Applying the same techniques used by meteorologists to forecast the weather or banks to evaluate someone's creditworthiness, predictive models can help advancement 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 build and apply predictive models to improve your annual giving results.This webinar is eligible for 1.25 points of CFRE credit.
WHAT YOU'LL DISCOVER
- Tips for understanding basic terminologies and uses for predictive modeling
- Guidelines and steps for building a predictive model on your own
- Tactics for applying model scores to improve prospect research and segmentation
- Methods for evaluating the effectiveness of your models
- Examples from other institutions, 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.