Leverage a wealth of historical data to seek answers to questions such as which predictive modeling methods will work best, which factors will influence donation likelihood, and what’s the best way to make the results actionable for university advancement
Prominent university in Great Lakes region with over 12,000 students, more than $8 billion in total endowment, and 67 undergraduate academic programs.
The university was searching for a way to define which of the donors in their university advancement database were most likely to give. This would enable the university to more effectively target staff time and efforts.
The university engaged with Ironside data scientists to collect, prepare and analyze data from 20+ years of past donor behavior—and to test and select statistical modeling methods to maximize prediction accuracy, identify the strongest drivers of behavior, and integrate predictive scores into daily university advancement activities. This required Ironside and the university to:
Analyze Available Information
Model and Score
KEYS TO SUCCESS
Predictive donor scoring is allowing the university to: