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Analytics Overview
DR. SATISH NARGUNDKAR
GEORGIA STATE UNIVERSITY
Key Tasks in Analytics/Data Mining
1.
Description/Visualization
• Charts/Graphs/Tabulations
2.
Segmentation
• Cluster Analysis
3.
Prediction / Classification
• Regression Techniques – Linear, Logistic
4.
Association
• Market Basket Analysis
5.
Optimization
• Linear Programming
The Data Mining Process
Shearer, 2000
The Cross-Industry Standard Process for Data Mining (CRISP-DM)
Application in Financial Services
Stage 1
Product
Planning
Customer Stage 2
Acquisition
Customer
Valuation
Stage 4
Collections
and
Recovery
Customer
Management
Stage 3
Measuring Effectiveness
Percent of potential
responders captured
Lift/Gains Chart
100
Targeting
90
Random mailing
45
0
45
100
Percent of population targeted
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