In our last post, we talked about how insights derived from data are the missing ingredient for prioritizing enrollment management initiatives and identifying students to recruit.

But how do you put everything together to create an enrollment strategy that makes sense for your school and is possible to achieve?

That’s where predictive and prescriptive analytics comes in.

Predictive and prescriptive analytics software, like Othot’s platform, offers powerful capabilities that can make all the difference to your strategies and your budgets. With analytics, we would have known how a marketing campaign, a campus visit, or a financial aid award would influence a student’s decision to apply, enroll, and persist.

During our tenure in higher education, there were many times when this type of intelligence would have been critical to our decision making. In this post, we’ll share some trials and tribulations from our time in the Admissions office and how our experiences could have been different with predictive and prescriptive analytics software.

Hindsight is 20/20

Looking back, if we had enrollment analytics software, we could have used different strategies and tactics to achieve a better result. We could have applied the intelligence to the current class to improve results with the same or less effort.

With predictive and prescriptive analytics, we could have improved the efficiency of our teams and increased our focus on student success.

We can’t change the past, so we’ll fast forward to now. With declining and stagnant enrollment and retention rates at many colleges and universities, Othot’s SaaS model provides an edge in Admissions leadership.

Admissions professionals can improve their strategies with prescriptions derived from advanced analytics.

So, if you are looking to make a positive impact now or for your next enrollment class, keep reading below!

Your Questions. Answered.

At any point along the enrollment lifecycle, you want to develop strategies and execute tactics to improve your likelihood of success.

How great would it be to know who to target AND how at every stage of the enrollment process?

Othot’s platform can provide answers to what worked, why it worked, and how to implement strategies and tactics for the coming year with the data to back it up.

Wouldn’t it be nice to answer these questions with certainty using data from your previous enrollment years?

  • How can I improve the efficiency of my recruitment/admissions team, focusing on a specific population of students?
  • How can I spend less next year on the new student population and achieve increased enrollment or a higher quality of student? (Or if it’s even possible?!)
  • What activities yield the best results, during what stage of the enrollment lifecycle?
  • How can we develop a better strategy to recruit a more diverse population?

These answers and more are available when you use Othot’s platform.

Advanced Analytics at Work

Here are two examples:

Campus Visits
You have data from previous years that show students (enrolled or not enrolled) who attended a campus visit. Let’s look at the attributes associated with each individual student who attended the visits.

Next, we take that data and show you which individual students from your current enrollment class are impacted by a campus visit. Then you can target your marketing campaigns to the appropriate population. This information is available on an individual and group level.

Financial Aid
Let’s say that you employed a financial aid strategy two years ago that included increasing institutional gift aid to every student that was admitted. Last year, you had a different financial aid strategy that was more merit-based or selective.

Othot takes the data from the past years and provides you with a strategy that will tell you which students are most impacted by what dollar amount of aid. For example, two years ago you offered $20,000 to student A. Now with advanced analytics, we now know that $15,000 would have had the same impact on that student’s likelihood to enroll. Apply that logic to the current class, and you have a financial aid strategy that works for you.

With this information, you can either spend less money to get the same number of students or provide more aid to other potential students that are positively impacted to increase enrollment all while keeping your aid budget flat.

Use the same money, allocate it differently, and shape your class.

So, who doesn’t need predictive and prescriptive analytics? 

Success in Admissions and Higher Education can be summed up by being able to anticipate obstacles and “see around the corner before you get there.” 

That’s why we would have loved to have predictive and prescriptive analytics software, like Othot’s platform, when we worked in Admissions.

To put it in a more fun way, Othot is like using your go-go gadget neck and getting a crystal-clear view, way before that corner approaches!

This post is co-authored by Traci Roble.