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

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John Wiley & Sons, Mar 23, 2011 - Computers - 888 pages
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The leading introductory book on data mining, fully updated andrevised!

When Berry and Linoff wrote the first edition of Data MiningTechniques in the late 1990s, data mining was just starting tomove out of the lab and into the office and has since grown tobecome an indispensable tool of modern business. This newedition—more than 50% new and revised— is asignificant update from the previous one, and shows you how toharness the newest data mining methods and techniques to solvecommon business problems. The duo of unparalleled authors shareinvaluable advice for improving response rates to direct marketingcampaigns, identifying new customer segments, and estimating creditrisk. In addition, they cover more advanced topics such aspreparing data for analysis and creating the necessaryinfrastructure for data mining at your company. 

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

Data Mining Techniques, Third Edition covers a new datamining technique with each successive chapter and then demonstrateshow you can apply that technique for improved marketing, sales, andcustomer support to get immediate results.

 

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User Review  - jamet123 - LibraryThing

Anyone interested in automating and improving decisions should have this book. It is one of the classic works on data mining and well worth the read. I really liked the book both because it is well ... Read full review

Contents

Chapter
1
Chapter
7
Chapter
13
Data Mining Applications in Marketing and Customer
27
The Data Mining Process
67
What You Should Know About Data
101
Profiling
151
Data Mining Using Classic Statistical Techniques
195
Alternative Approaches to Cluster Detection
499
Market Basket Analysis and Association Rules
535
Association Analysis
547
Link Analysis
581
Data Warehousing OLAP Analytic Sandboxes and Data Mining
613
Building Customer Signatures
655
Making the Data Mean More
693
Too Much of a Good Thing? Techniques for Reducing the Number of Variables
735

Decision Trees
237
Artificial Neural Networks
281
MemoryBased
321
Measuring Distance and Similarity
335
Using Survival Analysis
357
Genetic Algorithms and Swarm Intelligence
397
Pattern Discovery
429
Automatic Cluster Detection
459
Text Mining
775
Ad Hoc Text Mining
786
From Text to Numbers
794
Sentiment Analysis
806
Lessons Learned
819
Index
821
Copyright

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About the author (2011)

GORDON S. LINOFF and MICHAEL J. A. BERRY are the founders of Data Miners, Inc., a consultancy specializing in data mining. They have jointly authored two of the leading data mining titles in the field, Data Mining Techniques and Mastering Data Mining (both from Wiley). They each have decades of experience applying data mining techniques to business problems in marketing and customer relationship management.

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