Applying Holistic Admissions To and Through Yield

January 16, 2025

minutes read.
Applying Holistic Admissions To and Through Yield

Holistic admissions has been championed as the antidote to reductive, numbers-driven decision-making. By considering the full breadth of an applicant’s background, experiences, and potential, institutions proudly craft classes that reflect their values. But here’s the uncomfortable truth: most colleges abandon the principles of holistic admissions the moment the acceptance letter is sent.

Why do we stop listening?

Admissions teams pour resources into understanding who students are before they’re admitted, but once decisions are made, they often revert to outdated, scattershot approaches to yield management. Every admitted student is treated the same, despite the clear signals they send about their level of interest, intent, and engagement. This approach wastes time, alienates students, and undermines the entire purpose of holistic admissions.

It’s time to redefine holistic admissions—not as a process that ends with an offer, but as a commitment to respecting and responding to each student’s journey through their decision-making process. Machine learning makes this possible, revealing the hidden patterns in post-admission behaviors like event attendance, email replies, and portal activity. These signals hold the key to understanding where students stand and what they need to convert.

Instead of flooding students with generic outreach, machine learning enables admissions teams to prioritize their efforts where they matter most: with high-potential students who are actively deciding, or those who need encouragement to stay engaged. By ignoring these signals, institutions squander their counselors’ time and lose valuable opportunities to connect with students who might otherwise enroll.

Redefining holistic admissions demands that we extend its principles beyond the decision. The same care used to admit students should be applied to yield them. If institutions truly believe in treating students as more than data points, they must commit to engaging admitted students with the same intentionality—powered by machine learning and the respect for individual signals it enables. Anything less is a betrayal of the values holistic admissions claims to champion.

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