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雷达卡
Table of Contents
Course Description.....................................................................................................................vii
Prerequisites ..............................................................................................................................viii
General Conventions ................................................................................................................... ix
Chapter 1 Introduction ........................................................................................... 1-1
1.1 Web Sites and Web Solutions ..........................................................................................1-3
1.2 A Selection of Business Pains........................................................................................1-22
1.3 A Collection of Data Mining Tools................................................................................1-31
1.4 Introduction to Predictive Modeling..............................................................................1-38
1.5 The Apache Web Server (Optional) ...............................................................................1-66
1.6 References......................................................................................................................1-73
Chapter 2 Data ........................................................................................................ 2-1
2.1 Types of Data ...................................................................................................................2-3
2.2 Web Log Data ................................................................................................................2-44
2.3 Cookies and Other Data Collection Tools......................................................................2-71
2.4 Proactive Web Data Gathering: Bots and Intelligent Agents .........................................2-81
2.5 Data Preparation for Predictive Modeling .....................................................................2-91
2.6 Exercises ........................................................................................................................2-99
2.7 References....................................................................................................................2-100
Chapter 3 Knowing Your Customers .................................................................... 3-1
3.1 Web Site Statistics for Evaluating Visitors ......................................................................3-3
3.2 Introduction to Clustering and Segmentation ................................................................3-53
iv
For Your Information3.3 Customer Profiling.........................................................................................................3-79
3.4 Exercises ......................................................................................................................3-119
3.5 References....................................................................................................................3-120
Chapter 4 Attracting Cyber Consumers ............................................................... 4-1
4.1 Introduction to Web Site Marketing.................................................................................4-3
4.2 Evaluating Visitor Behavior...........................................................................................4-51
4.3 Evaluating Web Page Design .........................................................................................4-69
4.4 Comparing Your Web Site to Competitors...................................................................4-106
4.5 Exercises ......................................................................................................................4-113
4.6 References....................................................................................................................4-114
Chapter 5 Evaluating Cyber Consumers .............................................................. 5-1
5.1 Descriptive Techniques for Evaluating Buyer Behavior..................................................5-3
5.2 Estimating the Propensity to Buy ..................................................................................5-21
5.3 Estimating the Propensity to Abandon the Site..............................................................5-33
5.4 Model-Based Selection of Banner Ads ..........................................................................5-54
5.5 Exercises ........................................................................................................................5-75
5.6 References......................................................................................................................5-76
Chapter 6 Keeping Cyber Consumers .................................................................. 6-1
6.1 Data Driven Service for Shopping Comparison Sites......................................................6-3
6.2 Introduction to Recommender Systems .........................................................................6-19
6.3 Recommender System Applications ..............................................................................6-27
6.4 Exercises ........................................................................................................................6-55
6.5 References......................................................................................................................6-56
For Your Information
vAppendix A Data....................................................................................................... A-1
A.1 Ad Campaign Data..........................................................................................................A-3
A.2 Banner Ad Data...............................................................................................................A-4
A.3 Buy Data and Abandon Data...........................................................................................A-6
A.4 Customers Data...............................................................................................................A-9
A.5 Direct Mail Data ........................................................................................................... A-11
A.6 Financial Services Data.................................................................................................A-13
A.7 Movie Data ...................................................................................................................A-15
A.8 Path Analysis Data ........................................................................................................A-18
A.9 Profile Data ...................................................................................................................A-19
A.10 Stochastic Process Data ................................................................................................A-21
A.11 Web Logs ......................................................................................................................A-22
A.12 Web Time Series Data...................................................................................................A-23
Appendix B SAS Programs ..................................................................................... B-1
B.1 The SAS System ............................................................................................................. B-3
B.2 Reading Web Log Files................................................................................................... B-9
B.3 A SAS Robot................................................................................................................. B-14
B.4 The Output Delivery System and HTML ..................................................................... B-21
B.5 Web Stats....................................................................................................................... B-23
B.6 Time Series Methods .................................................................................................... B-27
B.7 Analysis of Data from Designed Experiments.............................................................. B-30
B.8 Transition Probabilities for Stochastic Processes.......................................................... B-31
B.9 Logistic Regression....................................................................................................... B-32
vi
For Your InformationB.10 Data Driven Web Services ............................................................................................ B-34
B.11 Enterprise Miner Macro Variables and Score Code...................................................... B-40
Appendix C SEMMA Methodology..........................................................................
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