The Missed Opportunity of Social Media

Data Science

Data Revolution

Change Management

Enrollment Growth

Admissions Strategy

May 23, 2024

minutes read.

*** This post is a follow up to yesterday's webinar with Gil Rogers, "Opportunities We Missed." The recording remains available here. ***

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In the world of college admissions, where every interaction counts, the rise of social media presented an incredible opportunity. Platforms like Cappex, Zinch, and raise.me promised personalized connections with students, offering a glimpse into their aspirations, achievements, and unique stories. Yet, as an industry, we missed the mark. We were so locked into a one-size-fits-all approach, focused on mass communication through emails and brochures, that we overlooked the power of individual outreach and engagement.

At the heart of this missed opportunity lies a fundamental lesson: the importance of embracing data science in our admissions strategies. Imagine if we had leveraged advanced analytics and AI tools, like enroll ml, to dive deep into the wealth of data available through social media platforms. We could have moved beyond generic messaging to tailor our communications based on students' interests, preferences, and needs. Instead of bombarding them with generic emails, we could have crafted personalized messages that resonated with their unique journeys.

The true essence of our profession lies in serving students and institutions well. It's about forging meaningful connections, understanding aspirations, and guiding students toward paths that align with their dreams. However, our reliance on outdated communication methods limited our ability to achieve these greater goals. We were stuck in a cycle of mass communication, where students could easily see through the impersonal nature of our outreach.

In hindsight, it's clear that an embrace of data science could have transformed our admissions landscape. By harnessing the power of data analytics, we could have spent more time getting to know new students, understanding their unique backgrounds and aspirations. This personalized approach not only benefits students by making them feel valued and understood but also allows institutions to build stronger, more meaningful relationships with their prospective students.

Moving forward, it's essential to learn from these missed opportunities and embrace innovative solutions like data science in our admissions processes. Platforms like enroll ml offer the tools and insights needed to personalize communications, improve engagement, and ultimately serve students and institutions in a more impactful way. It's time to shift our mindset, harness the power of data, and unlock new possibilities in college admissions.

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Teege Mettille

Higher education professional with experience in admissions, enrollment, retention, residence life, and teaching. After working on six different college campuses, I'm excited to be consulting with a wide variety of institutions to better meet enrollment targets.I have been fortunate to serve as President of the Wisconsin

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Featured blog posts

Unlock Yield by Addressing Behavior-Action Mismatches in Enrollment

October 30, 2024

minutes read.

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.

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