September 2016

September 2016 Meeting

September 21, 2016 | 12:00pm - 2:00pm

Machine Learning and Artificial Intelligence applied to a Pharmaceutical Marketing Problem

Machine Learning and Artificial Intelligence have increasingly been used as innovative ways to extract meaningful value from data. This presentation will describe how those techniques were applied to generate a set of business rules and a predictive model for a pharma company to increase their physician client base’s propensity to prescribe their drug to their patients as opposed to the competition’s drug(s). The result is a personalized recommendation for each physician, with accompanying auditable rules to audit results and validate success.


Michael Eichorst

Michael Eichorst

Senior Vice President, Citibank

Michael Eichorst is currently SVP at Citibank and has over 30 years’ experience applying analytic techniques in banking to maximize the business impact of their investments in marketing and advertising. That has included roles as Strategic Planning Executive and Head of Analytics for the Chase Credit Card Business, and head of Marketing Analytics for Branch Banking, Personal Banking, Home Equity, Mortgage, and Wealth Management. He pioneered the use of Market Mix Modeling at Chase, TIAA-CREF, and at Citibank. Mike has been President of the NY chapter of INFORMS, a member of the Editorial Advisory Board for 1to1 Magazine, and judge for the annual “Gartner Impact Awards” contest. He is a frequent speaker at Industry conferences, including those sponsored by Business Week, American Banker, Acxiom, MMA, Marketing Evolution, SPSS, TIMS/ORSA, Business Objects, SAS, Fair-Isaacs, and others. He holds a Bachelor’s degree in Electrical Engineering from SUNY Stony Brook, was inducted into the National Engineering Honor Society, and received an MS in Management Science from Long Island University, where he was later awarded the Plock Prize for "Exceptional Scholarship and Contributions to the Advancement of Engineering and Science".