What can big consumer brands teach graduate and adult enrollment leaders?
October 17, 2022
Brands seemingly know what I want the minute I decide it – sometimes even before! That’s because modern marketing leverages machine learning, advanced targeting, and deep consumer knowledge to personalize messages that drive greater engagement, stronger results, and seek to answer questions before they’re even asked. The good news for schools looking to improve their graduate and adult learner marketing is that big consumer brands are setting an example for higher ed—especially at a time when finding and recruiting prospects is increasingly complex.
In my role as a Senior Data Scientist in EAB’s Adult Learner Recruitment division, I have seen first-hand that applying these marketing strategies to graduate and learner student recruitment translates to enrollment growth.
Your high affinity students might surprise you
Your student body has a truly unique profile—and it might not be what you think. For example, we partnered with a nursing program at a college adjacent to a lake and found that 72% of its prospects were women who owned boats. While the prospective student gender was expected in a known female-dominated field, the applicants’ nautical affinities were a surprise, and helped the college pivot its creative strategy. The nursing program tripled its click through rate after incorporating images of boating and fishing in its advertisements.
In the era of marketing analytics, many schools I talk to are starting to apply basic modeling strategies to elevate how they recruit adult students. They identify profiles of students they want to attract, reflect on their past students using Student Information System (SIS) and Customer Relationship Management (CRM) system data, and use basic regression models to inform their targeting. This DIY-modeling can work well, but your insights are only as good as the quality and quantity of the data you have. For most schools I talk to, there is a desire to know more than what their current systems can tell them.
Tactics Aren't Reaching Prospective Graduate & Adult Learners
70%
of adult learner applications are stealth applicants.29%
of surveyed graduate and adult learners are opting not to take admission tests.Taking a cue from companies like Proctor & Gamble and Target, EAB uses a consumer database (comprised of information on purchasing behaviors, consumer surveys, public record demographics, and similar) of more than 200 million individuals to help our partners be more efficient and effective in their targeting.
How machine learning is used in graduate and adult learner marketing
References to machine learning are ubiquitous in marketing conversations these days, though it isn’t always clear what is (and isn’t) machine learning or how it impacts our daily lives. Here’s one tangible example: If you’ve ever had your credit card frozen when “you” tried to buy a lawnmower in a town you’ve never been, you’ve encountered a common form of machine learning used by big brands called outlier detection. Your creditors use your purchasing history to identify new transactions that are unusual and potentially fraudulent. Machine learning determines whether your new behavior was supported by previous observations.
Enrollment and marketing teams can use similar techniques, such as high-affinity modeling, to identify patterns that can be used to discern which prospective students in the general population exist within the same orbit as their current and past students.
To laser-focus our affinity-profiles, we scrutinize data across as many as 115 variables per consumer. Each data set fills in gaps in the other, appending the attributes of prior students with those of potential students according to their similarities in such things as their love of travel, interest in basketball, ethnicity, where they live, how much money they make, and whether they’ve spent money on online education. These data points allow us to identify prospects who are a good fit for graduate or adult learner programs, often before they themselves have raised their hands or started actively looking.
Translating insights into increased campaign performance
It’s not enough to know incredibly nuanced things about your prospective students. You must also understand best practices for applying those insights. The art of graduate and adult learner recruitment is in taking data and using it to inform specific, and potentially transformative decisions about campaign messages, creative strategies, and communication plans.
For example, one of the large public schools we work with is looking to grow their graduate education program. After closely analyzing their historical data, the models we ran indicated that this school’s students were motivated by helping others, often putting their own needs second.
Using these insights, we helped the program shift its messaging strategy from one designed to appeal to “career advancers” to a more mission-driven message, which tripled campaign performance. If you want to increase engagement, every choice matters—from photography, to copy, to sequencing.
The most important lesson we are learning about adult learner recruitment is that no two student populations are the same. Even as I compare schools that seem similar (business school to business school, regionally similar schools, etc.), data always reveal a distinct set of attributes. When dealing with this level of nuance, the key to success is always in the analysis. Which data you use, how frequently you examine it, and how nimble you are with your messaging strategy will determine the results you see.
Personalized marketing is effective
Although I sometimes find the ads in my social media feeds eerily on-point, the reality is they’re effective. The more personalized to my needs the ads I see are, the more likely I am to engage and commit, whether it’s buying something I want, discovering something I didn’t know I need, or making the big decision to pursue additional education.
200M + consumers in EAB’s proprietary database.
Chances are, your graduate and adult students aren’t much different.
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