Spotlight On KPI: Higher Education Applicant Yield Rates
One of the most critical set of metrics for Higher Education organizations is related to applicant yield rates. In this blog I will discuss, and illustrate, an example of how this set of metrics can be visualized, beginning with the first point of contact point a student has with a university, an inquiry from a prospective student. Figure 1 depicts a scenario where 1000 inquiries from prospective students are received, of these inquiries 600(60%) “Did Not Apply”, and 400(40%) “Applied”.
In order to dive deeper into this information, the next step is to breakdown the Application Decisions, as displayed in Figure 2. It’s important to note that at this point in the process we are left with 400(40%) prospective students of the total 1,000 inquiries. The chart shows that of the 400 applicants there are 100(25%) “Not Admitted”, and 300(75%) “Admitted”.
As we continue to drilldown deeper into the data it is necessary to breakdown the number of students still remaining into a pool of prospective students whom have enrolled. Keep in mind that initially we began with 1000 inquiries, and thus far in the process there are 300(30%) remaining which will make an enrollment decision. Figure 3 shows that in this scenario 75(25%) are “Not Enrolled”, and 225(75%) are “Enrolled” at this snapshot in time.
Finally we will analyze the prospective students whom have “Deposited/Confirmed”, note that there are 225(22.5%) inquiries remaining at this point in the process. As illustrated in Figure 4 we can now see that there are 25(11.1%) “Not Deposited/Confirmed”, and 200(88.9%) are “Deposited/Confirmed”. This provides a total yield from “Inquiry” to “Confirmed” of 20%, and a loss of 80%.
The complexity of this scenario could certainly increase by adding filter criteria to the process such as; College, Student Type, Gender, Athletic Status, State, Financial Need, etc., however, in this scenario, we examined a simple example of a yield rate using a funnel cone chart type and a method utilizing a funnel cone chart process.
Zach Breimayer- Technical Consultant, iDashboards