Data mining techniques for sales

By | 06.01.2018
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The NOOK Book (eBook) of the Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management by Gordon S. Linoff, Michael J. A. Berry |4.5/5(2). Data Mining Techniques, Third Edition covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results. Data Mining Techniques. For Marketing, Sales, and Customer Relationship Management. 3rd EditionPrice: €84.
Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management [Michael J. A. Berry, Gordon S. Linoff] 4.5/5(9). Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness 4/5(6). The NOOK Book (eBook) of the Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management by Gordon S. Linoff, Michael J. A. Berry |4.5/5(2). Data Mining Techniques, Third Edition covers a new data mining technique with each successive chapter and then demonstrates how you can apply that technique for improved marketing, sales, and customer support to get immediate results. Data Mining Techniques. For Marketing, Sales, and Customer Relationship Management. 3rd EditionPrice: €84.
The leading introductory book on data mining, fully updated and revised!

When Berry and Linoff wrote the first edition of Data Mining Techniques in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable tool of modern business. This new edition—more than 50% new and revised— is a significant update from the previous mountain pass mining, and shows you how to harness the newest data mining methods and techniques to solve common business problems. The duo of unparalleled authors share invaluable advice for improving response rates to direct marketing campaigns, identifying new customer segments, and estimating credit risk. In addition, they cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company. 

  • Features significant updates since the previous edition and updates you on best practices for using data mining methods and techniques for solving common business problems
  • Covers a new data mining technique in every chapter along with clear, concise explanations on how to apply each technique immediately
  • Touches on core data mining techniques, including decision trees, neural networks, collaborative filtering, association rules, link analysis, survival analysis, and more
  • Provides best practices for performing data mining using simple tools such as Excel

Data Mining Techniques, Third Edition covers a new data mining technique with each successive chapter and then demonstrates how data mining techniques for sales can apply that technique for improved marketing, sales, and customer support to get immediate results.

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Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, Third Edition

Data Mining Techniques. For Marketing, Sales, and Customer Relationship Management. 3rd EditionPrice: €84. Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, 2nd Edition. The leading introductory book on data mining, fully updated and revised! When Berry and Linoff wrote the first edition of Data Mining Techniques in the late 1990s 5/5(1).

Packed with more than forty percent new and updated material, this edition shows business managers, marketing analysts, and data mining specialists how to harness 4/5(6). Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management, 2nd Edition. The NOOK Book (eBook) of the Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management by Gordon S. Linoff, Michael J. A. Berry |4.5/5(2).


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.

  • Offers concise, clear, and practical explanations of complex concepts                                  

  • Covers core datat mining techinques, including:  decision trees; neural networks; collaborative filtering; association rules, link analysis, clustering; and survival analysis

  • Provides an overview of data mining best practices and how to perform data mining using simple tools like Excel.

  • Includes advanced chapters which cover such topics as how to prepare data for analysis and how to create the necessary infrastructure for data mining at your company.

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