Enrollement Analalytics

Student enrollment growth on your mind? | Look out for these 10 performance metrics

These 10 data analysis metrics (and the bonus tip at the end) will help you tap into the right resources and give you actionable insights to boost your institution’s student enrollment growth effectively.

With COVID-19 and its effects hitting institutions across the higher education industry, enrollment growth is not a guarantee anymore. Countering this challenge has engendered the need for fast, user-friendly, and easily integrable processes to boost enrollment growth in educational institutions. This is where Data Analytics comes in.

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 data analytics can 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 own 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 around the best times to reach out to prospects, what type of 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.

#1 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.
Student-Enrollment-Journey-Funnel
The deeper a student is in this funnel, the closer they are to enrolling at your institution.

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 speed up the student enrollment process drastically.

#2 Leads Generated vs Expected

Zeroing in on the first stage of the student journey of the funnel 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.’

Lead-Generated-vs-Expected
Use this metric to tap into the right sources for lead generation.

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.

#3 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.

Cost-per-Lead
One technique for reducing your cost per lead is to run a remarketing campaign.

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.

#4 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.

Applications-Received-vs-Expected
It might take some trial and error to figure out exactly which changeable aspects of the application lead to students feeling overwhelmed and dropping off.

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.

#5 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.

Acceptances-vs-Yield-%
A month-on-month view will bring up the best times when you can drop message to check upon and engage applicants.

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.

#6 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.

Student-Demographics-Leads
You can even bifurcate this metric as per each step of the student journey funnel, gaining deeper actionable insights.
Student-Demographics-Applications-Received
You can even bifurcate this metric as per each step of the student journey funnel, gaining deeper actionable insights.

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.

#7 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.

Average-Days-till-Application-Checked
Free up your staff’s time to take up more complex tasks.

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 Essay Analyzer and the Video Interview Analyzer tools developed by iSchoolConnect.

#8 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.

Advisor-Load
The metric can also be used to streamline the load distribution amongst the advisors.

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.

#9 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.

Courses Enrolled
A breakdown of this metric based on course names can also provide details about which of your institution’s courses are attracting more students.

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...

#10 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.

Total-Revenue-vs-Expected-Revenue
Learn which of your representatives can be incentivized to meet realistic and ambitious targets, and how.

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

Lead-Distribution
Use this metric to personalize your institution’s marketing.

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

Application-Dropout-Probability
Reach out to the students likely to drop-off at the right time.

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-look at 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.

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