Othot developed models for a higher education institution after its initial aid allocation and to manage its appeals process. Using Sensitivity Analysis, the institution discovered which students were more sensitive to incremental aid awards.
The institution evaluated each prospective student for appeal, and disbursed additional funding only when the models deemed it necessary.
The institution is currently on target to grow its overall enrollment by 10% compared to last year, while managing to spend the same amount of aid through the appeals process.
Othot and the higher education institution are partnering to create a financial aid matrix to inform the budget for 2019 and evaluate prospect buys.
For a large public university, the Othot platform uncovered unique factors that influenced out-of-state students to enroll and created models for those markets that accounted for critical differences in behavior and performance.
The University restructured its key out-of-state market recruitment approach and utilized Othot’s financial aid sensitivity to determine which students to impact with additional aid.
Initial results showed an increase in admits (10 percent) and deposits (20 percent) year-to-date from key out-of-state markets.
The University is taking Othot’s predictions and integrating them into its CRM to automate marketing campaigns based on the predicted likelihood scores for future prospects.
The Othot platform showed a large public university that a time-intensive recruitment tactic had little to no impact on likelihood to enroll, but phone calls from a current student and a specific email/phone cadence were very impactful.
The recruitment team refocused priorities on the phone and email campaigns.
The platform’s predictive models provided a leading indicator that showed the University could hit its enrollment goal based on the quality and quantity in the applicant pool and could shift its efforts to converting students from the admit and deposit phases.
The large recruitment and admissions team is empowered to use the platform and prioritize their day-to-day activities versus having one user or consultant own all of the data and insights.
Othot’s platform showed a large public research institution which 20 percent of their purchased names would produce 90 percent of their enrollees, as well as who would respond most favorably to a viewbook.
The University focused its spend on those students most impacted by a viewbook.
The University reduced its viewbook budget by more than 10 percent and still met its overall enrollment target and shaped the class.
The team identified their next challenge and is using the platform to help allocate merit aid.
The Othot platform revealed engagement metrics were down year-over-year for a small, private liberal arts college and that campus visits were a top indicator for yield.
The College revamped its strategy to focus on driving campus visits through incentivized travel vouchers for early action students.
The college gained 30 additional students and $800,000 in net tuition revenue with a $32,000 investment in the travel vouchers.
The team is directing its energy to influence early action and regular decision candidates with optimized financial aid offers.
A large public higher education institution needed to accelerate its access to predictive modeling to meet enrollment goals during a critical period in its enrollment cycle.
The University and Othot collaborated to expedite the onboarding process so the University could use predictive modeling for its current class.
Insights from the platform showed the University that it had enough applicants in its pool and it could focus its efforts on accepted student campus visits and financial aid allocations to convert admits to deposits.
Othot is working with the University to review the financial aid appeals process and help with summer melt.