The Goal
To leverage Statwax’s in-house data science capabilities in order to refine marketing messaging, targeting, and overall usage of personas – with the ultimate goal of boosting marketing-driven enrollments and cost efficiency.
The Client
A major four-year state university that is partnered with Statwax for all digital student acquisition efforts across its main campus and programs.
The Challenge
Statwax had already been partnered with the client and delivering success through digital strategies. With full closed-loop tracking in place and integrations with the school’s CRM and SIS, attention needed to turn toward how to better analyze and use the available data. The challenge became how to unearth the hidden stories within years of student and marketing data, and create a narrative that could influence the way we adjusted ads and messaging.
The Strategy
Through all of Statwax’s digital acquisition efforts – both localized and nationally for the university – specific demographic audiences were at the core of the strategies. We wanted to maintain precise messaging based on demographics and higher education desires – whether the target was a parent, adult learner, program-specific interest, legacy student, etc.
Statwax knew that the next evolution in its campaign strategy would be to model out more precise and confident ad targeting strategies at a national level. Budgets could not effectively engage the entire U.S. at once, and hitting enrollment goals meant we had to dig deeper to find out exactly where and how to engage prospects.
Statwax developed an in-house statistical modeling program to pinpoint the best way to launch a multi-channel effort nationwide without exceeding budget. This model looked at a variety of personas that Statwax and the client had developed, based around demographic signals such as age and gender, income level, educational history, and more. Statwax’s model then mapped the historic application and enrollment performance as well as realized revenue for the university by zip code across the entire nation, using years of data from the internal systems. From this mapping, proprietary modeling formulas matched up application and enrollment performance against the presence of those personas in each zip code. The result was a look at individual areas nationwide where the school was under- or over-performing application and enrollment volume against the expected outcomes, based on how heavily the key personas were found there. If a particular zip code was heavily populated with one key persona, for example, but there were few applications from them and those few did well at converting to enrollment, the model would highlight it as an opportunity to invest more marketing focused on that specific persona. Statwax then baked in revenue forecasting to identify the areas of most potential financial impact for the client to prioritize.
The outcome was zip code- and county-level scoring to show the best opportunity for gaining more applicants, enrollments, and revenue as well as the specific personas to target in that area. This was all output as a series of “scores” to help sort and identify locations.
The raw scoring data and maps were then developed in-house into a proprietary web application that the client was able to securely access. It provided immediate visibility into the outputs of the model, filterable by key persona as well as location.
The dataset was set up with automated bulk sheet capabilities for Statwax – allowing the Paid Advertising team to export a location list of the top-priority and top-opportunity locations and apply bid modifiers en masse before uploading into active campaigns.
Statwax saw further interest in using this data model and web application to improve the client’s non-digital outreach efforts. The university was spending time and money to send in-person recruiters to markets and high schools with limited direction. The one-size-fits-all approach worked fine, but we saw an opportunity to give the on-ground team more guidance on where to deploy resources and how to structure their approach and content.
Statwax integrated third-party datasets into the application that provided visibility into the high school makeup of each location being modeled. The client could instantly see individual high school demographics in each location identified as having the highest opportunity and priority for marketing, thus allowing better deployment of on-ground resources and better creation of specific messaging, materials, and talk tracks.
Statwax used this data to map out a spend plan that maintained a nationwide focus but skewed ad spends and bid levels at a zip-code level. A full-funnel channel mix was developed for each persona to generate awareness, nurture interest, push conversion, remarket across all touchpoints, and follow up post-application for additional nurturing to enrollment. And all touchpoints were crafted around the key demographics and persona traits identified as having the best per-zip code opportunity in Statwax’s models.
The Results
With the deployment of this data-driven targeting analysis, Statwax was able to produce immediate lifts in all KPIs. Ad reach fell by 8% year-over-year, as Statwax was able to confidently trim the fat from campaigns by eliminating locations or channels that did not reach the right personas or predict the best success. While this reach (and total ad spend) declined, actual engagements on ads increased by 47%. Applications generated through Statwax efforts improved 69%, helping Mizzou achieve their best application totals since COVID began. And the ultimate desired metric – enrollments – improved by 36% over the same period of time as Statwax’s analysis helped ads reach the best locations and personas that were most predicted to enroll.
The Takeaway
Your data tells a story, even if you can’t always see it right away. With the proper tools and modeling, a school’s entire marketing strategy can be refined and optimized based not just on what’s already happened, but on what we can predict to happen. And when marketing spends, touch points, and messaging are all aligned with the ideal personas and demographics, a school can generate far more students without actually spending more.
