Sharpening Instinct With Intelligence: Evansville's Story

Every admissions leader knows the value of counselor instinct. Those gut lists, built from calls, visits, and FAFSA completions, have long shaped how teams decide where to focus. But what happens when instinct collides with the reality of student behavior?

At the University of Evansville, Dr. Blair Doneske asked that exact question. His team had talented counselors and strong intuition, but too often the lists they built didn’t line up with actual outcomes. Some students who “looked strong” drifted away quietly. Others, dismissed as unlikely, enrolled after subtle but important engagement patterns.

By layering enroll ml’s behavioral intelligence on top of counselor instincts, Evansville shifted the conversation. Counselors didn’t lose their judgment, they gained confidence in it. Each morning now begins not with “first cup of coffee work,” but with prioritized lists that point them to the students whose behavior signals real potential or risk.

As Blair put it: “If the data matches your gut, great, it confirms your thinking. But when it doesn’t? That’s when you lean in. That tension is where opportunity lives.”

This case study shows how Evansville moved from guesswork to clarity, balancing the human side of admissions with machine learning precision—and building a culture where counselors spend more time doing what they do best: connecting with students.

Read the full case study here.