10 Performance Metrics to Boost Student Enrollment

The effects of COVID-19 have reshaped the landscape of higher education, making enrollment growth a challenging task for many institutions. With shifting priorities and new uncertainties in the education sector, achieving enrollment growth is no longer a guarantee. In response, universities must adopt innovative, fast, and user-friendly processes that can effectively boost enrollment and improve the student experience. This is where Data Analytics plays a pivotal role.

AI and ML have the potential to transform student experience across the admissions cycle. Universities can effectively study the data they garner from prospective students. Actionable insights from both high-level and granular analytics can be used to drastically improve your brand value, personalize conversations with students, boost enrollment rates, and elevate academic performance.

But what are these analyses? Why trust data analytics? And how can it help YOUR institution? Let’s find out.

How can Data Analytics boost student enrollment?

Data analytics steers you away from manual processes, giving you and your institution the right tools to effectively utilize the hoard of student data you’re sitting on. Not only does data analytics process large amounts of data in no time, but it also uses AI to improve its performance. The result? You get more actionable insights faster.

Here are some of the ways in which data analytics can help boost your institution’s student enrollment-

1. Targeted marketing: Get insights into the best times to reach prospects, what content works for them, and which channels you should regularly use for marketing your institution to them.
2. Better conversion rates: By looking at a few key data points about a student, data analytics can help you decide how many students you should admit, allowing you to maintain or even bump your tuition revenue.
3. Accurate identification of drop-off points: Data Analytics can predict exactly at what point a student might drop off from the funnel and help you avoid it.
4. Personalized interaction with prospective students: With insights on what a student is more likely to do next, data analytics can create customized and personalized admission experiences for your prospective students.
5. Reduced expenses and operational costs: If you keep your data analytics initiatives centralized, you can repurpose your performance models with ease and reduce overall operational expenses.

Analyzing data is one of the most important aspects of boosting student enrollment. But knowing what data will offer the right actionable insights for your institution is a different deal altogether.

Here are 10 performance metrics that we think are indispensable.

The student journey funnel

The student journey funnel gives you an overview of where your prospective students are in their journey toward enrolling at your institution. It covers the hundred thousand prospects that come across your university and bifurcates them into specific levels, including-

1. Leads generated.
2. Applications started.
3. Applications reviewed.
4. Applications accepted.
5. Course enrolled.

Looking at this metric, you would be immediately able to point out which stages are seeing the least conversion rates. You can also assess what the average wait time is for students in each stage. This data will help you make the right operational decisions and drastically speed up student enrollment.

Leads generated vs. expected

Zeroing in on the funnel’s first stage of the student journey can give you detailed insights into your lead generation process. Looking at it, metrics like impressions, click-through rates, contact sources, demographics, etc., come to mind. But an imperative factor to consider here is ‘Leads generated vs. expected.’

A month-on-month or year-on-year report of this metric can help you recognize which activities are working best when it comes to lead generation, allowing you to replicate your success and set realistic goals for the coming period.

Cost per lead

Marketing your institution to reach the right students comes at a cost. Looking at ‘Total Leads vs. Lead Conversion %’ will tell you exactly what that price is. And if you look at this metric campaign-wise, i.e., source-wise, you will learn what sources gave you the most leads at the lowest costs.

With this knowledge, you can easily redirect your funds to the campaigns that are working for your institution while also reducing your institution’s total expenditure on branding, marketing, and lead generation.

Applications received vs. expected

Branding and marketing your institution is only one aspect of enrolling students. You also have to consider how many students actually end up applying to your university. The ‘Applications received vs. expected’ metric gives you that number, offering detailed insights into how smooth (or difficult) your institution’s application process is.

A month-on-month view of this metric can help gauge the general student mindset when filling out their applications. Using this data, it’d be easier for you to generate automated messages that land in a student’s inbox, nudging them to complete their application on time. You can also recognize the drop-off points, which would help you zero in on the aspects of the application that cause them and optimize the application process accordingly.

