What Students Say vs What Students Do

What They Say vs What They Do: The Financial Aid Disconnect

Every spring, institutions invest enormous energy in perfecting their financial aid strategy. And understandably so—survey data consistently ranks “financial aid” and “scholarship amount” as top factors in student decision-making.

But here’s the paradox: when we look at the actual enrollment outcomes, financial aid amounts don’t rise to the top in predictive power.

At enroll ml, our machine learning models analyze real-time behavioral signals across the funnel. After three years of deployment and tens of millions of student records processed, we’ve found that financial aid amount is rarely a top predictor of enrollment.

Why the disconnect?

Because what students say—and what they do—often diverge. Behavioral science calls this the gap between stated preference and revealed preference. In enrollment, it plays out like this:

• Students say aid was the reason they didn’t enroll.
• But the data shows their engagement dropped long before the award.
• Or that they received a generous award—but never responded at all.

Financial aid is a stimulus, not a decision driver. The key isn’t the size of the award—it’s what the student does after receiving it. Did they log in? Schedule a meeting? Submit documents? Go dark?

That’s where the real insight lives. enroll ml decodes not just whether a student received aid, but how they responded. And those reactions—fast engagement, lingering silence, last-minute activity—are far more predictive than the dollar amount.

As you guide your team through yield season, don’t rely solely on what students say. Pay attention to what they do. That’s where the enrollment decision actually happens.
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If you're interested in further conversation on this topic, I invite you to watch a recording of an enroll ml webinar from August, 2024, How Predictive Is Financial Aid, with Matt Osborne from Ardeo Education. https://www.crowdcast.io/c/aid

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Admissions teams are drowning in data. From FAFSA submissions and campus visits to email opens and application statuses, there’s no shortage of signals to track. But here’s the problem—not all signals mean what we think they do. And when teams rely too heavily on traditional indicators, they end up making decisions based on assumptions rather than facts.

It’s time to move from guesswork to precision—and that starts with understanding the difference between surface-level signals and deeper behavioral patterns.

The Problem with Over-Indexed Signals:
Many admissions processes are built around major milestones: FAFSA submissions, campus visits, and application completions. These are easy to track and feel like strong indicators of student interest. But are they?

Take FAFSA submission for example. For those of us who’ve been in admissions for a decade or more, we know that where a student lists your institution on the FAFSA matters. If you were listed first, that likely meant high interest. If you were listed fifth, your chances of yielding that student dropped significantly. But now that we can’t see FAFSA rankings, many teams treat all submissions the same—ignoring the nuances behind the data.

The Role of Gut Instinct (and Its Pitfalls):
Without clear, nuanced data, many counselors fall back on gut instinct. And while intuition plays a role, it’s inherently biased. A counselor might assume that a student who hasn’t applied for financial aid isn’t serious about enrolling—because they wouldn’t have enrolled without aid. But that assumption doesn’t hold true for every student. Relying on personal bias leads to missed opportunities and inconsistent outcomes.

The Hidden Signals We’re Missing:
What admissions teams often overlook are the subtle, behavioral signals that truly indicate student intent. It’s not just whether a student opened an email—it’s how quickly they opened it after receiving it, how many links they clicked, and whether they engaged again after a follow-up. The time windows between student actions matter far more than a simple yes/no.

For example:

• A student who visits your website multiple times within a week but hasn’t yet applied might be more interested than a student who submitted an application months ago but hasn’t engaged since.
• A student who opens your emails consistently but doesn’t respond may still be deeply engaged—they just need the right kind of outreach.

These patterns aren’t easy to spot manually. Machine learning tools like enroll ml analyze these time windows and engagement rates, surfacing students who are truly ready for proactive outreach.

From Data-Aware to Data-Driven:
Most admissions teams believe they’re data-driven. In reality, they’re data-aware. They track numbers, run reports, and create lists—but the depth of analysis needed to uncover true enrollment signals isn’t something you can get from pivot tables in Excel.

To make the leap from guesswork to precision, admissions teams need to pull the highest level of data analysis possible. This isn’t about working harder—it’s about working smarter, using tools that can decode complex behavioral patterns and guide counselors to the right students at the right time.

The Bottom Line:
Moving from guesswork to precision isn’t just about improving enrollment outcomes—it’s about freeing counselors from the endless cycle of assumptions and giving them the tools to engage meaningfully with the students who need it most. It’s time to stop guessing and start understanding.

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Admissions teams are busy—really busy. But being busy doesn’t always mean being effective. What many admissions counselors call “proactive” outreach is actually what I call pre-active outreach. It looks like proactive work on the surface, but it’s fundamentally reactive at its core.

If your outreach strategy involves sending batch emails to dozens or even hundreds of students and waiting for responses—or following up only after students submit their FAFSA or attend an event—you’re not being proactive. You’re preparing to react.

What Is Pre-Active Outreach?
Pre-active outreach is when counselors send messages or make calls with the expectation that the student will take the next step before any real relationship is built. It’s mass communication disguised as engagement. For example:

• Sending an email to 300 students asking for their FAFSA.
• Following up with students after they visit campus, but not engaging beforehand.
• Waiting for students to respond to a call-to-action before personalizing outreach.

This isn’t proactive—it’s a sophisticated form of waiting.

How Did We Get Here?
Admissions has evolved into a numbers game. With increased application volumes and fewer resources, counselors are pressured to manage large funnels and meet outreach quotas. To cope, they’ve borrowed tactics from marketing: mass emails, segmented lists, and simple calls to action.

But here’s the problem—counselors aren’t marketers. Their role is to build relationships, not run miniature search campaigns. This shift from personalized counseling to high-volume communication has blurred the lines between marketing and meaningful engagement.

The Problem with Pre-Active Outreach:

1. It’s Not Personal: Mass emails and generic follow-ups don’t foster real connections. Students can tell when they’re just another name in the CRM.
2. It’s Inefficient: Counselors spend countless hours sending broad messages, hoping students will engage. This leads to burnout and missed opportunities.
3. It’s Reactive by Nature: Pre-active outreach waits for students to make the first move. By the time counselors engage meaningfully, it may be too late—the student has disengaged or chosen another institution.

What True Proactive Outreach Looks Like:
Proactive outreach flips this model on its head. Instead of waiting for students to respond, counselors anticipate needs based on behavioral signals and engage before the student even realizes they need support.

• Proactive Outreach Example:
  A student consistently opens your emails, clicks links, but hasn’t visited campus or submitted a FAFSA. Instead of waiting, you reach out personally to understand their hesitations and guide them through the next steps.

This kind of outreach leads to deeper connections, better support for students, and, ultimately, higher enrollment results.

The Bottom Line:
Admissions teams need to stop confusing pre-active outreach with proactive engagement. Mass communication has its place in marketing, but counseling is about relationships. By shifting from pre-active tactics to truly proactive outreach, counselors can better support students—and feel more fulfilled in their work.

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