Matthew Newman (Sociology), Sonia Xu (Statistics), and Alexandra Zrenner (Economics) spent ten weeks exploring giving patterns and demographic characteristics of anonymized Duke donors. They worked closely with the Duke Alumni Affairs and Development Office, with the goal of understanding the data and constructing tools to generate data-driven insight about donor behavior.
The team used a variety of statistical techniques to build predictive models of giving behavior, and they also used sophisticated high-dimensional clustering techniques to group donors according to similarity of demographic characteristics and university experience. A key finding was that high-giving and low-giving donors exist in every cluster, an insight which will aid the Development Office in constructing strategies to cultivate future donors.
- Stephen Bayer, Associate Vice President for University Development
- Nathalie Spring, Duke University Development
- Robert Calderbank, Director, iiD
- Sheng Jiang, Ph.D. student, Statistics
- Matthew Newman, Duke University Sociology
- Sonia Xu, Duke University Statistics
- Alexandra Zrenner, Duke University Economics
- All quantitative STEM
“The Data+ program was filled with intelligent people from all different fields, so it was a great learning experience. Furthermore, since we worked in teams, it taught me how to work with others in a more efficient, collaborative, and overall better level. Working to meet our clients’ needs, I feel as if I gained real-world work experience in a classroom-like atmosphere (project mentor as my teacher, my group as the students). It is a great transition for people who are unsure of what they want to do with their careers or feel under-qualified to pursue a real internship.”
-Sonia Xu, Duke University Statistics