After six years of working with dozens of universities and education companies, there’s one limitation I keep coming back to — attribution tracking. Or rather, the lack of it.
I’ve rarely seen a CRM and tech stack that truly speak to each other. Data sits in silos across different tools, teams, and dashboards, and as a result, it’s almost impossible to get a clear picture of how the full marketing machine is performing. We analyze email performance without knowing whether open and click rates correlate with paid campaigns. We review conversion rates from lead to started application and ask whether events impacted those numbers, but often overlook whether someone spent significant time on the website — and what content actually drew them in.
Social media metrics are another example: we track engagement, impressions, and clicks, but don’t connect that activity to started or submitted applications. There are so many gaps in attribution that, at times, it feels like most institutions have quietly given up trying to fix them. And honestly, I understand why. In higher education, projects are complex. Everything needs strategy, research, and committee approval. The “just do it” mentality that drives experimentation in other industries often gets lost in the process.
I’m not criticizing marketing teams — far from it. But universities are businesses just as much as they are educational institutions. And our sector doesn’t always operate with the agility or integration the commercial world relies on.
So, what’s the solution? Realistically, no single tool can fix this. But there should be a business intelligence (BI) team working for marketing — feeding insights back, not just reporting upwards. Over the years, we’ve tested countless ways to improve attribution reporting for our clients. Most didn’t work. Until one did.
If you don’t have one single source of truth, you need to create one. The most effective approach we’ve found is extracting raw data from every source via automated schedules into a central data warehouse (or even just a spreadsheet), manipulating and merging it there, and then visualizing it in a BI tool. Think of it as an MVP — a proof of concept to show senior leadership how powerful real attribution insight can be.
Because when you can trace every lead, application, and enrollment back to a specific campaign — down to the creative asset used — that’s when you can finally optimize based on meaningful signals, not vanity metrics.
It’s daunting, yes. But without it, you’re not getting the most out of your agency, your team, or your marketing spend.
What would your decisions look like if you truly knew what was driving them?
