Predictive Analytics World Conference: Agenda At a Glance

DAY 1: Monday October 19, 2009
Full-day Workshop Putting Predictive Analytics to Work James Taylor, CEO, Decision Management Solutions Room: Poplar	Full-day Workshop Hands-On Predictive Analytics Dean Abbott, President, Abbott Analytics Room: Walnut B

DAY 2: Tuesday October 20, 2009
8:00am-9:00am	Registration & Continental Breakfast
9:00am-9:50am	Keynote Five Ways to Lower Costs with Predictive Analytics Eric Siegel, Ph.D., Conference Chair Room: Magnolia
9:50am-10:10am	Platinum Sponsor Presentation The Perfect Storm: The Rise of Predictive Analytics Room: Magnolia
10:10am-10:30am	Morning Coffee Break – Exhibit Hall Open from 10:10am to 7:30pm Upper Foyer / Exhibit Hall
	Track 1: Thought Leader Room: Magnolia	Track 2: Non-profit Room: Walnut A&B
10:30am-11:20am	Case Study: Infinity Insurance & PREMIER Bankcard Putting Predictive Analytics to Work James Taylor, Decision Management Solutions	Case Study: National Rifle Association How to Improve Customer Acquisition Models with Ensembles Dean Abbott, Abbott Analytics
11:20am-12:30pm	Multiple Case Studies: Anheuser-Busch, Disney, HP, HSBC, Pfizer, and others The High ROI of Data Mining for Innovative Organizations John Elder, Elder Research, Inc. Room: Magnolia
12:30pm-1:45pm	Birds of a Feather Lunch Room: Pan Am Foyer
1:45pm-2:35pm	Keynote Predictive Analytics over On-line and Social Network Data Usama Fayyad, Ph.D., Open Insights Former Chief Data Officer, Yahoo! Room: Magnolia
2:35pm-2:45pm	Gold Sponsor Presentation Leveraging Speech Analytics to Gain a Competitive Edge Room: Magnolia
2:45pm-2:55pm	Session Break Upper Foyer / Exhibit Hall
	Track 1: Incremental Modeling (Uplift Modeling) Room: Magnolia	Track 2: Telecommunications Room: Walnut A&B
2:55pm-3:45pm	Case Study: Target Challenges of Incremental Sales Modeling in Direct Marketing Andrew Pole, Target	Case Study: Sunrise Communications (Switzerland) Cost Reduction in Bill-Insert Campaigns With Predictive Analytics Stamatis Stefanakos, D1 Solutions AG
3:45pm-4:30pm	Case Study: US Bank Raising the Bar in Cross-Sell Marketing With Uplift Modeling Michael Grundhoefer, US Bank	Case Study: Optus (Australian telecom) Know Your Customers by Knowing Who They Know, and Who They Don't Tim Manns, Optus
4:30pm-4:55pm	Afternoon Coffee Break Upper Foyer / Exhibit Hall
	Track 1: Financial Services Room: Magnolia	Track 2: Telecommunications Room: Walnut A&B
4:55pm-5:40pm	Case Study: PREMIER Bankcard The Development of a "Good Customer Score" for Use in Customer Acquisition, Rewards, Retention and Recovery Rex Pruitt, PREMIER Bankcard, LLC	KDDcup 2009 Competition Results: Orange Labs (France Telecom) Churn, Baby, Churn: Fast Scoring on Large Telecom Dataset Srivatsava Daruru, Univ. of Texas at Austin
	Track 1: Financial Services Room: Magnolia	Track 2: Text Analytics Room: Walnut A&B
5:40pm-6:30pm	Case Study: Citizens Bank Building In-Database Predictive Scoring Model: Check Fraud Detection Case Study Jay Zhou, Business Data Miners, LLC	Predictive Text Analytics Seth Grimes, Alta Plana Corporation
6:30pm-7:30pm	Reception Sponsored by Upper Foyer / Exhibit Hall
7:30pm-10:00pm	Sponsored by useR Meeting Room: Magnolia

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DAY 3: Wednesday October 21, 2009
8:00am-9:00am	Registration & Continental Breakfast
9:00am-9:50am	Keynote Opportunities and Pitfalls: What the World Does and Doesn't Want from Predictive Analytics Stephen Baker, BusinessWeek - author, The Numerati Room: Magnolia
9:50am-10:10am	Platinum Sponsor Presentation Strength in Numbers: ACE! Room: Magnolia
10:10am-10:30am	Morning Coffee Break – Exhibit Hall Open from 10:10am to 6:00pm Upper Foyer / Exhibit Hall
	Track 1: Verticals Room: Magnolia	Track 2: Forecasting Room: Walnut A&B
10:30am-11:20am	Case Study: Reed Elsevier Where Do We Go from Here - So the First Model Worked. What About the Next 6? John Mcconnell, Analytical People	Case Study: The Financial Times, The New York Times, Sprint-Nextel Predicting Future Subscriber Levels Michael Berry, Data Miners, Inc.
11:20am-12:10pm	Case Study: Amway Establishing a Performance-Based Culture with Predictive Analytics Mike Kinlaw, Alticor (Amway)	Case Study: Coke A Predictive Approach to Marketing Mix Modeling Ram Krishnamurthy, The Coca-Cola Co. & Anish Nanavaty, WNS Global Services, Inc
12:10pm-1:50pm	Birds of a Feather Lunch Room: Pan Am Foyer
1:50pm-2:40pm	Expert Panel: Predictive Analytics and Consumer Privacy Stephen Baker, BusinessWeek - author, The Numerati Jules Polonetsky, Future of Privacy Forum Mikael Hagstrõm, SAS Room: Magnolia
2:40pm-2:45pm	Session Break Upper Foyer / Exhibit Hall
	Track 1: Health Care Room: Magnolia	Track 2: Fraud Detection Room: Walnut A&B
2:45pm-3:35pm	Case Study: Lifeline Screening Segmented Modeling Applications in Health Care Industry Ozgur Dogan, Merkle	Keep Winning the Eternal Fraud Battles Antonia de Medinaceli, Elder Research, Inc.
3:35pm-3:55pm	Afternoon Coffee Break Upper Foyer / Exhibit Hall
	Track 1: Insurance Room: Magnolia	Track 2: Product Recommendations Room: Walnut A&B
3:55pm-4:45pm	Case Study: Zurich Top 10 Ways to be Successful in Implementing Predictive Modeling in Insurance Commercial Markets Joel Appelbaum, Zurich Steve VanDee, Zurich	Lessons That We Learned from the Netflix Prize Istvan Pilaszy, Gravity R&D
	Track 1: Insurance Room: Magnolia	Track 2: Education Room: Walnut A&B
4:45pm-5:30pm	Case Study: Aflac Establishing a Customer Retention Analytics Framework Heather Avery, Aflac	Case Study: Walden University, Kendall College, University of Liverpool The Use of Lead Scoring Solutions in the For-Profit Education Industry Sherry Bennett-Flatt, Laureate Higher Education Group Chris Scandlen, Laureate Education

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DAY 4: Thursday October 22, 2009

Full-day Workshop
The Best and the Worst of Predictive Analytics:
Predictive Modeling Methods and Common Data Mining Mistakes
John F. Elder, Ph.D., CEO and Founder, Elder Research, Inc.
Room: Hickory