About the Episode
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About the Episode:
Welcome to AI for Yield Season, a special mini-series of The Application! Each episode is short (less than 10 minutes!) and packed with actionable insights to help enrollment professionals use AI effectively during one of the busiest times of the year.
This episode dives into the key metrics to track in yield marketing, how AI can help analyze success, set up A/B and multivariate tests, and, most importantly, how to adjust strategies based on data-driven insights.
Key “How Tos” You’ll Learn:
✅ Track the right metrics: email engagement, ad performance, deposit trends, event attendance, and chatbot interactions.
✅ Use AI to analyze student sentiment, predict yield likelihood, and identify high-performing messaging strategies.
✅ Set up and run A/B and multivariate tests efficiently with AI-generated content variations.
✅ Adjust outreach strategies based on AI-powered insights for continuous improvement.
If you’ve used AI in an innovative way for enrollment marketing, share your story with Allison! And don’t forget to subscribe to The Application and Allison’s newsletter at allisonturcio.com for more AI-driven strategies in higher ed.
Defining Key Metrics for Enrollment Success
Before diving into AI-powered tracking, it’s essential to set a baseline for success. Depending on your role—whether you’re an enrollment marketer, admissions counselor, or VP—your metrics may differ. However, some key performance indicators (KPIs) remain universal across institutions:
- Email Engagement – Click-through and response rates (rather than open rates) show true student interaction.
- Ad Performance – Tracking which ads drive deposits helps optimize marketing spend.
- Event Attendance – Monitoring admitted student events can reveal engagement trends.
- Deposit Trends – Are students who received AI-personalized messaging more likely to deposit?
- Student Engagement – Chatbot interactions, video views, and social media responses provide insight into student concerns.
For example, if an institution runs two deposit reminder emails—one written manually and one AI-assisted—comparing click-through rates can reveal whether AI-generated messaging is more effective. The goal isn’t for AI to replace human instincts but to use data to back up what’s working and refine what’s not.
Using AI to Analyze Enrollment Marketing Performance
Tracking performance manually can be time-consuming, but AI simplifies the process by identifying trends and making data-driven predictions. Here are three ways AI can help enrollment teams analyze success:
- Sentiment Analysis – AI can analyze email responses and chatbot interactions to gauge student concerns and preferences. If admitted students frequently ask about financial aid or housing, institutions can adjust their outreach to address these concerns proactively.
- Predictive Analytics for Deposits – AI can assess past data to predict which admitted students are most likely to deposit. For instance, if data shows that students who visit campus twice are 70% more likely to enroll, institutions can prioritize follow-up outreach to encourage second visits.
- Optimizing Messaging with AI – AI can evaluate past marketing content to determine which subject lines, CTAs, and formats generate the most engagement. For example, analyzing the last ten email CTAs to identify trends in high-performing click-through rates can provide actionable insights for future campaigns.
Beyond just analyzing data, these insights should be shared across teams—from admissions to social media managers—to ensure a cohesive enrollment strategy that aligns with student needs.
AI-Powered A/B and Multivariate Testing for Enrollment Success
To maximize the effectiveness of AI-driven campaigns, institutions should use A/B testing and multivariate testing to continuously refine their outreach.
- A/B Testing – This method compares two variations of content (emails, subject lines, ad copy, etc.) to determine which performs better. AI can assist by generating multiple versions of a message, such as:
- A subject line with urgency: “Secure Your Spot—Deposit Now!”
- A subject line featuring a success story: “Meet Sarah—How She Chose [Your University]”
- Multivariate Testing – This method takes A/B testing further by testing multiple elements simultaneously (e.g., subject line + CTA + image combinations). AI can assist by suggesting different content variations, helping institutions quickly identify which mix drives the best engagement.
For example, a multivariate test might include:
- Version A: Subject Line A + CTA A + Image A
- Version B: Subject Line B + CTA B + Image B
- Version C: Subject Line A + CTA B + Image C
By analyzing these combinations, institutions can determine which factors most effectively influence student engagement and deposits.
Refining Strategy Based on AI Insights
Tracking and testing are only valuable if institutions act on the insights. AI-generated data should be used to:
- Increase AI usage for content areas that show higher engagement.
- Adjust messaging when an email, ad, or outreach campaign underperforms.
- Personalize outreach further based on engagement trends from specific student segments (e.g., STEM students, first-gen students, out-of-state applicants).
For instance, if an analysis reveals that first-generation students engage most with financial aid-related content, institutions can tailor follow-up messaging and resources specifically for them.
Ultimately, AI should enhance human decision-making, not replace it. Marketers who leverage AI to track success, test new strategies, and refine their approach will build more effective, data-driven yield marketing campaigns.
Connect With Our Host:
Allison Turcio
https://www.linkedin.com/in/allisonturcio/
https://twitter.com/allisonturcio
About The Enrollify Podcast Network: The Application with Allison Turcio is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows, too!
Some of our favorites include Mission Admissions and Visionary Voices: The College President’s Playbook.
Enrollify is made possible by Element451 — the next-generation AI student engagement platform helping institutions create meaningful and personalized interactions with students. Learn more at element451.com.
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