Program Content:
Businesses around the globe have deployed analytics for the business impact it delivers. Across many industries and departments, predictive analytics has been applied to address a vast range of business challenges. What’s next? In this webinar, Dr. Eric Siegel offers his predictions.
Join Dr. Siegel and Anne Milley for a look at the hot trends shaping how organizations will use predictive analytics in 2010. Explore three emerging opportunities that will ultimately lead to new insights and better answers.
Trend #1: Innovative Applications – Taking a step beyond standard business applications such as those in marketing, fraud, and credit scoring, innovative applications of predictive analytics benefit organizations in new and creative ways, representing a virtually boundless incoming wave of new "killer apps." Data-driven models predict new things such as the reliability of hardware and corporate processes alike, and drive all kinds of organizational decisions, for the likes of air traffic management, military operations, mobile consumer applications, and startup investment strategy.
Trend #2: Data, Data, Data – New data sources include "unstructured" textual data and (quite structured) social network analysis. On the social data side, there's great value gained leveraging the simple fact that people behave similarly to those to whom they're socially connected. Telecommunications, online social networks, and other verticals find that such "birds of a feather" churn and even commit fraud "together" in collusion.
Trend #3: New Methodologies – Advanced analytical methods, are increasing in scope and reach. For example, incremental lift modeling is branching out, with applications going beyond response and churn modeling, identifying those customers most "persuadable" by new kinds of marketing contact or treatment.
Do our experts have it correct? No matter your role or use of predictive analytics, this webinar provides insights that you can use to help your organization make better, more informed decisions.
Intended Audience and Level of Understanding:
This seminar is intended for analytics decision makers, direct marketing or online marketing managers, those responsible for improved response rates and retention, marketers responsible for up-sell and cross-sell, analysts, data warehouse administrators, and those who wish to extend their expertise in predictive analytics.
About Eric Siegel, Ph.D., Conference Chair, Predictive Analytics World
Dr. Eric Siegel is the Conference Chair for Predictive Analytics World, the business-focused event for predictive analytics professionals, October 20 and 21 in Washington, DC. He is an expert in predictive analytics and data mining and a former computer science professor at Columbia University, where he won awards for teaching, including graduate-level courses in machine learning and intelligent systems - the academic terms for predictive analytics. After Columbia, Dr. Siegel co-founded two software companies for customer profiling and data mining, and then started Prediction Impact in 2003, providing predictive analytics services and training to mid-tier through Fortune 100 companies.
Dr. Siegel is the instructor of the acclaimed training program, Predictive Analytics for Business, Marketing and Web, and the online version, Predictive Analytics Applied. He has published 13 papers in data mining research and computer science education, has served on 10 conference program committees, and has cochaired an Association for the Advancement of Artificial Intelligence Symposium held at MIT.
As senior director of SAS’ technology product marketing in worldwide marketing, Anne Milley oversees the marketing of SAS technologies. Her ties to SAS began with her thesis on bank failure prediction models and the term structure of interest rates. She completed this at The Federal Home Loan Bank of Dallas and became a manager in the credit group. She continued her use of SAS at 7-Eleven, Inc. as a senior business consultant performing sales analysis and designing and conducting tests to aid in strategic decision-making, e.g., price sensitivity studies, advertising and promotion analysis.
Milley has authored various papers, articles and an award-winning report for the 1999 KDD Contest. She co-chaired the SAS Data Mining Technology Conferences, M2001 and M2002 as well as SAS’ inaugural forecasting conference, F2006. She has served on web mining committees for KDD and SIAM and on the Scientific Advisory Committee for Data Mining 2002. In 2008 she completed a five-month working sabbatical at a major financial services company in the United Kingdom.
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SAS Analytics can be applied to a vast range of business challenges across many industries and departments. To learn more about what you can achieve with SAS Analytics, explore the SAS Analytics Info Kit. |
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