Mapping The Student Journey With AI

At NACAC, there was plenty of discussion around using AI to automate tasks, but few touched on AI's ability to track and predict where students are in their decision-making process. This is one of AI’s most powerful, yet underutilized, capabilities in admissions. Understanding what stage a student is at—whether they’re still exploring options, actively researching, or ready to apply—enables admissions teams to tailor their communications, making every interaction more meaningful.

The Challenge: Understanding Student Decision-Making

Admissions teams often rely on broad, linear models to track where students are in the funnel—prospect, inquiry, applicant, admit, and enrolled. While these categories are helpful, they don’t account for the complexity of individual student behavior. Some students may linger in the exploration phase for months, while others fast-track to applying after a single campus tour.

Knowing exactly where a student stands isn’t always clear with traditional methods. You might rely on surface-level cues—did they submit an inquiry form? Have they opened emails?—but these only provide part of the story. This is where AI can step in to give a clearer, more nuanced picture.

AI's Ability to Predict the Student Journey

AI excels at processing large amounts of data quickly and spotting patterns humans might miss. By analyzing behavior like how often a student visits your website, what pages they view, and when they open emails, AI can track subtle signals that indicate their progress through the decision-making process. AI models can even predict future behaviors, offering insights into where a student is headed and what kind of interaction they’ll need next.

Here are some ways AI can help map the student journey:

• Behavioral Analysis: AI looks at the frequency and nature of student interactions—such as visiting specific academic program pages or registering for events—to estimate how far along a student is in their journey.
• Predictive Staging: Based on past behaviors, AI can predict a student’s next steps. For example, if a student starts spending more time on financial aid or housing pages, AI might suggest they’re getting ready to make a decision, prompting your admissions team to send a personalized outreach.
• Engagement Milestones: AI helps track when students hit certain engagement milestones, like signing up for an info session or downloading an admissions brochure. These milestones help admissions teams know when it’s time to switch from general engagement to more specific, personalized communication.

Why Predicting Decision Stages Matters

Understanding where a student is in their journey allows admissions teams to deliver the right message at the right time. A student still exploring their options might need a broad overview of campus life, while a student deep into the decision phase might appreciate personalized insights into scholarships or financial aid opportunities.

Instead of bombarding every student with the same set of emails or phone calls, AI enables admissions teams to focus their efforts more strategically. This targeted approach can make the student experience feel more personal and relevant, which in turn increases the chances of them moving forward in the process.

A More Tailored Approach to Engagement

AI doesn't just help predict where students are—it also helps you communicate with them more effectively. A student in the early stages of exploration likely won’t respond well to an email asking them to apply now, but they might engage with content highlighting the academic programs or campus life they’re interested in. Conversely, a student nearing the end of their decision-making process will likely appreciate direct guidance on deadlines, financial aid, or next steps for enrollment.

By meeting students where they are, you’re not just improving your chances of conversion—you’re improving their experience with your institution. A more tailored, relevant approach to engagement shows students that you understand their needs and are there to support them throughout their journey.

AI and the Power of Predicting Student Behavior

AI’s ability to map and predict the student decision journey is a game-changer for admissions teams. By analyzing behavior patterns and engagement milestones, AI provides invaluable insights into how students are progressing through the funnel. This allows for more personalized and strategic communication, ultimately improving the chances of turning prospects into enrolled students.

Next week, I’ll explore how AI can help admissions teams craft the perfect approach for each individual student, providing guidance on the best way to engage based on their unique profile and preferences.

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After attending the NACAC conference, it’s clear that AI is a hot topic in admissions. Session after session showcased AI’s potential to automate tasks like reading transcripts and sending mass emails. But that conversation misses a critical point: AI’s real power is in guiding human decisions, not just replacing human tasks.

While automation has its place, the true value of AI in admissions lies in its ability to help us understand which students need attention, where they are in their decision-making journey, and how best to approach them. AI can analyze patterns in behavior and engagement, providing admissions teams with a data-driven way to make smarter decisions.

