Predictive Modeling in Annual Giving
Recorded On: 06/21/2016
Applying the same techniques used by meteorologists to forecast the weather or banks to evaluate someone's creditworthiness, predictive models can help annual giving and alumni relations programs prioritize prospects and identify winning segments. Modeling can help predict which individuals are most likely to respond to an appeal, attend an event, get involved as a volunteer, sign up for recurring gifts, meet with a gift officer, and more!
Register now for your entire team to learn how to use predictive models to drive success in your annual giving and alumni relations programs.
This recording is eligible for 1.25 points of CFRE credit.
WHAT YOU'LL DISCOVER
- Overview of predictive modeling's purpose, terminology, processes, and applications
- Guidelines for building your own predictive models either in-house or by outsourcing
- Strategies for using predictive models to increase alumni engagement and annual giving
- And more!
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Director of Engagement Analytics, Massachusetts Institute of Technology (MIT)
Ryan Bersani is the Director of Engagement Analytics at the Massachusetts Institute of Technology (MIT) Alumni Association, where he champions the use of analytics to support strategic decision-making within all areas of the Alumni Association. Previously, he served as a Senior Data Analyst at MIT, a Data Analyst and Online Giving Manager in the Office of Annual Giving at Boston University, and a Mathematics Teacher at Boston College High School. An active speaker with CASE and incoming member of the CASE DI Board of Directors, Ryan holds a degree in Mathematics from Boston University.