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2022-11-28T21:10:10+00:00July 31, 2018|

Breaking Down the Complexities of Higher Ed Data Systems

Collegis Education Sr. Marketing Technology Manager Dan Antonson presented on “Using Search and AI-Driven Analytics to Deliver Instant Answers to Everyone” at the Big Data Tech conference in Bloomington, Minnesota. The conference was hosted by MinneAnalytics, “a nonprofit organization dedicated to serving the data science and analytics community in Minnesota, the Upper Midwest, and beyond by providing accessible, authentic and engaging events.”

Dan Antonson: Breaking Down the Complexities of Higher Ed Data Systems

Dan Antonson, Sr. Marketing Manager, Collegis Education

This was the event’s fourth consecutive year and more than 1,800 registered or joined the waitlist for the event, breaking past attendance records. The daylong conference featured more than 50 sessions on a diverse range of topics, according to a MinneAnalytics event recap.

Antonson’s session was filled to capacity with close to 40 people in the room. A show of hands indicated that about two-thirds of the session’s attendees were involved in analytics for higher education. Focusing on data processes, capture and reporting, Antonson used hand-drawn slides to illustrate the complex nature of college-based data environments. (See images below.)

Hand-drawn slide by Dan Antonson: partial map of a typical college’s data ecosystem.

Antonson finds that drawing the slides by hand allows his audiences to follow along as he charts how a college’s data systems are connected. He shared that when he presents this way to colleges, the people in the room are able to chime in and become a part of the presentation as he draws. Another benefit is that the complexities of the system are revealed one piece at a time and that helps keep the audience from becoming overwhelmed.

“It can be a great way to identify gaps in the team’s understanding of their systems,” said Antonson. Once we draw it out together, the team is more likely to be aligned regarding how they think the system works today, and how to optimize it for tomorrow.”

Antonson addressed challenges typically faced by colleges in that their data management teams are usually small, siloed and manage “tons and tons” of users. Considering that colleges manage lifelong relationships with students, and that the way data is used differs during each phase of the student lifecycle: admissions, enrollment and alumni – data management needs quickly spiral.

What’s more, data must be captured from a variety of inputs including marketing, admissions and IT, and is often stored in multiple systems that do not connect.

One roadblock typical to higher ed is that a key tool that colleges depend on, the customer relationship management system (CRM), can make or break whether data capture may be automated or not. If data cannot be captured, the barriers to mining it to create meaningful reporting are so resource intensive that it becomes impractical.

Unfortunately, many colleges’ CRMs were not built to connect with other systems. Some may allow for nightly automated updates that connect the CRM data with marketing attribution or funnel information so that the admissions and marketing team can get a read on how their campaigns are doing.

Hand-drawn slide by Dan Antonson: Detailed map of a typical college’s ecosystem.

Other CRM systems will only work with products made by the same company. This means that the college would need to buy more products from that company to expand their abilities. The result is that it becomes more difficult to replace any one piece as needs evolve. Once an institution gets deeply invested in a branded platform it becomes dependent. But, even a large investment doesn’t necessarily mean that a single platform is going to be enough to help accomplish admissions, marketing or other data-management goals.

Antonson took the audience through a demo of a data visualization tool that Collegis uses when a college’s CRM system allows for it. Called “Collegis Discovery Engine powered by Thoughtspot” the system allows users to connect data inputs from a variety of sources. It then translates them into user-friendly charts and graphs that help colleges monitor enrollment campaigns. Some of the more popular charts and graphs capture data points such as yield rate, admissions efficiency, rep performance and marketing source trends.

The session concluded with time for questions and answers, with the discussion continuing up until the clock ran out. With questions still hanging in the air, many attendees made arrangements to follow up with Antonson afterward.

— Special thanks to Michael Jarvis, marketing analytics specialist with Collegis Education, for contributing to this article.