Finding Purpose In A Tough Admissions Cycle

The Transformative Power of Machine Learning in Enrollment Management

In the recently released whitepaper, “Harnessing the Power of Machine Learning in Enrollment Management,” we identified high-level data insights from watching thousands of behavioral data elements among nearly a million students.  While the full paper is available here, you can get a teaser on this page.

In the competitive landscape of higher education, enrollment management teams face increasing pressure to attract and retain high-fit students with limited resources. Traditional methods, such as top-of-the-funnel marketing and profile-based probability models, often fall short, leading to data overload and missed opportunities for meaningful student engagement.

At enroll ml, we know that artificial intelligence (AI), particularly machine learning (ML), offers a transformative potential to address these challenges. Our 2023 work-time study revealed that admissions teams spend over 30% of their time on data management, even with sophisticated CRM and predictive analytics systems in place. By automating data analysis, identifying high-potential students in real-time, and enabling more effective and efficient enrollment strategies, machine learning can significantly improve enrollment team efficiency, performance, and results.

Insights from Machine Learning

While the full whitepaper offers deeper context, there are three key breakthroughs that our machine learning engines have made available for enrollment leaders in 2024.

- Behavioral Tracking: The shift from simple if-then behavior tracking to complex pattern recognition captures nuanced and dynamic student behaviors, providing deeper insights into student engagement.

- Increased Precision: Quick identification and understanding of high-potential students through real-time behavioral pattern recognition enhance the accuracy of predictions.

- Enhanced Efficiency: Automating data tasks increases counselor capacity by up to 30%, allowing for more strategic use of time and resources.

These advancements demonstrate the critical role of behavioral-driven ML in modern enrollment management, offering early adopters a competitive edge. The insights and strategic recommendations outlined in our whitepaper can help higher education institutions enhance enrollment processes, optimize resources, and improve student engagement.

Conclusion

Machine learning has already demonstrated the power to transform enrollment management by providing real-time insights into student behaviors, increasing precision, and enhancing efficiency. Institutions that embrace these technologies early will be better positioned to meet future challenges and capitalize on emerging opportunities.For a deeper dive into how machine learning can revolutionize your enrollment management processes, download our full whitepaper, "Harnessing the Power of Machine Learning in Enrollment Management."

The onset of the modern CRM has drastically changed the work we do in college admissions. While some of these changes are self-evident, such as our increasing comfort with sending millions of emails to a graduating class of students or embracing text message blasts, there's something many of us our missing.

The technology behind CRMs has produced an immense data warehouse for each institution - and you're probably only using a fraction of it.

Today, the ability to manage data to drive enrollment strategy is what will separate institutions that meet their potential and institutions that miss.

If you're wondering why we continue to struggle with counselor morale, this is as good a place as any to start.  Over the course of a generation, we slowly changed the job of an admissions counselor - reducing the work they find rewarding and increasing the work they find draining.