Sports sponsorship is the last great measurement frontier in marketing. Not for much longer.

Relo Metrics is focused on measuring all the things that are not an ad. Sport, growing into all forms of entertainment and culture, brand integrations, sponsorships, influencers, creators. These worlds are combining. It is a large-scale data problem to understand what's happening across these places and create holistic valuations so brands, rights-holders (leagues), media companies (Netflix), and creators (the buyers and sellers in every marketplace) all have accurate scale data to keep the market growing.

I've been focused on measurement versus the programmatic buying and selling for the better part of 15 years. There is a continuity of data: data from the contemporary advertising and marketing stack flowing into the data needed to measure things that are not ads. The linear TV model was did someone watch it and what was the ad break? The digital walled-garden world is did someone click, did someone buy? That isn't why people invest in sport and entertainment.

People invest in sport because they want to be part of culture, part of the conversation, associated with something people love. The ad industry loves itself and loves advertising; people love sport. When you have that consumer affinity, brands have to find creative, tactful ways to integrate. This was the last area not yet revolutionised by big data in terms of measurement optimisation. Now with computer-vision AI plus generative AI for new creative based on performance data, things are changing quickly.

If you talked to anyone working at a sports team in the 80s, 90s, or early 2000s, they had a stopwatch, a notepad, and a VHS tape. Interns would watch, stop, and write down here is when your banner was visible. Now you have virtual assets that change and animate. Computer-vision AI detects everything second-by-second.

The roots of sports marketing were the halo: the CEO wants to do it, that's the local team, I'm the biggest bank in this town, I need to be a part of that team. The local model was you're a pillar of the community, we should be together. There wasn't pressure to measure because that reasoning was enough. Now you have global sports and you hear about $400m World Cup packages. That's where the innovations around how to create the data to measure it are happening.

The Abu Dhabi Grand Prix was the most-watched in history. They were shooting the F1 movie during it. The agency was offered the chance to sponsor Brad Pitt's fake team in the movie. We tracked all the brands and exposures in the F1 movie and started looking at Drive to Survive the same way. The visibility and memory those brands are getting is striking. Gaming is the next layer (esports is up and down; gaming itself is huge for youth).

Logo slaps have always been there. Now there is much more layered sophistication. F1 fan zones at every Grand Prix where the brands and partners are part of the experience. F1's business is about creating the most sophisticated driving machine on earth, so the technology partners and their technology are being used by the engineering teams. NFL and Verizon: every NFL stadium is Verizon 5G, so your phone works there. It's part of the fan experience, part of team and sport development, part of the coaching, and full-cycle from the product through sponsored social-media content and short clips.

The vision is to create more opportunity for more athletes, more teams, more publishers, and more brands, so the global ecosystem of sport (based on competition, sports, and passion) keeps growing. For that to keep growing it needs accurate measurement, because without measurement you don't understand the financial incentives across each part of the ecosystem.

The technology (computer vision, data warehousing, generative AI for instant insights and automating functions) is the means to that vision. The vision isn't apply new cool technologies; the vision is give the global sport and entertainment ecosystem liquidity in the form of accurate measurement and data.

Faster data that's cheaper and easier for the team to use and monetise. With generative AI specifically, there's more policy and legal complication for large organisations bringing it in-house. As an outside provider in the cloud, we can measure on the customer's behalf; the customer interacts with the data from our platforms, so the technology poses no risk inside the customer's stack. When they're ready to create their own LLM or their own enterprise model, we'll be ready to interact with it. In the meantime, our infrastructure poses no risk.

For measurement and analytics companies, the end output has historically been a dashboard (graphs, charts, tables, filters). The billion-plus people using AI tools today aren't doing all that work to get an answer or an insight. The inference is the form: the system knows who you are and what you care about and finds the information for you. Automated insights. An agent that knows what to do on your behalf and talks to other agents to optimise.

This isn't years away. The biggest companies are rolling these tools out daily. Nvidia is a wonderful partner helping us accelerate the core AI work; we're developing on what they were ready to do two years ago. Measurement that isn't instantly usable and doesn't change something is just a number.

Different networks have different camera angles, different stadiums have other logos around. A creative that's crisp and highly visible in one broadcast might be washed out in another (the NBA's basket stanchion and pole pad permanent positions are a common case). For one former client we recommended shortening the brand name to a shorter version and changing the font colour and type. The visibility lifted by around 80%. That visibility drove more search data, more searches for the brand, and better brand recall. That's base case stuff.

