Advertising is so good these days that sometimes it feels...too good.
The purse I just told my husband I plan to buy appears in my Instagram feed the next day. My new favorite coffee? All over my Facebook news feed.
Brands seemingly know what I’m into the minute I am into it. This is happening because marketing as a discipline has changed dramatically in recent years. While less progressive brands continue to resort to the "spray and pray" tactics of traditional advertising, today’s marketing winners are leveraging machine learning, advanced targeting, and deep consumer knowledge to personalize messages that drive greater engagement and stronger results.
The good news for schools looking to improve adult learner recruitment: These same tactics work in higher education.
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 recently 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 smartly pivot its creative strategy. The nursing program tripled its click through rate after incorporating images of boating and fishing in its advertisements.
This strategy of knowing your audience and tailoring your messages accordingly is as old as marketing itself. But in the era of marketing analytics, "big data" is changing the rules of the game for personalized messaging. 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 some schools I talk to, there is a desire to know more than what their current systems can tell them.
Taking a cue from companies like Proctor & Gamble and Target, who have perfected this art, 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 clients be more efficient and effective in their targeting.
How machine learning is used in adult student 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 used your purchasing history to identify new transactions that are unusual and therefore possibly fraudulent. Machine learning determines whether your new behavior was supported by previous observations.
Adult student marketers can use a similar technique, such as high affinity modeling, to identify non-outlier patterns 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, ethnic heritage, where they live, how much money they make, and their Myers-Briggs typology.
Translating insights into increased campaign performance
As an adult student marketer, it's not enough to know incredibly nuanced things about your prospective students. You must also understand best practices for applying your insights. The art of 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 big public schools I work with is looking to grow their graduate education program. After closely analyzing their historical data, we found some very specific and useful attributes about their student population. Specifically, 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.
You can see some examples of this in the image below.
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, nursing program to nursing program, regionally similar schools), data always reveal a distinct set of attributes. When dealing with this level of nuance, the key to success is always in the analysis. What 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 creepily 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 buy. And as a busy professional, mom, and consumer, my shopping is becoming increasingly efficient. I love it when I don’t have to search for things I want. They just come to me.
Chances are, your adult students aren’t much different.