Last week we looked at acquisition models for higher education. This week we are going to look at retention models. Retention is important because on average it costs about 7 times more money to acquire a student than to keep one. Think of all of the advertising, incentives, time on the phone, registration expenses and, if they are on financial aid, the time spent with their FAO.
Because of all of the expenses involved in acquiring a student, it is important to make sure they actually start classes, and once they do, to make sure they graduate. But are some students a higher risk not to start? Or to not graduate? What if you could identify these students at risk of dropping out or falling out? How much incremental revenue could you generate?
Fall out is a very important problem in education. Students sign up, but somewhere between their decision to go to college, and their actual start date they change their minds. That is, they fail to start. Statistical analysis can determine which students have a high risk of fall out. If you know who is at more at risk of fall out, you can proactively manage this student segment between the enrollment date and start date to ensure they actually start classes. This allows you to allocate your resources where they are needed most.
And, there is also the issue of dropping out. A lot of students don’t finish / graduate. Sometimes this can be due to a variety of reasons – family, personal, academic or financial. But statistical analysis can parse out key characteristics that identify those at risk from those who are more at risk of dropping out. Again, you have the opportunity to more closely manage that relationship. Think of it like having an early warning signal, and the opportunity to intervene before they actually drop out.
Last week we talked about the acquisition of new students. This week we talked about increasing start and graduation rates. Next week we will talk about how to combine the two. You will see that when we do, we really start to maximize the ROI on your marketing dollar.