Mastering Data Mining: The Art and Science of Customer Relationship Management
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Published by:John Wiley & Sons Inc (US)
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Published:14/12/1999
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Price:$115.00
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"This is a great book, and it will be in my stack of four or five essential resources for my professional work." -Ralph Kimball, Author of The Data Warehouse Lifecycle Toolkit
Mastering Data Mining
In this follow-up to their successful first book, Data Mining Techniques, Michael J. A. Berry and Gordon S. Linoff offer a case study-based guide to best practices in commercial data mining. Their first book acquainted you with the new generation of data mining tools and techniques and showed you how to use them to make better business decisions. Mastering Data Mining shifts the focus from understanding data mining techniques to achieving business results, placing particular emphasis on customer relationship management.
In this book, you'll learn how to apply data mining techniques to solve practical business problems. After providing the fundamental principles of data mining and customer relationship management, Berry and Linoff share the lessons they have learned through a series of warts-and-all case studies drawn from their experience in a variety of industries, including e-commerce, banking, cataloging, retailing, and telecommunications.
Through the cases, you will learn how to formulate the business problem, analyze the data, evaluate the results, and utilize this information for similar business problems in different industries.
Berry and Linoff show you how to use data mining to:Retain customer loyaltyTarget the right prospectsIdentify new markets for products and servicesRecognize cross-selling opportunities on and off the Web
The companion Web site at http://www.data-miners.com features:Updated information on data mining products and service providersInformation on data mining conferences, courses, and other sources of informationFull-color versions of the illustrations used in the book.
Biography
Table of Contents
Data Mining in Context.
Why Master the Art?
Data Mining Methodology: The Virtuous Cycle Revisited.
Customers and Their Lifecycles.
THE THREE PILLARS OF DATA MINING.
Data Mining Techniques and Algorithms.
Data, Data Everywhere...
Building Effective Predictive Models.
Taking Control: Setting Up a Data Mining Environment.
CASE STUDIES.
Who Needs Bag Balm and Pants Stretchers.
Who Gets What? Building a Best Next Offer Model for an Online Bank.
Please Don't Go! Churn Modeling in Wireless Communication.
Converging on the Customer: Understanding Customer Behavior in the Telecommunications Industry.
Who Is Buying What? Getting to Know Supermarket Shoppers.
Waste Not, Want Not: Improving Manufacturing Processes.
The Societal Context: Data Mining and Privacy.
Index.
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