From Profiles to Behaviors: Transforming Data Analysis in Enrollment Management

Introduction
In today’s competitive enrollment landscape, yield and retention hinge on data-driven precision. Traditional methods often fall short, relying on subjective judgment and missing critical engagement signals. enroll ml changes this by identifying behavior-action mismatches, helping admissions leaders spot opportunities and risks in real time for measurable impact.

Understanding Behavior-Action Mismatches
Behavior-action mismatches occur when engagement doesn’t align with commitment indicators, such as:

• High Engagement, No Commitment: High-potential students show interest but haven’t reached a commitment milestone, signaling a prime yield opportunity.
• Low Engagement, Commitment Met: Students with commitment indicators but low engagement, often an early indicator of melt risk.

Challenges with Traditional Methods
For many admissions teams, sifting through high application volumes and disconnected engagement data can feel overwhelming. Traditional models track disconnected behaviors that may correlate with enrollment but don’t provide enough depth to detect patterns. This often leads to delays or missed opportunities for timely intervention.

How enroll ml Closes the Gaps
enroll ml’s machine learning and Outcome Optimization Theory detect behavior-action mismatches in real time, transforming how admissions teams prioritize engagement:

• Multi-Marker Modeling: By analyzing an interconnected range of behaviors—engagement depth, timing, communication patterns—enroll ml precisely identifies high-potential, high-impact students.
• Automated Flagging and Prioritization: enroll ml flags behavior-action mismatches daily, eliminating time spent on manual record review. This prioritization empowers teams to re-engage at-risk students before melt occurs, turning data analysis into focused, real-time action.

Strategic Impact of Addressing Behavior-Action Mismatches
By automating prioritization, enroll ml can reduce counselor time spent on administrative tasks by up to 30%, freeing them to focus on high-impact engagement with top-yield prospects.

• Enhanced Yield: With immediate engagement, admissions teams lift yield by focusing on high-engagement students nearing commitment.
  • Case in Point: Within days of launch, Columbia College Missouri identified and converted high-potential students previously overlooked, directly boosting yield by X%.
• Reduced Melt: Proactive outreach to at-risk students with commitment indicators minimizes last-minute withdrawals.
  • Case in Point: Roosevelt University significantly reduced melt by re-engaging low-engagement depositors flagged by enroll ml, leading to X% decrease in summer melt.

Takeaway for Enrollment Leaders
Monitoring and responding to behavior-action mismatches directly impacts final yield outcomes. With enroll ml, admissions teams continuously identify actionable signals, strategically unlocking yield and reducing melt. Ready to turn data into yield? With enroll ml’s behavior-action insights, admissions leaders can unlock hidden yield potential and reduce melt, leading to X% gains in yield and X% reductions in time spent on administrative tasks.

‍

Just over a year ago, our own Madison Snyder hosted a conversation with four cutting-edge leaders in enrollment management about how they leveraged data to achieve success in enrollment management.

The full conversation is available on demand here: https://www.crowdcast.io/c/womeninenrollment

For many admissions teams, FAFSA submissions have traditionally been viewed as a strong signal of student interest. However, in reality, not all FAFSA submissions indicate serious intent to enroll. As competition for students increases, it's critical to re-evaluate how FAFSA data is interpreted, especially in light of the information colleges can't access.

One important data element that has been affected is FAFSA Position, eliminated about a decade ago, which provided insights into where a student listed a particular college relative to others on their application. For years, many institutions used FAFSA Position to infer a student’s level of interest—assuming that being listed first or second meant the student was highly likely to enroll. While this wasn't a formal tool, the position was often treated as an important clue in the enrollment puzzle. However, due to concerns from the Department of Education about how colleges were using this information, FAFSA Position is no longer available. This change forces institutions to rely on other indicators of interest, and it underscores the need to diversify strategies for assessing commitment.

Why FAFSA Submissions Alone Don't Reflect Engagement

While none of us have assumed that every FAFSA submission equals similar levels of intent - this data blindspot has left us no alternative way of measuring this signal by student. Students now apply to more schools than ever before, and many submit FAFSAs to schools they’re considering only as “backup” options. Completing the FAFSA is simply a procedural step for many students, not a declaration of their commitment to attend a particular institution.

As a result, colleges that heavily weigh FAFSA submissions may end up focusing resources on students who have no serious intention of enrolling. Without the added layer of insight from FAFSA Position, schools are left with less context, making it more difficult to gauge genuine interest based on FAFSA data alone.

The Changing Landscape of College Decision-Making

The dynamics of student decision-making have evolved over the years, but FAFSA submissions are no longer a reliable indicator of where a student will eventually commit. In today’s environment, students submit multiple applications and FAFSA forms, often as a matter of precaution rather than as an expression of intent. In this climate, admissions teams need to be more cautious about assuming that FAFSA submissions equate to real interest.

Additionally, the inability to access FAFSA Position means schools can no longer know where they stand relative to other institutions. This lack of visibility into a student’s preferences highlights the growing importance of using additional methods—such as behavioral data, engagement metrics, and predictive modeling—to better understand and prioritize students who are truly interested in enrolling.

Prioritizing Engagement Over FAFSA Data

The shift away from relying on FAFSA Position presents an opportunity for admissions teams to reframe how they assess student intent. Rather than focusing on FAFSA submissions as a primary indicator, schools should shift their attention to other forms of student engagement. Metrics such as website visits, participation in virtual tours, attendance at campus events, and interactions with admissions officers can provide far more reliable insights into a student’s commitment to your institution.

In addition, colleges can leverage machine learning and predictive analytics to better understand how engagement behaviors correlate with enrollment decisions. By analyzing patterns in student interactions—such as the frequency of communication, the types of inquiries made, or the timing of their engagement—admissions teams can develop a more nuanced understanding of student intent. These insights help schools prioritize their outreach efforts toward students who are most likely to matriculate, rather than relying solely on the submission of financial aid forms.

Diversifying Your Approach to Student Commitment

The end of FAFSA Position data had forced an abandonment of nuance in interpreting the signal of FAFSA submissions. The rise of high-level data science now allows for a reassessment of how colleges interpret FAFSA submissions, making it clear that this form alone should not be the main driver of admissions decisions. While FAFSA remains an important part of the financial aid process, it is no longer a reliable indicator of student commitment. By focusing more on engagement behaviors and leveraging data-driven insights, admissions teams can make smarter, more informed decisions about how to allocate their resources and shape their admit pool.

In today’s competitive landscape, relying on a single metric—like FAFSA—can result in missed opportunities and misallocated efforts. Schools that embrace a broader, more holistic approach to understanding student commitment will be better equipped to build strong, resilient incoming classes.

‍