Konstantinos Tsiptsis, Antonios Chorianopoulos

Data Mining Techniques in Crm

Inside Customer Segmentation

• Gebundenes Buch

Produktbeschreibung

The book aims to be a complete and comprehensive handbook for the use of Data Mining Techniques in the CRM framework. It combines a technical and a business perspective, bridging the gap between data mining & business professionals. By using non-technical language it focuses on Customer Segmentation and presents guidelines for the development of actionable segmentation schemes.

It guides readers through all phases of the data mining process, from the understanding of the business objective and the setting of the data mining goal to the model development, evaluation and deployment.

Methodological and technical guidelines are supplemented by real-world application examples from all major industries, including Telecommunications, Banking and Retailing and recommendations for the use of the data mining results for effective marketing.

Data mining algorithms are presented in a simple and comprehensive way for the business users with no technical expertise.

Mining data marts for Telecommunications, Banking and Retailing and full lists of recommended input fields are proposed that can serve as the base for the implementation of data mining applications.

The book is mainly addressed to business users who are looking for a practical guide on data mining. It presents the authors' knowledge and experience from the 'data mining trenches', demystifying the secrets for data mining success.

Produktdetails

• Verlag: Wiley & Sons
• Artikelnr. des Verlages: 14574397000
• 1. Auflage
• Seitenzahl: 372
• Erscheinungstermin: 1. März 2010
• Englisch
• Abmessung: 250mm x 175mm x 25mm
• Gewicht: 816g
• ISBN-13: 9780470743973
• ISBN-10: 0470743972
• Artikelnr.: 26841929

Autorenporträt

Konstantinos Tsiptsis, CRM and Customer Intelligence Manager, Eurobank, EFM, Greece Antonios Chorianopoulos, Greek Ministry of Economy and Finance, Data Analysis Unit, MIS Service, Greece.

Inhaltsangabe

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.