If you’re in higher ed, you’re probably wellacquainted with big data. Maybe you’re even putting it to work tracking student performance. But if you’re not using it to streamline your recruitment model, you’re not realizing big data’s incredible potential.
The uses of data mining and analysis extend much further into the education arena than just keeping students on course to complete their programs. And while statistics show that less than a third of colleges are effectively strategizing with data analysis, schools who do incorporate these methods see a decrease in marketing spending and higher successful enrollment. Case in point, the University of Iowa has been developing predictive modeling strategies since 2014 and, as a result, has seen more accurate enrollment projections and lowered marketing costs.
How can data analysis be used to advance your recruitment model?
So how exactly does data analysis fit into the equation and deliver these results?
You can sum it up in three main concepts: prediction, prioritization and performance tracking.
Data for Prediction
Predictive modeling examines historic patterns in order to project future results. By culling data from your most successful past students and looking for commonalities, you’re able to see trends that can be extended into forecasts for future enrollees. These predictions and common traits are used to help create personas: models of which types of students are more likely to be interested in and flourish at your institution. And because your student demographic is broad, you will likely have multiple personas that are generalizations of these demographics – a microcosm of your student body.
Once you have your ideal students categorized into personas, you are able to effectively target them based on what you already know about them: their interests, media usage, personalities, age bracket, motivations, and so forth. You can then tailor the marketing experience to each persona. How can data analysis be used to advance your recruitment model? INNOVATION The frank Agency 29 Not only does this increase the effectiveness of your campaigns, but it also provides a more personalized experience for the prospective students and demonstrates that you see and understand their needs.
Data for Prioritization
Developing personas for more focused targeting is certainly useful for gaining inquiries. But once you have a slew of inquiries in your system, they can be impossible to sort and prioritize without some indication of which inquiries are most likely to convert.
Using the same data from developing personas, you can identify specific traits that indicate whether the inquiry should be prioritized as High, Medium or Low. These labels essentially tell you which inquiries have the highest likelihood to enroll and stay enrolled in your program, so you can focus on them first. By pairing these categories with your CRM, you can even automate the follow-up process according to your prioritization to save time.
Data for Performance Tracking
We get it – tracking your return on investment is a pain. In a higher education setting this is particularly true, as you’re not just dividing the lifetime value (LTV) of a student by the cost spent on marketing to the student. You also have to treat each program and degree level individually, then factor in the cost of the program, the average length of enrollment, whether the student is a transfer student or not, and the source of the enrollment itself. It’s a complicated formula. But before you write it off as a waste of time and energy, consider that all of these scenarios and values can be figured using your historical student data.
You already have all the information – now use it to see if your marketing investment is delivering the return that it should. And if it isn’t, you can return to the data to see where the breakdown occurs and tweak your model accordingly.
Tracking ROI shouldn’t be considered a cringeworthy practice in education. It’s in the best interest of both school and students to ensure that money is not being thrown to the wind – or in this case, ineffective marketing strategies. By tracking ROI, you can cut costs on ineffective practices while increasing your enrollments and retention – and this, in the end, means more funding can go toward developing first-class degree programs and investing in students.
The Big Data Movement
The number of schools utilizing data mining for retention programs is increasing as schools realize the potential of big data. However, without applying these strategies to the very first steps of recruitment and enrollment, your campaigns will quickly lose steam. With inexhaustible amounts of information at our fingertips, the best way to benefit schools and students alike is to utilize this data to form a single, united process that runs from recruitment to enrollment to graduation. And the efficiency and financial gains to be had from this would allow institutions to focus on the real mission: developing students that are primed for success gains to be had from this would allow institutions to focus on the real mission: developing students that are primed for success.