Relevance is the New Acquisition Advantage

With the emergence of prediction markets, regulatory scrutiny, and higher taxation inflating acquisition costs and increasing financial pressure on sportsbook operators, Nikolaus Beier, SVP Media and Marketing Services at Sportradar, explains why relevance – rather than simply more advertising – will increasingly determine marketing performance.

Sportradar talks about the importance of acquiring high-value customers in today’s competitive market. How do you define a high-value player?

Everyone wants to acquire high-value customers, particularly because we know that in sports betting a relatively small percentage of players can account for a significant proportion of revenue. Ultimately, though, it comes down to data.

Operators will define value slightly differently, but customer lifetime value is the key metric. If you understand where and how you’ve acquired those high-value customers across your campaigns, you can optimise future activity accordingly. This is where marketing technology designed exclusively for betting becomes so valuable. It provides direct access to these target audiences and a granular understanding of their content preferences and consumption patterns, to continually refine campaign performance.

Scale also helps. If you’ve acquired three million registered users in 2025, for example, the likelihood of identifying the right people within that dataset is much higher and the patterns become easier to scale than when you’re working with non-specialist technology.

Prediction markets have quickly become part of the conversation. Do you see them competing with sportsbooks, complementing them or eventually converging with them?

From an advertising perspective, the logic is similar because there is clearly an overlap between the potential audiences, particularly sports fans who are interested in the probability of a particular event occurring. What I think prediction market operators have done particularly successfully is build products that appear very attractive to consumers, the simplified approach of effectively saying yes or no to an outcome seems to resonate.

I think we’ll see more of that simplicity within traditional sports betting as well. From the user’s perspective, whether something is technically considered a financial product or a betting product isn’t necessarily the important question. They want to be entertained.

In addition, our years working with hundreds of sports betting operators, we’re very proud to have recently announced partnerships with both Kalshi and Polymarket. They’re using our data and technology, and marketing is an important part of these agreements. They’ll use our marketing engine to help acquire, retain and engage users. The deals demonstrate that the products we offer are relevant both to traditional betting operators and prediction market businesses. Essentially, we have the expertise to identify and target relevant audiences very effectively.

Could prediction markets expand the overall audience rather than simply compete for existing sportsbook customers?

Prediction markets are increasing the total addressable market by attracting new participants and creating new ways for people to engage with sports. We are seeing the ecosystem continue to grow with new exchanges, market makers, and brokers entering the category. That creates a growing need that Sportradar is uniquely positioned to address through our data, fan engagement products, and customer acquisition solutions, helping these platforms attract and retain new customers while differentiating their offerings.

Does supporting sportsbooks and prediction market businesses create a conflict when they’re potentially competing for the same customers?

At Sportradar, we sit at the intersection of the sports, betting, gaming and media industries, and we’re one of the biggest providers of sports betting services in particular. 

So, it’s our role to serve our thousands of clients, from sportsbooks and iGaming operators, prediction markets, rightsholders, media and tech companies, and even government agencies and law enforcement through our integrity services.

Our multiple sportsbook clients compete with one another, so we don’t see any conflict with prediction markets. From Sportradar’s perspective, we remain agnostic and provide solutions according to each client’s needs and their individual goals, as they all have different budgets, strategies, markets and objectives. Our job is to provide the best tools possible to help deliver success, regardless of who you are or where in the ecosystem you may be.

Marketing platforms promise better targeting and attribution, but you’ve been particularly critical of last-click attribution. Why is it still such a problem?

I’m always fighting against last-click attribution because I think it’s outdated. It’s effectively how we measured digital advertising 20 years ago. We now have a much better understanding of the broader acquisition journey. The job of marketers should be to understand that journey and optimise against it.

What I still see too often is an isolated view of individual channels. I recently heard a great analogy involving Bayern Munich and Harry Kane. If you ask how Bayern can score more goals – while considering that Kane scores 30 goals per season, you don’t simply buy another 10 Harry Kanes and assume you’ll score 300 goals. Obviously, that’s nonsense. You need Harry Kane to score the goals, but you also need the rest of the team to create those opportunities.

Marketing works in much the same way. Acquisition channels and other forms of marketing work together. There are plenty of ways to measure this properly. You can use multi-touch attribution, while AI is creating more opportunities around media mix modelling where you can run experiments and understand how individual channels influence the eventual outcome. Simply measuring the last click is easy, but anybody who understands how customer decisions are made knows there’s much more happening before that final interaction.

Does Sportradar’s betting-specific data and technology create a significant advantage over general advertising platforms?

Generalist platforms struggle to understand some of the specific requirements of the gambling industry. It starts with having the right data available and being able to target and trigger advertising according to relevant sporting events. It also involves understanding which supply sources you need and having a curated supply. Creative requirements can also be different from other industries. The combination of those elements is unique. What we’ve built is entirely focused on the gambling industry and its proprietary technology rather than us customising a third-party solution.

The results support that approach. Again, look at the World Cup final example where we achieved a 400 per cent increase in attention. That’s very significant, particularly in competitive markets where efficiency is increasingly important. Ultimately, advertising always comes down to return on investment. What we’re offering isn’t necessarily more expensive than generalist platforms – it’s more targeted.

As advertising rules tighten and third-party identifiers disappear, where is the boundary between useful personalisation and excessive targeting?

First, there are regulations in place, with GDPR being the obvious example, and operators have to comply with those. There are technical and legal limitations around personalisation, but there are also ways to personalise without requiring huge amounts of first-party data. Contextual advertising is one example. If you understand the context of what someone is currently reading or the page they’re visiting, that creates opportunities to make advertising more relevant.

AI also opens significant opportunities because historically one of the limitations on personalisation was simply creating the volume of advertising required. You can’t manually create thousands or millions of different ads. AI makes that much more achievable and we’re using it extensively within our platform specifically for betting. I don’t think we’ve reached the sweet spot yet. You can certainly overdo the number of touchpoints, but I think that’s a bigger concern than personalisation itself.

What about over-personalisation? Can operators reach a point where more data becomes counterproductive?

Potentially. Using large amounts of data comes with a cost. You need to collect it and make sure it’s technically usable, so there may be circumstances where the cost of collecting and accessing additional data exceeds the benefit it produces.

Ultimately, though, it comes back to relevance. You want to be relevant to the customer. The best advertising is advertising that isn’t really perceived as advertising at all, but as valuable information that helps someone make a decision. That’s where personalisation can help. Can you overdo it? Maybe. But when I look at how many operators are still essentially advertising by taking a bonus and pushing it out to everybody, I think we’re still relatively far away from that point.