Data-driven relationships: The secret to recruiting and retaining students

According to the National Center for Education Statistics, nearly half of students who begin college do not continue to complete their degree. In the United States:

  • the average institution loses $9.9 million annually in revenue due to student attrition (Educational Policy Institute)
  • 34 million people over the age of 25 have some college credit but no degree to show for it (US Dept of Labor)

This is a devastating reality in higher education today—one that comes at an extremely high cost to students, institutions, and society at large. Many institutions spend a lot of effort and money getting students into their programs only to shift the onus largely onto the student to persist through to graduation. To ensure students both enroll and graduate, institutions must employ strategies that address retention from the very first inquiry, and through the entire student lifecycle. By basing student interactions on both data and coaching during both the enrollment and retention stages of the student lifecycle, institutions can ultimately improve outcomes and grow enrollment.

The secret to recruiting to retain, and retaining to recruit is the creation of a data-driven relationship with each individual student. This data-driven relationship comes when an institution implements a high-touch coaching model early in the inquiry process and then uses those interactions to execute a personalized, proactive, and informed outreach strategy. If every interaction with a potential student is viewed as an opportunity to capture data relating to her life experiences, her academic experiences, and her career aspirations, data can ultimately be leveraged to find shared themes among the entire student body and ultimately automate individualized communications at scale. By using data to identify when a student might need a little extra help in a particular area or some moral support while going through a life transition, institutions are better equipped to support students through shared barriers to success.

There are a number of things to keep in mind when developing strategies to create a data-driven relationship with students.  At Helix, we feel very passionate about how we approach students, and our approach is based on a coaching philosophy grounded in relationship building. When even one person from an institution can build a relationship with a student, that single relationship can be a saving grace for that student. It is important to help your prospects and students feel supported from the very beginning. Establishing baseline knowledge of a student’s goals, life circumstances, and communication preferences will help inform further outreach and communication efforts. Additionally, establishing expectations and discussing the resources with each student will build a solid relational foundation between your institution and each individual. Use this preliminary relationship-building time to help them understand the institution is working in their service.

One of the biggest tools of coaching is the ability to ask great questions. It’s easy to make assumptions and ask closed-ended questions. Asking open-ended questions and letting students do the talking is an important way to enhance and empower students to feel supported and taken care of. Embrace coaching, build great relationships, and ask great questions. The insights obtained in coaching interactions will then ultimately inform a data strategy that will empower an institution to improve outcomes on a larger scale while also growing future enrollment by recruiting more and better-fit students for the institution.

To inform personalized communication strategies with students at scale, colleges and universities must arm themselves with the necessary data. Starting with the very first inquiry conversation, institutions should begin capturing data and looking for early indicators that could potentially factor into a student’s success. Quantitative data—highest level of education completed, employment status, years since last enrolled, etc.—and qualitative data—goals, motivations, obstacles—can begin to paint a preliminary picture (or predictive model) of the student’s initial chances of success. This data can allow you to have a cohesive and proactive recruitment and retention strategy that will give you more and better data over time.

Leverage technology to streamline the process
Before an institution can build out a data strategy, however, they must ensure their data collection and analytic components are in place. Capturing data using something like spreadsheets or Google docs—while certainly possible—might not be the most efficient way to share information about individual students with multiple departments over time. What we’ve seen our partners do with much success is leverage institutional tech capabilities—usually the CRM—to capture data, then integrate this data with information from an LMS or SIS. Once this data is consolidated, you’ll be able to get a good idea of the various demographics and behaviors that correlate with the retention of a student. By consolidating those data points into one central location that supports multiple institutional constituents, you can impart a proactive and cohesive student strategy that combines coaching—which Helix often refers to as success coaching—and various communications throughout the student lifecycle.

If you do not currently have the technological capabilities to aggregate your data in a way that is meaningful, it might be time to look at implementing technology that you don’t currently have.

Construct a data strategy
Once a data analysis system is in place, this data can inform all outreach and communications activities to enhance a student’s opportunity to graduate. Use the data to form insights into the various risk factors demonstrated by your student body that may stand in the way of academic success. Some of these risk factors may show up during recruitment, and some after they’ve begun pursuing a degree. It is important to do more than simply collect this information; you must do something with it. Create models to identify which students are at risk, and implement personalized action plans. Ultimately, these data-driven actions can inform a comprehensive retention strategy.

Personalize action plans using a tiered approach
It is important for students to feel like they’re being treated as individuals, acknowledged for their strengths, supported through their challenges, and proactively guided to their goals. Yet it can be logistically hard to impart a separate strategy for each individual student. A tiered approach is a good way to mitigate the logistical challenges of an individualized retention action plan. In a tiered approach, students are placed into one of three tiers that indicate how much support the student will require. The tiers are represented as follows:

  • Tier 1 – These students are characterized as highly motivated and persistent, with little need for institutional support. The indicators for this tier include high levels of engagement, participation, and academic performance. While still supporting this tier, you needn’t spend a large amount of resources on students in this category.
  • Tier 2 – These students are those in need of the most support and make up the tier that you should emphasize in your outreach. The indicators for this tier include inconsistent participation and engagement—they might be participating in one class but at risk of failing in another. Their GPA may be above satisfactory, but they might have a track record of not always earning credits in the classes they take. This group is important to recognize and actively engage; get to know them and evaluate red flags and motivations to ensure they overcome their challenges and persist through to graduation.
  • Tier 3 – This student group is most at-risk, and they might drop out no matter what level of support they are provided by the institution. Indicators include failing several classes in a row, starting a term on probation, and a history of unsuccessful attempts at a degree.  This tier is where many institutions might direct most of their focus and resources, but that can be a large and costly investment with minimal return.

Analyze closed-loop data insights to inform future recruitment
Data is like a fine wine: it gets better over time. Your data inputs are always changing, and it’s important to view data analysis in terms of iteration. As your data set grows more substantial, you’ll be able to derive insights that are deeper and more detailed over time.  These insights will, in turn, inform future recruitment and retention efforts, closing the loop on student success.

The relationship between coaching and data is cyclical and iterative. These two components can be called upon to solve myriad institutional challenges, from enrollment attrition to low graduation rates. By utilizing these best practices throughout the entire student lifecycle, your institution can focus on recruiting more and better-suited students for your institution while also graduating those same students.

To learn more about best practice predictive retention technologies and proactive coaching interventions in higher education, download our free quick guide: Predictive Student Retention: The Power of Data + Coaching.


*This is a reposted article. The original article was published by Career Education Colleges and Universities (CECU). 

Sarah Horn

As the VP of Retention at Helix Education, Sarah brings unique insight into student retention from more than a decade of experience in higher education, nearly all in operations. She has designed, scaled and managed a success coaching program for an online Associate's Degree, and has a tremendous amount of experience aligning and implementing relevant, practical retention strategies that drive results. Previously, she worked for Inside Track as Campus Director, implementing large-scale partnership. Sarah is a graduate of The University of Rochester and earned her Master's degree at John F. Kennedy University.