The other layer: interesting social branded content. A brand, a team, and an athlete producing something specifically meant for social drives additional engagement. If the team isn't doing well this year and viewership is down, the values are down, and the team can still reach the loyal fan base through social. They may not be buying tickets as much, may not be tuning in at night, and they're still engaging. We have predictive numbers: this kind of content on TikTok versus Instagram versus Facebook versus X will produce this much value. That helps brands and teams shape the content marketing strategy.

Exposure values are a media equivalency: what it would have cost to buy the equivalent in 15 and 30-second ads. Usually a high number because sponsorship assets are visible for an entire three-hour broadcast plus the hour-long pre- and post-game shows.

Then the move toward CPM. We bring in actual viewership numbers: 42 million people watched. Divide the sponsorship media value by viewers and you have a CPM, which lets the work be compared like advertising.

Then search lift. Partnership with Captify to see whether sponsorship is driving increased searches, the intent in those searches, the language used, and the comparison to competitor baselines (so during the MLB playoffs you know how much you increased versus the competition).

Then outcomes. Partnerships with VideoAmp and Snowflake combine sponsorships, content, and ads by reach, unique reach, and cross-platform streaming versus linear. Then foot traffic, sales lift, increase in car sales. Retail data. Is it working? However granular a brand or a team wants to go, it's there. Some still don't care about the mid or lower funnel; that's changing fast.

The price tag continues to go up for sponsorship and media rights. There needs to be more accountability that can be reduced back to shareholders, otherwise goodwill alone on the balance sheet doesn't hold when you're spending billions a year. This is now serious capital investment. Private equity and other sophisticated institutional investors are owning or investing in more professional sports. Sport is now an asset class, like real estate or physical data-centre space, both of which are receiving hundreds of billions of dollars. Asset classes have specific ways to be measured, and that sophistication is coming to sport.

Milan-Cortina Winter Olympics in February. FIFA World Cup in the US, Canada, and Mexico in summer. Super Bowl. LA28 the year after. The typical annual tentpoles are getting bigger and combine with these mega-tentpoles. We'll really test the attention limits of fans and consumers; it's going to be an overload. World Cup sponsorships are already running in ad spots and outdoor in Manhattan ahead of a summer event. Multi-phased campaign rollouts. FIFA has some innovative things planned for during the games and fan-experience campaigns at all the different stadiums (we do in-venue measurement). All new stuff no one has seen.

The market is growing and splintering. The focus this year is understanding linear versus streaming. In the US, regional sports networks have moved sports rights to over-the-air broadcast networks in some markets. Fans ask where do I watch this game? The leagues themselves on their own apps (the NBA app tells me, as a Milwaukee Bucks fan, where every Bucks game is on and how to watch).

The new and emerging sports are bypassing the traditional media model and going straight to fans on Twitch and YouTube as their distribution partners. The Kings League is coming to the US with more investment. Soccer matches where dice are rolled to determine how many players play in the last two minutes before halftime; the pitch is voted on by fans; the creators and influencers with the biggest audiences share in the revenue. Groundbreaking. That will open the door for more new sports. Probably a small threat to the established ones, and better products come from more competition, and more demand for measurement comes with it. Music to my ears.

Computer vision scales. We build models, deploy in a new sport in a new market, test, reinforce. Cricket World Cup is breaking records. F1 continues to grow year over year, has the youngest core audience of any global sport (the average fan is around 35), and huge social-media engagement. The Premier League and La Liga matches are watched in around 90 countries every Saturday, in multiple global broadcasts. Localising sponsorship assets virtually into the regional feeds is happening at scale. US fans now watch Serie A, Ligue 1, the Premier League, and La Liga on cable and streaming. There's no boundary on which country a trend can come from. Incredible mass niches.

We recently launched in Japan, have been in Europe for five years, and are looking at partnerships for Latin America. In the US we're moving more towards outcomes; the FIFA World Cup is the impetus for that. Computer vision is the base; other forms of vision AI built on base computer-vision models are emerging; all of this will become agentic. The multi-year adoption curve means we want to be early into the market, learning and testing, because that will drive the liquidity (less friction to understand what works and to change it to work better).