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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
Hosted by Prediction Impact, Inc. in association with the Emetrics Summit
________________________Eric Siegel Ph.D.Prediction Impact, [email protected](415)385-1313
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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
Case Study: Direct Response1. Company overview:
National veterans organization Non-profit organization; fund raising
2. General Objectives Find good donors Recapture “lapsed” donors Find “high dollar” donors
• There is often an inverse correlation between likelihood to respond and dollar amount of gift.
Cost-effective fund raising—net revenue
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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
Problem-Solving Session Template1. Overall strategy
Outline of initiative and its primary phases
2. Predictive modeling approach Prediction statement/goal Data required
• Applicable segments• Predictors
Deployment: How the model will be integrated or otherwise made use of Business case
3. Evaluation KPIs (a la business goals) Final AB test; control group Baseline method for comparison
4. Challenges and bottlenecks anticipated Organizational Technical
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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
Problem-Solving Session #1: Retention• Business: Web-o-Rama House of Metrics (worhm.com)• Year: 2012• Type: B-2-B• Description: Web analytics services for small to medium
businesses• Customer Breakdown:
– 100k free subscribers– 30k premium subscribers
• Credit card auto-bill monthly• High churn rate: 35% per year
• Problem: Attrition rate has increased 20% since last quarter, while conversions have remained the same. Another team is working on increasing conversions.
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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
Summary of Killer Apps• Increased profit with response modeling for direct marketing
– Increase response rate– Decreased spending
• Increased customer retention by predicting defection– Retaining tenured customers– Converting first-time customer
• Increased response with targeted content– Dynamic, behavior-based content selection– From AB selection to ABC...Z selection
• Increased sales by predicting cross-sell opportunities– Recommendations engine– Collaborative filtering
• Increased net worth by predicting customer lifetime value (LTV)– Higher valued acquisitions– Optimized retention targeting
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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
Jellybeans Brain Teaser• Good: red red red red red red red red red red red
• Good: blue yellow green orange
• Bad: black moive magenta beige turquoise fuisha
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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
How a Crystal Ball Works
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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
Predict This!
• Introduction• Data Overload• How Modeling Works• Statistical Models in Fashion• Modeling Methods• Deployment & Results• Conclusions
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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
Can Computers Think
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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
Next Steps for you• Moving towards a predictive analytics initiative
– List your top 3 to 5 business optimization objectives– Match the list of killer apps to these objectives– Scope the data collections requirements
• Other courses– The Modeling Agency's Level II and III Training– Tools courses, such as Salford Systems– These courses go beyond business apps to include science and
engineering
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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
Recommended References Sources• Prediction Impact’s bi-annual email newsletter: Case studies, articles, events.
Click “subscribe” at www.PredictionImpact.com.• www.KDnuggets.com: A comprehensive online reference and newsletter.• The UCI KDD Database Repository (kdd.ics.uci.edu): the most popular site for
datasets used for research in machine learning and knowledge discovery. But all the core references such as this are found under KDnuggets, above.
• The Cartoon Guide to Statistics, L. Gonick and W. Smith.• Data Mining: Practical Machine Learning Tools and Techniques with Java
Implementations, E. Frank and I.H. Witten.• Database marketing books for preliminary steps towards modeling, and for a
more holistic, less technical marketing viewpoint:– Strategic Database Marketing, Arthur Hughes– See JimNovo.com for his “Drilling Down” book (first 9 chapters for free)– Email Marketing by the Numbers, Chris Baggott
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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
Predictive Analytics and Data Mining Services:
• Defining analytical goals & sourcing data• Developing predictive models• Designing and architecting solutions for model deployment• "Quick hit" proof-of-concept pilot projects
Training programs:• Public seminars: Two days, in San Francisco and other locations• On-site training options: Flexible, specialized• Instructor: Eric Siegel, Ph.D., President, 15 years of data mining, experienced
consultant, award-winning Columbia professor• Training participants: Boeing, Corporate Express, Compass Bank, Hewlett-
Packard, Liberty Mutual, Merck, MITRE, Monster.com, NASA, Qwest, SAS, U.S. Census Bureau, Yahoo!
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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
Predictive Analytics and Data MiningApplications: Response modeling for direct
marketing Product recommendations Dynamic content, email and ad
selection Customer retention Strategic segmentation Security
– Fraud discovery– Intrusion detection– Risk mitigation– Malicious user behavior
identification Cutting-edge research for
groundbreaking data mining initiatives
Verticals: Online business: Social networks,
entertainment, retail, dating, job hunting
Telecommunications Financial organizations A fortune 100 technology company Non-profits High-tech startups Direct marketing, catalogue retail
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Predictive Analytics for Business and Marketing
© 2007 Prediction Impact, Inc. All rights reserved
Predictive Analytics and Data MiningTeam of several senior consultants:• Experts in predictive modeling for business
and marketing• Relevant graduate-level degrees• Communication in business terms• Complementary analytical specialties and
client verticals• Published in research journals and
industrials
Extended network of many more:• Closely collaborating partner firms• East coast coverage
Eric Siegel, Ph.D., PresidentPrediction Impact, Inc.San Francisco, California
[email protected](415) 385-1313
For our bi-annual newsletter, click “subscribe”:
www.PredictionImpact.comTo receive notifications of training
seminars: [email protected]