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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, Inc. (415)
Predictive Analytics for Business and Marketing © 2007 Prediction Impact, Inc. All rights reserved Case Study: Direct Response 1.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
Predictive Analytics for Business and Marketing © 2007 Prediction Impact, Inc. All rights reserved Problem-Solving Session Template 1.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
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.
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
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
Predictive Analytics for Business and Marketing © 2007 Prediction Impact, Inc. All rights reserved How a Crystal Ball Works
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
Predictive Analytics for Business and Marketing © 2007 Prediction Impact, Inc. All rights reserved Can Computers Think
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
Predictive Analytics for Business and Marketing © 2007 Prediction Impact, Inc. All rights reserved Recommended References Sources Prediction Impact’s bi-annual newsletter: Case studies, articles, events. Click “subscribe” at 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)JimNovo.com – Marketing by the Numbers, Chris Baggott
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!
Predictive Analytics for Business and Marketing © 2007 Prediction Impact, Inc. All rights reserved Predictive Analytics and Data Mining Applications: Response modeling for direct marketing Product recommendations Dynamic content, 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
Predictive Analytics for Business and Marketing © 2007 Prediction Impact, Inc. All rights reserved Predictive Analytics and Data Mining Team 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., President Prediction Impact, Inc. San Francisco, California (415) For our bi-annual newsletter, click “subscribe”: To receive notifications of training seminars:
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