Student Enrollment

Strategic initiatives to use Data Analytics in education for enrollment growth

Many college and university leaders are unaware of the potent ways in which data analytics can help boost their enrollment rates and lack expertise in incorporating these methods into their operations effectively.

Following a decade of consistent growth in international student enrollment up until 2019-2020, US institutions alone saw a decrease of almost 20,000 international enrollees the next year. Then came COVID-19 and its side effects, dropping international enrollment in the U.S. by 16%! Now, more than ever, universities and colleges are looking for cost-effective and smart ways to improve student experience across the entire admissions cycle. But how can data analytics help you drive enrollment growth? Which strategies will actually work when it comes to utilizing Data Analytics in education? And which solutions will work for your institution? Let’s find out.

The problems we’re facing

In September 2019, The Chronicle of Higher Education published an article [1] stating that students have begun to wonder if post-secondary education is worth investing in.

As a consequence, US Institutions have been facing a decline in enrollment even before COVID-19 struck with its side effects, including limited access to US embassies and consulates, travel restrictions, and general health concerns arising from the pandemic.

The bottom line is this - Enrollment is not guaranteed anymore.

Budget cuts
University leader troubled by budget cuts
Budget cuts only cause more pressure on private institutions to target and convert a larger pool of students.

The decline in the economy has led to pressing budget cuts by institutions.

Knowing that global aid to education has remained roughly the same since 2009, it is very less likely that it will be prioritized anytime soon. This would disrupt the equilibrium within the education market, increasing the level of inequality in terms of where students are allocated - public schools or private institutions.

Inefficient management

Without an easy-to-use centralized and automated system, it becomes impossible to manage student data effectively.

The current policies and processes can only drive enrollment growth so far, creating an excessive need to move out of cost-ineffective and unscalable systems into more streamlined, cost-efficient, and automated processes.

Disparate sources and systems

Several institutions are still practicing data sharing only within departments using disparate sources such as Excel spreadsheets, CRM, and PDFs. Inter-department communication continues to remain inexistent.

Moreover, the data collected comes from simple resources, like surveys conducted at a single instance of time, which is not good enough to keep up with the rapidly changing student mindset these days. Admissions and IT need to communicate regularly. Similarly, Admissions need to regularly touch base with Marketing.

Lack of technical knowledge
Staff confused about Data Analytics
Training your staff to keep up with the latest technological developments can be time consuming and requires constant effort.

Even when an institution does have the ability to collate information on prospective students, there is a need for expertise in deriving actionable insights by looking at data. This requires extensive knowledge of the multitude of difficult-to-use data sources currently being used by institutions, along with the ability to understand it acutely when combined altogether.

Slow turn-around-time

A study by Marketing Dive[2] states that “40% of millennials claim to engage with chatbots on a daily basis,” showcasing that students today are looking for faster responses from their prospective institutions. A slow-turn-around time not only means losing a student’s interest but also a lower conversion rate.

It is undeniably clear that there’s a need for fast, user-friendly, and easily integrable processes to boost enrollment and engagement growth in educational institutions. This is where Data Analytics comes in.

The use of data analytics in education

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.

Targeted marketing
University staff doing targeted marketing
Use the channels and spots your prospective students are browning to invite them to your institution.

Data Analytics can provide you 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.

This careful, informed nudging ensures that you intervene with your message at a convenient time, helping you increase your enrollment rate.

Note: The same concept also helps with student engagement and retention

Better conversion rates

Studying a few key data points about a student, such as their previous/current school, GPA, standardized test scores, academic interests, location, financial metrics, and engagement rates can tell if he is more likely to enroll and succeed at your institution. This would help you set an optimal number for how many students you should admit, allowing you to maintain or even bump your tuition revenue while also not stretching your resources thin.

Better identification of drop-off points

From the time a prospective recruit learns about you, up until he gets admitted to your institution, data analytics scrutinizes each and every point in his journey. This can help you predict exactly at what point a student might drop off from the funnel and install automation to avoid it.

Personalized interaction with prospects
Student interacting with a university chatbot
40% of millennials claim to engage with chatbots on a daily basis.

With insights on what a student is more likely to do next, data analytics can create customized and personalized admission experiences. It can speed up administrative processes, fasten admissions decisions, and help international students with automated visa processing, housing selection, and course registration.

Reduced expenses and operational costs

According to McKinsey[3], who interviewed over a dozen senior leaders at universities known for their transformation through analytics, there is a need to establish a central analytics team that oversees how data is shared and used across departments.

There would be no need for staff across departments to be aware of how this centralized system works, while its managers can repurpose their performance models with ease, reducing the overall operational expenses.

Strategic initiatives that use Data Analytics to boost enrollment

Having seconded that data management policies and practices do need to be changed, the new direction being taken also needs to be right.

Here are a few best practices to follow when using data analytics in education-

  1. Establish a central analytics team that oversees all data-related operations
  2. Create a culture that promotes healthy data sharing to overcome the problem of data silos being restricted within schools & colleges
  3. Bridge the gap between raw data and actionable information by analyzing the risks and benefits associated with your decisions
  4. Grow the analytics team’s technical expertise so they can push the extent to which data is used for predictive analytics
  5. Stick to the best ethical practices as you improve your admissions modeling capabilities and boost enrollment
The future of Data Analytics in education

Transforming the end-to-end enrollment process requires institution and college leaders to change their approach and adopt a data-driven mindset. It takes time to bring about this change. 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 drive and maintain your enrollment growth.

Citations

[1] The Great Enrollment Crash, The Chronicle of Higher Education

[2] Study: Chatbots gain popularity with consumers, especially millennials, Marketing Dive

[3] How higher-education institutions can transform themselves using advanced analytics, Mckinsey

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