Welcome to enroll ml's AI reasoning & guidance

The Enrollment Personalization Problem: When Enrollment Data, Experience, Intuition and Time Hit Their Limits - and How AI Gets Us Over the Hurdle

For nearly a decade, I've been working to improve how enrollment teams operate. The goal isn't just better tools but better thinking. Better strategic returns on our investments in marketing, platforms, analytics, predictive scores, and people. Today, the need for this transformation has never been greater. Enrollment management is facing a Category 5 storm. Five converging forces are overwhelming traditional strategies and forcing a total reset:

The Personalization Mandate Students expect hyper-relevant, behavior-responsive communication. CRM mail merges won't cut it. Students are now comparing your outreach not to other colleges but to Netflix, Spotify, and TikTok. If you're not adapting to real-time student behavior, you're already falling behind. The new enrollment objective is deeper connection.

The Shrinking Demographic Base There are fewer students, but more applications per student. That means the funnel looks busy, but is more diluted than ever. The signal-to-noise ratio continues to worsen. With scarce enrollment resources playing a zero-sum game, we can't afford to have attention drift from students we can compete for to students where we are too far down their list.

The ROI Crisis Students and families are asking CFO-level questions: Will this pay off? They're analytical, not just emotional. And if you can't answer clearly (with trusted data and real relevance), they'll move on.

Signal Distortion from Application Inflation Applications are up. Yield is down. Traditional signals of interest are broken. The Common App and Direct Admit tools have opened access, but they've also shattered the data continuity admissions teams relied on.

The Rise of Alternate Paths College no longer holds a monopoly. Certificates, bootcamps, employer pathways - they're credible, affordable, and often clearer in their ROI. Higher ed must now compete and connect on a whole new level.

These forces have made one thing clear: we must get more personal, more aligned, and more deeply connected to the students who are most strategic to our enrollment objectives. That means listening harder, seeing more clearly, and responding more precisely to every signal.

The problem? Even our best people can't do this at scale.

That's why we built the enroll ml Reasoning & Guidance Engine. An AI system that actually thinks like your best admissions leaders. It doesn't just automate tasks. It synthesizes all the fragmented, noisy data across your CRM - signals, communications, vendor activity, checklists, timing patterns - and creates a complete, real-time understanding of each student and personalized, context-aware outreach content. Well beyond changing content based on <<interest>>, enroll ml creates a behavioral view of the applicant to help your institution connect more deeply with them, wherever they are on their individual decision journey.

To test it, we worked with four former VPs and Directors of Admissions. We challenged them to write personalized, behavior-aware outreach to real students. Not based on profile, but on the full picture: all signals, communications, hesitations, timing. They dove in, reviewing hundreds of data points on each student's record, relying on every ounce of experience, intuition, and pattern recognition they'd built over decades.

The conclusion: at best, we could craft 3-4 thoughtful, strategic messages per hour. But there was a deeper realization that much of what we call experience and intuition is really guessing, built on past pattern recognition that may or may not apply to the individual student in front of us. What this opened our eyes to was that what we have passed as "personalization" was in reality only a couple of steps beyond data merges. As we looked at more and more students it became clear: AI was doing this better, faster and at a scale that is impossible with our current tools and teams.

This is the gap we built enroll ml to close.

What many people don't know about enroll ml, and something that makes us fairly unique, is that we didn't create enroll ml to take out and sell to admissions teams. Enroll ml was built for my own personal use, and I used it across 2 institutions with 19 admissions counselors for two years. Of course it wasn't called enroll ml at the time; it was just our data system that was leveraging early AI to better understand, react to and connect with the individual student based on their individual signals, not because they were grouped into a profile. It was only after 2 years of daily use - and results that we had not been able to capture with any other combination of tools, lists or campaigns - that we decided to turn enroll ml into a product that anyone could use. It was just too impactful in pushing enrollment management forward as a profession to not do it.

Inside of enroll ml we have over 60 years of combined enrollment leadership experience. We know how the processes work. We've been in the high schools and led the tours. We've optimized our aid awards and battled with admissions committees on behalf of our applicants.

And when we saw what our enrollment funnel AI reasoning and guidance engine was able to produce, and the impact it would have had on our own admissions teams, we were absolutely blown away.

Our engine thinks like an admissions leader, creates individualized student strategies, and generates messaging that connects. Not based on where a student shows up on a spreadsheet, but on what they've shown us through their actions, hesitations, behaviors, and communication. We know every signal doesn't mean the same thing for every student. A campus visit from a first-generation student means something different than one from someone whose parents are both alumni. Until now, we didn't have a way to turn signals into context, and context into guidance at scale. Now we do.

With enroll ml's Reasoning and Guidance Engine, we've moved closer to true personalization at scale. We've built a core intelligence layer that makes the very best of your team (and your tools) better while raising the efficiency, effectiveness, and consistency bar for everyone involved in strategic enrollment.

AI is about to flood enrollment management. Some tools will orchestrate. Some will automate. Some will predict. But very few will watch them all to help reason with precision, personalization, and strategic clarity.

That's what we've built. And it's available now.