For the third installment in our impact series, I’d like to provide another financial aid example. Last week, I discussed how a customer used Othot’s insights to target a narrow population of students with a specific aid incentive, and this week, I’ll look at financial aid appeals. Specifically, how one of our customers used insights and analyses from the platform to manage their financial aid appeals process and overall spend. It’s a good example because this school achieved its desired enrollment growth, while maintaining the same appeals budget from the previous year.
We developed modeling for a school in parallel to its initial aid allocation, but in time for its appeals process. Using the Sensitivity feature in the Othot platform, we showed the institution which students were more sensitive to incremental aid awards and ultimately which students required the additional requested aid. Taking that a step further, our models also identified which students would still have a high likelihood to enroll if no additional aid was provided through the appeals process.
The institution evaluated each accepted student for appeal and disbursed additional incremental funding only when the model deemed it necessary. The prescriptive insights from the platform demonstrated exactly how much additional money would be required to increase a student’s likelihood score. The institution was able to evaluate the cost/benefit of how to allocate the appeals budget and could optimize the likelihood of student enrollment, while managing to the planned budget.
The institution is currently on target to grow its overall enrollment by 10% compared to last year, while spending the same amount of aid as last year in the appeals process. While other attributes and activities throughout the enrollment cycle also contributed to enrollment growth, this example demonstrates how the Othot Platform improved the appeals process to keep the institution on budget.
Othot is partnering with the institution to evaluate and restructure its financial aid matrices for the upcoming enrollment cycle. By analyzing aggregate variables within Othot’s Sensitivity feature, the institution will better inform its strategy year-over-year to evaluate a larger population of students based on merit quality, geographic location and other characteristics and attributes from the prospective student pool.
Continue to stay turned for our last impact series post next week. As always, if you would like to learn more or start gaining value for yourself and your institution, please reach out to me at email@example.com.