With the World Cup underway, global attention has once again turned to football. For football clubs, this moment should be a data analytics gold mine. Many already have years of fan data, especially in markets like Brazil, where membership programs are deeply embedded in the business model. Yet that data is often scattered across disconnected systems for ticketing, memberships, e-commerce, and social, making it hard to turn information into meaningful action.
In this episode of The AI Forecast, Paul Muller speaks with Caio Nogueira, co-founder of Lupa Data, about what’s holding clubs back—and how they can start turning fragmented data into real fan engagement.
What does this mean on the playing field? Here’s how they break it down.
Turning World Cup Moments into Fan Data Opportunities
Paul: How do you see the World Cup as an opportunity for customer engagement, and how quickly can clubs turn this data into insights?
Caio: In our segment, especially in sports, we focus on what we call fan data. And with that fan data, we saw a singular opportunity around the World Cup.
There’s a phenomenon where everyone watches the World Cup, even if they’re not football fans. What makes someone who doesn’t normally watch or care about football suddenly follow the World Cup so closely? I don’t know exactly what it is, but when the World Cup comes around, if there’s a game that day, everything stops. People don’t work, they go home and watch the game.
What makes people behave like this? We can get a lot of information from social media about how people interact with the games. That’s what draws people in. It’s an especially good time to capture that kind of unique information, something we only really get during big occasions like this. So, the World Cup can be a bit of an entry point for that.
Understanding Behavioral Segmentation in Sports Fans
Paul: That’s exciting. As I mentioned at the start, many listeners work with subscriber data—newsletter subscribers, clubs, associations, or loyalty programs.
We have lists of people interested in our company, sport, or brand, but many struggle to know how to engage. You mentioned "behavioral segmentation.” Can you explain what that means?
Caio: There’s an example coming from Europe, especially the Premier League, who already have this kind of segmentation in place. It’s about understanding the different groups of people—fans, not even just members—and what they want.
For example, what are the needs of fans who have children? What do they want when they go to a game? They want safety. They want a good environment where they can bring their kids and enjoy the experience together. In the Premier League, there are representatives for differently abled people. Their needs are likely around access.
So, all these groups have different needs. The question is, how can we offer benefits that align with those needs? Maybe that means seats that are easier to access, such as those closer to ramps.
At the same time, you wouldn’t place a family next to the more intense fan sections where organized supporter groups are chanting, waving flags, making a lot of noise. In some cases, especially in places like Brazil, those areas can even become confrontational. That’s not the right environment for kids. So, it’s about understanding these different needs, how each group interacts with the game and its culture, and then aligning your experience with that.
Why Clubs Struggle to Turn Fan Data into Action
Paul: It sounds to me like your perspective is that clubs and associations aren't really using their fan data effectively. Would you agree with that statement?
Caio: Oh, 100%. There’s a lot of data, mostly unstructured data, spread across Excel spreadsheets and different databases, like ticketing systems in stadiums. Most big teams have their own stadiums, so why aren’t we using that data to create a better experience for fans?
There have been some attempts, especially here in Brazil. For example, Palmeiras, one of the teams from São Paulo, has already developed an app to improve payments. Payments can be annoying sometimes because each venue has its own system. So, if you’re a Palmeiras fan, you can use their app to pay in their stadium. That brings convenience and generates data. But there still isn’t real communication between systems. I don’t see memberships connected to ticketing, or ticketing connected to e-commerce, or even to access control in some cases.
Take another example: when there’s a rival team playing at a local stadium, transportation becomes a problem. Buses get overcrowded, the metro fills up, so it’s difficult to even get to the stadium. Why not coordinate with the city and say, “From this time to that time, let’s add more buses on routes going to the stadium?” That would make things much more convenient and improve the overall fan experience.
Paul: That doesn't sound like a technology problem. That sounds like a problem of vision and a problem of collaboration. Would you agree with that statement? It's not like we don't have the technology.
Caio:
I would agree. The problem here, as you said, isn’t the technology. We already have the technology, we’ve had it for quite some time. What we need is a framework to make it happen, and the commitment to actually do it.
It really comes down to knowledge and application—understanding what data you have and how to transform it into usable, needs-aligned information. Right now, we’re working with teams to make that happen. At the moment, there’s a lot of loose data, some from e-commerce, some from membership, but it’s limited. Membership data covers only members; we don’t have much from the general public, which would be valuable to collect if we can figure out how to do so. We’re trying to clean and organize this data, so we can apply it directly to the needs of those segments we talked about.
Catch the full conversation with Caio Nogueira on The AI Forecast on Spotify, Apple Podcasts, and YouTube.
