Transforming Prospective Student Engagement through Data-Driven Insights

A Funny Thing About Humans

Information gathering is a universal behavior. Living creatures of all varieties gather information about their environment in order to thrive within it. But we humans take information gathering to a new level. Curiosity. We seek to learn, not just to survive, but to understand. This thirst for knowledge has led to our greatest discoveries and achievements.

But, besides knowing and learning things, we want to be known as individuals. To be understood. From Maslow’s Hierarchy of Needs to a global obsession with social “likes,” we crave recognition and yearn to be seen as the unique beings we are.

This need creates challenges for marketers across all industries, and the importance of leading with personalization seems to grow with each new generation. Fortunately, our ability to “know” our prospects has grown even faster, thanks to the information explosion of the past few decades.

Technology Adoption in Higher Ed

Despite the potential upside of the digital revolution, higher education has a history of approaching new technology with a healthy dose of caution. Concerns over quality, resource management, and compatibility with institutional values require a measured approach. While this mindset has helped the industry avoid many pitfalls, it has left us playing catch-up with the very students we intend to serve.

To be fair, technological advances have helped simplify and streamline many routine administrative processes, such as submitting an application or enrolling in courses, while simultaneously expanding access through virtual learning. But there is a much larger opportunity to transform prospective student engagement through data-driven insights.

Knowing vs. Understanding

Data-driven insights can take us from a position of “knowing about” our prospects to “understanding” them, creating a basis for enhanced student engagement across all touch points. And, while technology cannot, and will not, replace people, it can, when supplied with the right data, enable universities to transform student engagement in a holistic way. The following highlights three ways that institutions can take better advantage of the opportunities presented by technology and an expanded data universe.

Unifying data in fragmented systems to drive deeper insights

Universities have many specialized and legacy systems in place that monitor specific tasks – from marketing analytics that track ad performance to application systems to student information systems to learning management systems. While each provides valuable insight within its defined area of focus, the lack of communication among and between systems creates a fragmented student experience.

Developing a holistic approach to the student journey requires gathering data from disparate sources into one central source of truth. This “data lake” provides guidance to help address real-time needs, but also facilitates a deeper understanding of the learner journey. This allows universities, for example, to not just understand which ads generate click volume, but also which ads generate “quality” clicks and engage students with a higher propensity to graduate.

Expanding the data pool beyond historical benchmarks

The data sources that universities have traditionally leaned on—demographics, psychographics, academic performance/involvement—remain valuable as a framing mechanism, but with so much more information available, institutions must adopt a more wide-ranging and deep-diving approach. For example, while comparing performance measures against previous years can be indicative, the pace of change has made historical data less predictive. Similarly, we must be mindful of external events that impact traditionally reliable comparisons. As you can imagine, almost any data collected in 2020 is not likely to be a good predictor for behavior in 2025.

One simple way to expand your institution’s “student view” is to include peer benchmarks. This allows universities to better understand how they are performing in context and can provide valuable insight into what other learning opportunities are competing for student mindshare. Expanding still further to include benchmarking from alternatives like apprenticeships and skills-based certifications can help universities better understand the true environment and drive better models.

Embracing a student-first approach

Many KPIs for universities typically center around metrics such as CPC, enrollment targets, and deposits. While these data points are important and will remain important measures of success to institutional leadership and donors, today’s students expect, and indeed demand, that marketers of all kinds reach out to them in meaningful, personalized ways across all touch points. The considered analysis and use of an expanded data set enables universities to develop meaningful interactions that ensure students feel “known.”

A valuable tool in managing this growing “data lake” is AI. When combined with a deep data set, the prudent application of AI can allow universities to offer more personalized experiences at scale, without requiring additional staff. At Noodle, we fuel our support bots with all the available, relevant information to create a one-stop experience for students. Doing so eliminates the repetition of tasks and reduces bounce rates. Furthermore, the data gathered at each conversation follows the students, allowing them to feel known in other interactions, with humans or technology.

To AI or not to AI?

While each of these points will be expanded upon in subsequent articles, the 300-lb. gorilla in the room does merit a few observations:

1. Nearly half of online students use an AI tool at least once per week

2. 50% would likely use an AI-driven research assistant in their studies

3. 79% used an AI-driven chatbot during their search for a program

   
   

All of this has taken place largely in the absence of any significant endorsement or strategic utilization of the technology by universities. However, while there have been many companies touting AI products to higher ed, the solutions presented thus far have been underwhelming for a few reasons:

1. They’re too narrow in scope

2. They are often denied access to new and relevant data

3. Developers lack industry expertise

4. They are glorified chatbots or are prime candidates to be sold direct to consumer without customization

   
   

Clearly, AI has a substantial role to play in the evolution of the Learner Journey, but it must be viewed as a part of the solution, not an answer in and of itself.

Conclusion

We will continue to build our Noodling on AI in Higher Ed Series that will explore these ideas in greater detail, but for now, we encourage institutions to recognize that the application of technology and data-driven insights is critical to developing meaningful student engagement strategies and tactics. There has never been a greater opportunity to “know” our prospects and to use that knowledge to have a positive long-term impact on higher education recruitment.

Read original story here.

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