Rather than scripting emails or processing applications, AI can empower counselors with insights on when and how to engage with individual students. It gives humans the tools to personalize their outreach, make timely decisions, and enhance relationships—all with greater confidence.

The future of AI in admissions isn’t about turning the work over to machines. It’s about using machine learning to make better, more informed human decisions. By expanding the AI conversation beyond automation, admissions leaders can unlock new opportunities to connect with the right students at the right time, ultimately improving enrollment outcomes.

Next week, I’ll give examples of how AI can help you pinpoint which students to focus on for more impactful engagement.

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At the NACAC conference, AI was all the rage, but most of the conversation focused on automating tasks like processing applications or sending emails. While automation is helpful, there’s a bigger opportunity being overlooked: AI’s ability to help admissions teams figure out which students to engage with and when. That’s where its real value lies.

The Challenge: Prioritizing the Right Students

In any admissions cycle, you’re often inundated with student inquiries, applications, and expressions of interest. From the student who’s just starting to explore your school to the one on the verge of applying, how do you know who deserves your attention? Traditional methods, such as prioritizing based on GPA or test scores, don’t always give you the complete picture of a student's potential to enroll. Moreover, these methods often miss the nuance of where students are in their decision-making process.

That’s where AI steps in—not to replace your expertise, but to help you focus your efforts. By analyzing student behavior—like how often a student visits your website, what they click on, and how they interact with your communications—AI can predict who’s ready to engage and who might need more nurturing. This saves your admissions team time and allows for more personalized outreach.

How AI Identifies Key Prospects

AI does more than crunch numbers. It spots patterns in student behavior and engagement that humans might miss. For example, AI can track not just whether a student opens an email but how often they return to your website afterward, how much time they spend on specific program pages, and whether they sign up for a virtual tour or webinar. All these actions are indicators of interest, but they also provide a deeper sense of where the student is in their decision journey.

Here are some specific ways AI can help you identify key prospects:

• Engagement Scoring: AI assigns scores to students based on how engaged they are with your institution. A student who clicks on multiple emails, revisits the website, and signs up for events will score higher, indicating they may be ready for more focused outreach.
• Behavior Tracking: AI can look beyond simple interactions and assess deeper behavior patterns. For example, a student who consistently asks about specific programs or scholarships is likely more serious about enrolling than one who’s only browsing general information.
• Predictive Timing: AI can help admissions teams understand when students are most likely to respond to communication. Maybe a student opens every email in the early morning—AI will track that and suggest sending future emails during that window.

Smart Outreach: Prioritizing for Impact

One of AI’s biggest advantages is helping admissions teams focus on the right students at the right time. Instead of casting a wide net with mass communications, AI allows for targeted engagement. For instance, students who show high levels of engagement can be flagged for immediate follow-up, while those showing lower engagement can be put into nurturing campaigns to keep them warm without wasting time on direct outreach.

Some practical benefits of AI in outreach include:

• Optimizing Time and Resources: AI helps admissions counselors prioritize high-value students, freeing up time to focus on those most likely to apply and enroll.
• Personalized Communication: By tracking the specific needs and interests of students, AI helps you craft messages that speak directly to their unique situations, leading to more meaningful interactions.
• Intervention Before Drop-Off: AI doesn’t just highlight students who are ready to engage; it can also flag those who are disengaging, allowing for proactive outreach to keep them in the funnel.

Rethinking Your Engagement Strategy

With AI’s insights, admissions leaders can uncover students who might not have been flagged based on traditional criteria. Maybe they don’t have the highest GPA, but their behavior shows a deep interest in your programs. By digging into these hidden signals, you’re not only broadening your pool of high-potential students but also making your engagement strategy more inclusive.

This kind of data-driven, personalized approach helps ensure that you’re not missing out on great prospects simply because they didn’t meet the standard academic criteria.

AI’s Role in Identifying Key Prospects

AI is transforming the way admissions teams engage with prospective students by helping to identify who to focus on and when to reach out. With a data-driven understanding of student behavior, you can personalize your outreach and maximize the impact of your efforts.

Next week, I'll explore how AI can help map the entire student journey, allowing admissions teams to tailor their communications even more effectively.

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