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Data Mining Techniques: for Marketing, Sales, and Customer Supportby Michael Berry
Synopses & Reviews
Who will remain a loyal customer and who won't?
What kind of marketing approach is most likely to increase sales?
What can customer buying patterns tell us about improving our inventory control?
What type of credit approval process will work best for us and our customers?
The answers to these and all your crucial business questions lie buried in your company's information systems. This book supplies you with powerful tools for mining them.
Data Mining Techniques thoroughly acquaints you with the new generation of data mining tools and techniques and shows you how to use them to make better business decisions. One of the first practical guides to mining business data, it describes techniques for detecting customer behavior patterns useful in formulating marketing, sales, and customer support strategies. While database analysts will find more than enough technical information to satisfy their curiosity, technically savvy business and marketing managers will find the coverage eminently accessible. Here's your chance to learn all about:
* How leading companies across North America are using data mining to beat the competition
* How each tool works, and how to pick the right one for the job
* Seven powerful techniques -cluster detection, memory-based reasoning, market basket analysis, genetic algorithms, link analysis, decision trees, and neural nets
* How to prepare data sources for data mining, and how to evaluate and use the results you get
Data Mining Techniques shows you how to quickly and easily tap the gold mine of business solutions lying dormant in your information systems.
Learn how to quickly and easily access the wealth of information in your information systems
With data mining, companies can analyze customers' past behaviors in order to make strategic decisions for the future. This book is a practical guide to mining business data to help marketers and business managers focus their marketing and sales strategies. It explains how each mining technique works and what kinds of business problems each one can solve.
Includes bibliographical references (p. 443-444) and index.
About the Author
MICHAEL J. A. BERRY and GORDON LINOFF are principals at MRJ Technology Solutions, a Pennsylvania-based firm specializing in data warehousing and data mining for business applications. They also conduct seminars on data mining for Fortune 100 companies.
Table of Contents
Why Data Mining?
The Virtuous Cycle of Data Mining.
The Virtuous Cycle in Practice.
What Can Data Mining Do?
Data Mining Methodology.
Measuring the Effectiveness of Data Mining.
Overview of Data Mining Techniques.
Market Basket Analysis.
Automatic Cluster Detection.
Artificial Neural Networks.
Data Mining and the Corporate Data Warehouse.
Where Does OLAP Fit In?
Choosing the Right Tool for the Job.
Putting Data Mining to Work.
What Our Readers Are Saying
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