Abstract

University fundraising campaigns, which are typically a multi-year endeavor, help institutions build a strong financial foundation to enable a unique student experience. At the heart of effective fundraising is having strong relationships and partnerships with certain audiences that provide the best donation opportunities. Generally, alumni networks and the local community makeup these audiences as strong fundraising bases. Therefore, universities have a significant responsibility in developing these relationships to gain deeper insights into their constituents' needs and interests. This enables them to tailor effective engagement strategies, thereby increasing the likelihood of meeting donation expectations. This research explores how machine learning techniques can be used to predict who is most likely to donate and generate personalized email communication content at an individual level to maximize donations. The opportunity to automate email campaigns with a personalized touch with the goal of increasing the lifetime value of each donor can be beneficial to SMU over several years.

Recommended Citation

O'Neal, Jasmine; Hossain, Akib; and Bhalerao, Yogesh (2024) "Personalization: University Fundraising," SMU Data Science Review: Vol. 8: No. 1, Article 3.
Available at: https://scholar.smu.edu/datasciencereview/vol8/iss1/3