Education Commons^™

Optimizing The Enrollment Funnel With Decision Trees And Rule Based List, Stephen Merritt, Anne Francomano, Martin Garcia

SMU Data Science Review

In this paper, an analysis is presented of the enrollment funnel for prospective graduate school students, predicting application submission and enrollment. Efficient university outreach is critical to optimizing a positive interaction cadence for prospective students, reducing costs, and strengthening academic program revenue streams. Models employing rules, decision lists, and tree-based algorithms assessed the impact of a prospect's characterization and university outreach methods on application and enrollment probabilities. A novel two-stage modeling workflow, applied to each prediction problem, mirrored steps taken by a prospective candidate to become a future enrollee. This analysis could help a graduate school decide what communication mechanisms …