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

Első borító
John Wiley & Sons, 2004. ápr. 14. - 660 oldal
  • Packed with more than forty percent new and updated material,this edition shows business managers, marketing analysts, and datamining specialists how to harness fundamental data mining methodsand techniques to solve common types of business problems
  • Each chapter covers a new data mining technique, and then showsreaders how to apply the technique for improved marketing, sales,and customer support
  • The authors build on their reputation for concise, clear, andpractical explanations of complex concepts, making this book theperfect introduction to data mining
  • More advanced chapters cover such topics as how to prepare datafor analysis and how to create the necessary infrastructure fordata mining
  • Covers core data mining techniques, including decision trees,neural networks, collaborative filtering, association rules, linkanalysis, clustering, and survival analysis
 

Kiválasztott oldalak

Tartalomjegyzék

For Marketing Sales and Customer Relationship Management Second Edition Chapter 1 Why and What Is Data Mining?
1
For Marketing Sales and Customer Relationship Management Second Edition Chapter 2 The Virtuous Cycle of Data Mining
21
For Marketing Sales and Customer Relationship Management Second Edition Chapter 3 Data Mining Methodology and Best Practices
43
For Marketing Sales and Customer Relationship Management Second Edition Chapter 4 Data Mining Applications in Marketing and Customer Relati...
87
For Marketing Sales and Customer Relationship Management Second Edition Chapter 5 The Lure of Statistics Data Mining Using Familiar Tools
123
For Marketing Sales and Customer Relationship Management Second Edition Chapter 6 Decision Trees
165
For Marketing Sales and Customer Relationship Management Second Edition Chapter 7 Artificial Neural Networks
211
For Marketing Sales and Customer Relationship Management Second Edition Chapter 8 Nearest Neighbor Approaches MemoryBased Reasoning and ...
257
For Marketing Sales and Customer Relationship Management Second Edition Chapter 11 Automatic Cluster Detection
349
For Marketing Sales and Customer Relationship Management Second Edition Chapter 12 Knowing When to Worry Hazard Functions and Survival A...
383
For Marketing Sales and Customer Relationship Management Second Edition Chapter 13 Genetic Algorithms
421
For Marketing Sales and Customer Relationship Management Second Edition Chapter 14 Data Mining throughout the Customer Life Cycle
447
For Marketing Sales and Customer Relationship Management Second Edition Chapter 15 Data Warehousing OLAP and Data Mining
473
For Marketing Sales and Customer Relationship Management Second Edition Chapter 16 Building the Data Mining Environment
513
For Marketing Sales and Customer Relationship Management Second Edition Chapter 17 Preparing Data for Mining
539
For Marketing Sales and Customer Relationship Management Second Edition Chapter 18 Putting Data Mining to Work
597

For Marketing Sales and Customer Relationship Management Second Edition Chapter 9 Market Basket Analysis and Association Rules
287
For Marketing Sales and Customer Relationship Management Second Edition Chapter 10 Link Analysis
321
For Marketing Sales and Customer Relationship Management Second Edition Index
615
Copyright

Más kiadások - Összes megtekintése

Data Mining Techniques: For Marketing, Sales, and Customer Relationship ...
Michael J. A. Berry,Gordon S. Linoff
Korlátozott előnézet - 2004
Data Mining Techniques: For Marketing, Sales, and Customer Relationship ...
Michael J. A. Berry,Gordon S. Linoff
Nincs elérhető előnézet - 2004
Data Mining Techniques (2Nd Ed.)
Michael J. A. Berry,Gordon S. Linoff
Nincs elérhető előnézet - 2009

Gyakori szavak és kifejezések

applications approach association rules average billing building calculate call detail records campaign categorical chapter chi-square churn classification clusters columns combination computers create credit card customer behavior customer relationship customer relationship management customer signature data marts data mining techniques data mining tools data warehouse data warehousing decision tree described detail dimensions direct mail estimate example fields Figure fitness function genetic algorithms genomes graph hazards identify important input instance look market basket analysis measure model set month neighbors neural network node OLAP output p-value particular patterns percent population possible predictive prospects purchase records response rate retention curve sample score segments shows similar split statistical stops survival analysis Table target variable telephone number tenure tion tomers training set transactions types understanding users validation set values weights zip code

A szerzőről (2004)

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

Bibliográfiai információk

CímData Mining Techniques: For Marketing, Sales, and Customer Relationship Management
SzerzőkMichael J. A. Berry, Gordon S. Linoff
Kiadás2, illusztrált
KiadóJohn Wiley & Sons, 2004
ISBN0764569074, 9780764569074
Terjedelem660 oldal
  
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