Universities are data rich and insight poor. Here's how to fix it.

I’ve spent much of my career at the point where marketing meets data. I completed an MBA in Big Data Analytics because I could see, even in hospitality, that the organisations winning were the ones turning information into decisions faster than their competitors. When I moved into higher education, I found institutions holding extraordinary amounts of data and using remarkably little of it.

Student records, CRM data, web analytics, survey results, rankings data, research metrics, social listening, application funnels. Most universities have all of this. What they often lack is a way of bringing it together so that leaders can see what’s happening and act on it.

Why the gap persists

The problem is rarely the technology. It’s usually a mix of three things.

Data lives in silos. Admissions, marketing, planning, research and student services each hold part of the picture, in different systems, with different definitions. Nobody has the whole view.

Reporting replaces insight. Teams spend hours producing reports that describe what happened, and very little time explaining why or recommending what to do next.

Decisions aren’t designed around data. If the key decisions in an institution are made in committees that never see the data, or see it months late, even the best analysis changes nothing.

Reporting describes what happened. Insight tells you what to do next.

What made the difference for us

At Newcastle University, we implemented HubSpot with stronger governance and introduced Google Analytics 360, but the bigger change was cultural. We built a data-driven segmentation and content strategy and, most importantly, created processes to share insights across teams and channels rather than keeping them inside marketing. When colleagues could see how their activity connected to enquiries and applications, the quality of conversations changed.

Earlier, at the Students’ Union, personalisation based on better data increased email engagement by more than 300%. The data had always been there. We’d just never used it properly.

A practical route forward

Start with the questions, not the data. Ask senior leaders which five decisions they most need better evidence for. Build from there.

Agree common definitions. What counts as an enquiry, an applicant or a conversion should mean the same thing in every team. It’s unglamorous work and it underpins everything else.

Automate the routine reporting. Dashboards that update themselves free analysts to do what they’re actually good at: explaining, testing and recommending.

Put insight in front of decision-makers. A one-page summary at the start of an executive meeting is worth more than a hundred-page report nobody reads.

Invest in data literacy. The most sophisticated analysis is wasted if colleagues can’t interpret it. Short, practical training for managers pays back quickly.

Use AI carefully, and early. AI tools are already good at summarising data, spotting patterns and drafting commentary. Used with clear governance, they can dramatically shorten the time from data to decision.

The prize

Universities that close the gap between data and decisions will recruit more effectively, spend more wisely and understand their reputation in far greater depth. Those that don’t will keep producing reports while their competitors act.

The technology to do this is affordable and widely available. What’s needed now is the leadership to make it part of how the institution thinks.