Data Mining Techniques
For Marketing, Sales, and Customer Relationship Management
(Sprache: Englisch)
* Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems*...
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Produktinformationen zu „Data Mining Techniques “
* Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness fundamental data mining methods and techniques to solve common types of business problems
* Each chapter covers a new data mining technique, and then shows readers how to apply the technique for improved marketing, sales, and customer support
* The authors build on their reputation for concise, clear, and practical explanations of complex concepts, making this book the perfect introduction to data mining
* More advanced chapters cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining
* Covers core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, clustering, and survival analysis
Klappentext zu „Data Mining Techniques “
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 getData Mining Techniques shows you how to quickly and easily tap the gold mine of business solutions lying dormant in your information systems.
Inhaltsverzeichnis zu „Data Mining Techniques “
Acknowledgments.About the Authors.
Introduction.
Chapter 1: Why and What Is Data Mining?
Chapter 2: The Virtuous Cycle of Data Mining.
Chapter 3: Data Mining Methodology and Best Practices.
Chapter 4: Data Mining Applications in Marketing and Customer Relationship Management.
Chapter 5: The Lure of Statistics: Data Mining Using Familiar Tools.
Chapter 6: Decision Trees.
Chapter 7: Artificial Neural Networks.
Chapter 8: Nearest Neighbor Approaches: Memory-Based Reasoning and Collaborative Filtering.
Chapter 9: Market Basket Analysis and Association Rules.
Chapter 10: Link Analysis.
Chapter 11: Automatic Cluster Detection.
Chapter 12: Knowing When to Worry: Hazard Functions and Survival Analysis in Marketing.
Chapter 13: Genetic Algorithms.
Chapter 14: Data Mining throughout the Customer Life Cycle.
Chapter 15: Data Warehousing, OLAP, and Data Mining.
Chapter 16: Building the Data Mining Environment.
Chapter 17: Preparing Data for Mining.
Chapter 18: Putting Data Mining to Work.
Index.
Autoren-Porträt von Michael J. A. Berry, Gordon S. Linoff
Michael J. A. Berry is (together with Gordon S. Linoff) the founder of Data Miners Inc., a consulting firm specializing in data mining. He provides analytic CRM consulting for customer-centric companies on and off the Web. He is author of Data Mining Techniques and Mastering Data Mining (both from Wiley). Gordon S. LinoffF is (together with Michael J. A. Berry) the founder of Data Miners Inc., a consulting firm specializing in data mining. He provides analytic CRM consulting for customer-centric companies on and off the Web.
Bibliographische Angaben
- Autoren: Michael J. A. Berry , Gordon S. Linoff
- 2004, 2nd ed., XXV, 643 Seiten, mit Schwarz-Weiß-Abbildungen, mit Abbildungen, Maße: 18,9 x 23,5 cm, Kartoniert (TB), Englisch
- Verlag: Wiley & Sons
- ISBN-10: 0471470643
- ISBN-13: 9780471470649
Sprache:
Englisch
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