978-0-470-68582-2 (ISBN)
Konstantinos Tsiptsis, CRM and Customer Intelligence Manager, Eurobank, EFM, Greece Antonios Chorianopoulos, Greek Ministry of Economy and Finance, Data Analysis Unit, MIS Service, Greece.
Acknowledgements.
1. Data Mining in CRM.
The CRM Strategy.
What Can Data Mining Do?
The Data Mining Methodology.
Data Mining and Business Domain Expertise.
Summary.
2. An Overview of Data Mining Techniques.
Supervised Modeling.
Unsupervised Modeling Techniques.
Machine Learning/Artificial Intelligence vs. Statistical
Techniques.
Summary.
3. 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.
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.
Summary.
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.
Summary.
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.
Mobile Telephony.
The Fixed Telephony Case.
Summary.
8. Segmentation for Retailers.
Segmentation in the Retail Industry.
The RFM Analysis.
Grouping Customers According to the Products They Buy.
Summary.
Further Reading.
Index.
"The book is written in a language that is easily accessible to
business users who are not fluent in statistical methods and who
have no prior exposure to the data mining or customer segmentation
domain . . . This book is poised to become a standard reference,
and I unconditionally recommend it to anyone working in this
field." (Computing Reviews, 23 June 2011)
"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
Erscheint lt. Verlag | 13.8.2010 |
---|---|
Sprache | englisch |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Mathematik / Informatik ► Mathematik ► Statistik | |
Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
Wirtschaft ► Betriebswirtschaft / Management ► Marketing / Vertrieb | |
Schlagworte | Computer Science • Customer Relationship Management • Database & Data Warehousing Technologies • Data Mining • Data Mining Statistics • Datenbanken u. Data Warehousing • Informatik • Statistics • Statistik |
ISBN-10 | 0-470-68582-4 / 0470685824 |
ISBN-13 | 978-0-470-68582-2 / 9780470685822 |
Haben Sie eine Frage zum Produkt? |
Größe: 4,3 MB
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