The University of Oklahoma did just that. It took a data-informed approach and created predictive models to assess the probability that an admitted student would enroll, then determined which actions recruitment officers should take. By narrowing the focus to a smaller list of students, recruitment officers could now pursue better prepared students–and use fewer resources to do it. As a result, the university had its largest and most academically prepared student body ever, including more National Merit students than any other public or private university.
As Oklahoma learned, analytics can help universities answer questions like this and more. Such as, which scholarships and amounts would not only attract select students, but also get them to apply and ultimately enroll? Are students with higher SAT scores more likely to be engaged throughout campus, perform better academically, and graduate? Are first-generation students more likely or less likely to get involved in campus? By answering questions like these, universities can tailor their recruitment and marketing efforts to enroll more successful cohorts of students.