16M and growing: What’s driving the NCAA’s effort to build its fan database?

In early 2024, the Indianapolis-based NCAA partnered with sports technology firm KAGR to develop a database to learn more about the tens of millions of people who tune in to collegiate athletics annually.

The database already has information on more than 16 million fans, and that figure is only expected to grow. That data is largely used for marketing, to help the NCAA connect with existing collegiate sports fans and sell them on events they might want to attend or tune in to involving the school or sports they like best.

Brian Higgins is the NCAA’s senior vice president of business performance and oversees the organization’s data collection and analysis work. He spoke to IBJ about the benefits of the database, the role artificial intelligence could play in using the database to develop long-term marketing strategies and how the NCAA has honed its site-selection process using the treasure trove of information.

This interview has been edited for length and clarity.

Could you give an overview of what this fan database is—and why the NCAA has one?

The fan database is a collection of everything we know about the fans that we’ve interacted with: contact information, where they live, what sports they like, what teams they root for, and the like. We first built it to help us grow revenue in selling tickets to our own championships, primarily. We sell tickets to men’s and women’s March Madness but also volleyball, softball and other sports that are really growing, but then we also sell tickets to swimming, and track and field and other sports that maybe don’t have the same commercial potential.

We wanted to know as much as we could about our fans to provide custom marketing through emails, social media posts—things like that—to drive people that might be interested in, for example, early rounds of the volleyball tournament to attend or watch on our TV partners. That’s why we built it.

How does the NCAA handle security around this data? How many people have access to it on a daily basis, and how does the organization safely implement strategies that involve its use?

There’s a handful of people that are involved and have access to the data tables, but we follow best practices, in terms of encryption and data-handling standards.

Obviously, contact information can be relatively sensitive, and we treat all that with the appropriate care, but we don’t have things like medical information, people’s entry financial information; we don’t store credit cards. Even though [credit cards] might help us identify people across different events, the data security risk of doing that is not worth the benefit of it. We do think a lot about that, so there are only a few people that have access to the underlying data, and then our sales and marketing team uses it to build segments.

A good example is when we found out Tennessee was coming to Indianapolis for the Sweet 16, and then they won in the Elite Eight and we had the game in Lucas Oil Stadium. We had a lot of unsold tickets. So the marketing team took the data and created a segment of people that we know to be Tennessee fans who live within a certain driving distance of Indianapolis, and they sent out a custom email.

How does the NCAA use artificial intelligence tools in how it uses the fan database?

Before I worked at the NCAA, I was a consultant, and I did a lot of projects with pretty high-end data scientists working with artificial intelligence. And one of them said to me, “Artificial intelligence is just what computers have only recently learned how to do,” and that’s a constant moving target.

I think a lot of what we are doing today would have been considered artificial intelligence maybe three or four years ago—segmenting people by geospatial analysis of driving distances and things like that. That’s pretty advanced computing relative to what computers could do 10 years ago, but it wouldn’t necessarily be what people think of as artificial intelligence today.

We’re much more focused on getting really good, rich data on people. But the analysis, we don’t really need artificial intelligence for that. I don’t think in the short term, AI is as useful for us in what we’re trying to do with the data as it may be for, certainly, other business units.

Going back to your earlier question about data security and data privacy: Without AI, we have total control and can make sure that all of the analysis we’re doing and everything we’re doing is totally within our own standards and practices and, frankly, the laws of all the states we operate in.

I don’t know that if you turn on an AI to start combing through our data for patterns that people would feel comfortable with the connections the AI was making. Every time we send out an email to somebody saying, “Here’s an event that we think you’re interested in,” we want to feel really confident that the person receiving that is like, “Oh, I can at least understand, based on my interactions with the NCAA, why they would think I would want to go to this thing.”

As soon as you start turning an AI loose, particularly large-language models, it may be great at identification, but if we can’t explain why the computer thinks someone would like to attend a University of Tennessee basketball game in Indianapolis, it’s probably not worth it for us.

Whenever the topic of Selection Sunday for March Madness comes up, there’s often a lot of misconceptions about who sees what, when, and even more pertinent, how certain decisions are made. So I’ll just ask you directly: Is this data ever used to set schedules or figure out what teams should compete with each other in which cities to drive ticket sales?

The answer to that is no. The selection committee sets and selects the brackets—and this is true of all the sports—based on their bracketing principles. This database doesn’t play in one bit.

Where it does play in a little bit is with site selection for where tournaments go. As an example, around this time last year we announced our sites for, I think, 2026 through 2028, and you have to do that many years in advance to book the buildings. So we worked with our championships team to give them data on where the fans of various sports are, to try and find good sites.

That data was helpful in making them feel comfortable enough to put our volleyball championship in San Antonio in the Alamodome, which is a much bigger configuration than where we typically go to—an NBA-type arena that tops out about 20,000 seats. With the Alamodome, we will be able to sell close to 30,000 for volleyball. I don’t think we would have been comfortable making that decision without an understanding of our volleyball fans, and we have a lot of them in Texas.

With Division I football being kind of its own thing—particularly in the postseason—what role, if any, does the NCAA fan database have in supporting ticket sales for those events?

While we don’t do much for the FBS (Football Bowl Subdivision) championship, we handle sales for the FCS championship (Division I-AA). That event had been in Frisco, Texas, for a number of years, and it’s going to be in Nashville this year due to renovations at our regular stadium, but we often keep our heads down trying to figure out how we can drive activity for that.

For FBS, we do use this data sharing with schools—we’ve worked with some to help them find who in their football data is also fans of women’s basketball, ice hockey, of baseball, so that they can expand the breadth of how they sell. The athletic departments in general at FBS schools are heavily focused on selling football tickets, as they well should be, because that’s what drives the most revenue. But we’re helping them to find fans of other sports beyond that, and then they help us with their data.

Is there anything interesting that the data has told you about Indianapolis, like what other sports people may be fans of that Indy hasn’t yet tapped into for hosting duties?

I’ve not gone in and tried to find any special nuggets that indicate, for example, there should be more field hockey or ice hockey in Indianapolis. But when we just look at our data-concentration ratios, we just have a ton of sports fans in Indianapolis, and we want to be good partners as members of the city and community to provide awesome events like the Final Four.

I’ll give you the last word. Is there anything else you’d like to add that we haven’t touched on?

I think now that we’ve built out the capabilities to sell our own tickets using this data, we really are focused on making the data useful to our member institutions. So, if there’s anybody at Indiana University, Purdue, Notre Dame or any other school—Division I, II or III—that wants to talk about how we can work together on data, we’re open for business.

We want to do everything we can to help our member institutions. It’s a really challenging time. It’s an exciting time with all the changes in college sports, but it places a real demand on everybody to grow revenue, and anything we can do at the national office to help them grow their own revenue sources, we’re excited to do that.•