Acceptances vs. yield%

While it’s common knowledge that both universities and applicants find the right fit through the process of elimination, the factors that they use to make their final decisions are a little more obscure. That’s where the Acceptances vs. yield% metric can help.

Collating data from thousands of interactions, this metric presents how many applications were received vs. how many of those actually converted. Moreover, diving into the details would also make it easier to pinpoint the top reasons why students choose not to enroll at your institution and address them.

Student demographics

One of the most obvious yet imperative metrics to look at, a student’s demographics can help you recognize where your institution’s reputation is most trusted. Using this data, you can redirect your resources to specific areas that you find most profit worthy.

Another aspect highlighted by this information is the set of regions where your brand has started to get recognition. This will point out which areas you should be focusing on when you plan to expand.

Applications Checked vs. Average Applications Reviewed

An instinctive next step in the student journey funnel is to check how your prospective students’ applications are being reviewed. This metric measures just that. It counts the number of applications checked and adds up the amount of time it took to review every single one of them. And the final result – Average Days till Application checked – emerges.

Using it, you can not only pinpoint and ease how the time-consuming parts of the application get reviewed. There are multiple techniques and AI technologies that you can incorporate at these stages – like the Document Intelligence tool developed by EDMO. This tool can help automate and streamline document processing, reducing the time spent on manual checks and allowing your staff to focus on more complex tasks.

Advisor Load

Dividing the ‘Average Days till Application Checked’ against individual advisors gives an insight into which advisors are doing it right, offering others the opportunity to learn and implement the more effective methods.

Once viewed along with the application backlog, Advisor Load provides a birds-eye view of the entire application review process, displaying a graph that, when combined with the Average Days till Application Checked stats, gives insights into how the average application review time can be optimized.

Courses Enrolled

The last stage in the student journey funnel is why everything that comes before it is imperative. One look at this metric, and you’ll know if the measures you’re taking to attract, recruit, and enroll better students are working or not.

When checked against the Deposit amount, Courses Enrolled also offers an insight into the amount of income being generated from student applications. A month-on-month or year-on-year view of this metric also helps set and achieve more realistic revenue targets. Speaking of revenue…

Total Revenue vs Expected Revenue

A breakdown of the total revenue basis your sales representatives’ performances offers ready insights into the deeper side of the enrollment process. It becomes much easier to understand which of them are doing better and why.

Enrollment Officers can also take a deeper dive into this metric by speaking to their sales representatives in person, figuring out their expertise, and utilizing these insights effectively. This way, it would become much easier to set realistic enrollment targets.

Bonus metrics

There are 2 aspects of lead generation and application progression that can give you detailed insights into the general student mindset. These include the Lead Distribution and the Application Dropout Probability graphs.

Lead Distribution

The Lead Distribution chart gives you an idea about which of your student prospects are extremely likely to apply at your institution (Hot lead), which ones are not interested at all (Cold lead), and which ones are unsure (Warm lead). It can also share details about the stage of the lead generation process they’re in.

Application Dropout Probability

The Application Dropout Probability, on the other hand, will help you zero in on the students that are going to drop out of the application process, helping you reach out to them and understand their quandaries.

Key Takeaways

Let’s re-examine the performance metrics that can help you boost your institution’s enrollment-

1. The Student Enrollment Journey Funnel
2. Leads Generated vs Expected
3. Cost per Lead
4. Applications Received vs Expected
5. Acceptances vs Yield%
6. Student Demographics
7. Average Days till Application Checked
8. Advisor Load
9. Courses Enrolled
10. Total Revenue vs Expected Revenue
11. Lead Distribution
12. Application Dropout Probability

Adapting to a data-driven mindset takes time. At first, you may lack certain types of data, or find that certain insights don’t work for your institution. However, by establishing a culture of data sharing and hygiene and assuming a test-and-learn approach, you can use data analytics to both boost and maintain your institution’s enrollment growth.

WRITTEN BY

Aastha Aarya

Sr. Content Writer

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