Predictive Analytics for Business and Marketing Hosted by

Predictive Analytics for Business and Marketing Hosted by Prediction Impact, Inc. in association with the Emetrics Summit ____________ Eric Siegel Ph. D. Prediction Impact, Inc. eric@predictionimpact. com (415)385 -1313 © 2007 Prediction Impact, Inc. All rights reserved

Predictive Analytics for Business and Marketing 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 © 2007 Prediction Impact, Inc. All rights reserved

Predictive Analytics for Business and Marketing 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 © 2007 Prediction Impact, Inc. All rights reserved

Predictive Analytics for Business and Marketing 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: – – 100 k free subscribers 30 k 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. © 2007 Prediction Impact, Inc. All rights reserved

Predictive Analytics for Business and Marketing Summary of Killer Apps • Increased profit with response modeling for direct marketing – – • Increased customer retention by predicting defection – – • Dynamic, behavior-based content selection From AB selection to ABC. . . Z selection Increased sales by predicting cross-sell opportunities – – • Retaining tenured customers Converting first-time customer Increased response with targeted content – – • Increase response rate Decreased spending Recommendations engine Collaborative filtering Increased net worth by predicting customer lifetime value (LTV) – – Higher valued acquisitions Optimized retention targeting © 2007 Prediction Impact, Inc. All rights reserved

Predictive Analytics for Business and Marketing Jellybeans Brain Teaser • Good: red red red • Good: blue yellow green orange • Bad: black moive magenta beige turquoise fuisha © 2007 Prediction Impact, Inc. All rights reserved

Predictive Analytics for Business and Marketing How a Crystal Ball Works © 2007 Prediction

Predictive Analytics for Business and Marketing Predict This! • • Introduction Data Overload How Modeling Works Statistical Models in Fashion Modeling Methods Deployment & Results Conclusions © 2007 Prediction Impact, Inc. All rights reserved

Predictive Analytics for Business and Marketing Can Computers Think © 2007 Prediction Impact, Inc.

Predictive Analytics for Business and Marketing 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 © 2007 Prediction Impact, Inc. All rights reserved

Predictive Analytics for Business and Marketing Recommended References Sources • • • Prediction Impact’s bi-annual email newsletter: Case studies, articles, events. Click “subscribe” at www. Prediction. Impact. 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 Jim. Novo. com for his “Drilling Down” book (first 9 chapters for free) – Email Marketing by the Numbers, Chris Baggott © 2007 Prediction Impact, Inc. All rights reserved

Predictive Analytics for Business and Marketing 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! © 2007 Prediction Impact, Inc. All rights reserved

Predictive Analytics for Business and Marketing Predictive Analytics and Data Mining Applications: Verticals: § § § § 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 § § § 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 © 2007 Prediction Impact, Inc. All rights reserved

Predictive Analytics for Business and Marketing 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: • • Eric Siegel, Ph. D. , President Prediction Impact, Inc. San Francisco, California eric@predictionimpact. com (415) 385 -1313 For our bi-annual newsletter, click “subscribe”: www. Prediction. Impact. com To receive notifications of training seminars: training@predictionimpact. com Closely collaborating partner firms East coverage © 2007 Prediction Impact, Inc. All rights reserved