Lecture Outline:
1. Introduction to Data Warehousing, Data Mining and the Customer Management Lifecycle. Examples from the credit card industry, insurance, airlines and banking.
2. Overview of basic statistics concepts and methods.
3. Introduction to Data Warehousing - The business dimensional lifecycle.
4. Data Warehousing - Project planning for managing a data warehouse Project.
5. Data Warehousing - Requirements gathering.
6. Data Warehousing examples from the Healthcare industry.
7. Online Analytic Processing (OLAP).
8. Automatic Cluster Detection.
9. Link Analysis.
10. Neural Networks & Genetic Algorithms.
11. Data Mining in customer acquisitions, e.g. credit card acquisition campaigns. Use of Logistic Regression models.
12. Data Mining in customer acquisitions - Discriminant Analysis models.
13. Data Mining in customer acquisitions - Measuring Customer Lifetime Value.
14. Customer Management - managing a credit card customer base.
15. Introduction to decision tree modeling.
16. Setting customer management policy - effect of management policies on
customer spending and credit losses.
17. Management of customer attrition and collections efforts.
18. Overview of CRM products and companies.
19. Market Basket Analysis.
20. Web mining applications in e-marketing.
21. Web mining applications in e-marketing-click-through rates and conversion rates for Banner ads. Placement of banner advertisements.
22. Designing E-loyalty programs.
23. Text mining and knowledge management systems.
24. Spatial data mining.
25. Data Visualization.