University fundraising campaigns are a unique type of cause-related marketing with its own challenges and opportunities. Campaigns like this typically last an extended period, such as five or more years, and goals exist beyond the dollar amount raised. These supplemental goals, such as awareness among potential future donators or brand reputation within the local community, are important to consider and strategize. There can also be unique limitations, such as requiring advertising specifically on recent large gifts or endowment programs. This research explores how machine learning techniques such as natural language processing can be used to optimize a fundraising campaign strategy, execution, and overall performance.
Anderson, Braden; Dobbs, Connor; Lam, Hien; and Santerre, John
"Professor Text: University Fundraising Optimization,"
SMU Data Science Review: Vol. 7:
1, Article 2.
Available at: https://scholar.smu.edu/datasciencereview/vol7/iss1/2