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Data Mining Techniques: For Marketing, Sales, and Customer Relationship Management [Paperback]

Gordon S. Linoff (Author), Michael J. Berry (Author)
3.7 out of 5 stars  See all reviews (33 customer reviews)

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Book Description

April 12, 2011
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 one, 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 you 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 + Data Analysis Using SQL and Excel
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Editorial Reviews

Review

"The book 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. This guide 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 this book accessible." (Fathbrain.com; Ganthead.com, 9/01) --This text refers to an out of print or unavailable edition of this title.

From the Publisher

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. --This text refers to an out of print or unavailable edition of this title.

Product Details

  • Paperback: 888 pages
  • Publisher: *Wiley Computer Publishing; 3 edition (April 12, 2011)
  • Language: English
  • ISBN-10: 0470650931
  • ISBN-13: 978-0470650936
  • Product Dimensions: 9.2 x 7.4 x 1.9 inches
  • Shipping Weight: 2.9 pounds (View shipping rates and policies)
  • Average Customer Review: 3.7 out of 5 stars  See all reviews (33 customer reviews)
  • Amazon Best Sellers Rank: #179,084 in Books (See Top 100 in Books)

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Customer Reviews

33 Reviews
5 star:
 (15)
4 star:
 (7)
3 star:
 (4)
2 star:
 (1)
1 star:
 (6)
 
 
 
 
 
Average Customer Review
3.7 out of 5 stars (33 customer reviews)
 
 
 
 
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Most Helpful Customer Reviews

26 of 27 people found the following review helpful:
5.0 out of 5 stars Author's comment, April 20, 2005
By 
Although this book was not written as a text book, we have noticed that it is frequently used that way. For the benefit of instructors, we have collected some exercises and datasets that can be used in the classroom or for self study. These can be found at www.data-miners.com/companion.
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26 of 27 people found the following review helpful:
5.0 out of 5 stars The first book on Data Mining everyone should read, May 3, 1999
It covers almost every aspect of data mining. It is clear, precise, goes to the point, and sometimes goes into some depth. If you are a marketing person, it will give you a very refined idea of what can be done with data mining, and what does it involves for your company ( remember the first thing you need is DATA!!). If you are an academic person, you will get a general idea of the different kinds of data analysis. You won't see any formulae or algorithms, after reading this book look for details somewhere else.
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22 of 24 people found the following review helpful:
3.0 out of 5 stars Depends what you want this book for, April 1, 2001
By 
Alex (Singapore) - See all my reviews
This book gives an overview of what data mining is and the tools available to perform it; Market Basket Analysis, Memory Based Reasoning, Automatic Cluster Detection, Link Analysis, Decision Trees, Artificial Neural Networks. Genetic Algorithms are also included, which, while not a data mining tool, are being used to train neural nets.

In each case the authors describe the principles behind the tool, its strengths and weaknesses and applications were it is applicable. The authors give tips on what data preparation is required for the tool, both in terms of data "massaging", (which is required for neural nets) and indicate were it is important to select training sets that have approximately equal proportions of "good" & "bad" outcomes, in order for the tool to predict correctly.

The descriptions include simple examples of the tool to give an overview of how the tool works. But as the title indicates, this book is for users who are considering using data mining tools. It does not describe how to use particular applications, neither does it include code examples (pseudo or actual) if you are interesting in developing your own tools.

The book is easy to read and includes many examples from their experience of data mining in the real world.

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