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Relo: It’s Time to Take the Guesswork Out of Sports Marketing Measurement

It’s the time of year for predictions-focused articles, and it doesn’t take great foresight to state that most will center on artificial intelligence (AI) to do the job smarter and quicker, and/or analytics that confirm that sponsorship buys being made are wise investments.

With the rapid changes occurring in the sports marketing industry, those are the important topics to track. But with the accelerated development of new technologies as well as constantly shifting customer expectations rights holders, solution providers and marketers need to keep several steps ahead of trends or risk falling behind, perhaps permanently.

That’s exactly what’s happening to the sports sponsorship industry; until recently, it’s been falling behind in the modern era. The not-so-distant past could really be called the Stone Age of sponsorship measurement: agencies relied on interns using stopwatches, Excel sheets, and YouTube to assess performance. Reporting cadence far behind game results, typically being served to clients far beyond the point where they could make alterations in placement or, more likely after the season was over. With many valuation metrics varying widely, the quality of this measurement overall has been called into question for its accuracy. 

So how can this be fixed? What are tangible steps to get scaled and accurate data into the hands of decision-makers while they can still impact their assets? What is the future of being able to make decisions based on this data in the age of generative AI?

Traditionally, in the sports marketing realm, whether on the creative, buy side or sell side, there hasn’t been a strong legacy of planning to validate trying new activations like a new digitally inserted, geo-targeted sponsorship assets or an in-game media buy, followed by a social media boost effort. Instead of having a credible reason for doing something, it’s been more driven on past behaviors and gut instinct. The fragmentation of viewership and expansion of major sports into international markets makes that method no longer feasible. 

With the continued shift from traditional broadcast viewership to more streaming, and digital content viewing experiences and the rise in programmatic advertising, our industry had to modernize measurement as well, focusing on the convergence of technology, data-driven software, and media assets to create a self-sustainable ecosystem that can lay the foundation for the future of sports currency.

And to be clear, sports is the critical link to the ongoing health of this delicate ecosystem. It’s the driving force that’s keeping broadcast alive, and it will remain at the center of the fight for streaming subscriptions. The question we are all wrestling with is how to accurately capture the entire value of sports sponsorships within what is widely estimated to be a $135 billion market by 2029. Even the actual number is hard to pin down since there are so many evolving market dynamics.

The market is global, and the investments on both sides—from media rights holders, leagues, and teams to brands and associated agencies—need to get a real-time handle on campaign performance during each and every game, and also optimize performance with creative and using audience targeting data The sports market hasn’t jumped in all the way, and it’s now imperative to capture the demand that is possible.

Relo

One successful approach is to build creative asset-level classification models for every sport and then use computer vision to analyze video and stream frames that capture these potential logo-heavy target areas. The Relo system, for example, analyzes each game in three-second by three-second video snippets, producing data that includes factors like number of exposures, duration of exposure, clarity of exposure, and share a voice of exposure.

Computer vision with machine learning training models that learn and improve themselves, allows all parties a credible, accurate and third-party valuation. Through years of work, we’ve been able to create a quality assurance system drives validation model accuracy into the 95% range.

So once you have logo placement duration, clarity, and the number of exposures, you have to bring in other data inputs and then run your algorithms for calculating the value. One of the largest market gaps historically has been the lack of census-level datasets. Now that is changing.

New datasets can allow sponsors to not only gauge the effectiveness of their in-venue investments but also benchmark their performance against other brands in their sport as well as across other sports in near-real time. Are sponsorship dollars better spent on a different sport, a different team, or a different position in a stadium or arena? We now have tools that can help make those decisions in real time, vs. the end of the season.

The Future: Getting There from Here

And for the future? It really isn’t that far.

We see a world where an interconnected system of data and AI-driven software can analyze all major sports on broadcast, cable, regional sports networks (RSNs), streaming platforms, across all of social media, and allow the sports business ecosystem to drill down into census-level data to determine ROI for their investments. Steps have also been taken to track visibility in arenas during in-venue activations, which is regularly seen on social as well as through new, team-centric streaming platforms as rights holders seek to increase club valuations.

This sports marketing vision unlocks the full financial opportunity and drive the creation of a new sports sponsorship currency, much like we’ve seen take its first steps in the digital advertising space.

We are in the middle stages in the maturation of this all. We’re coming out of the commoditized phase into the What is really going to matter for the next five years phase. No one wants to ever be in the part of a market that is shrinking per se, but if I look into my crystal ball, I believe that the media landscape will continue to fragment. There’s only going to be a handful of traditional media companies left standing, and they’re all going to need sports to stay alive, and they’re going to be under even more pressure to sell high-value, long-term brand partnerships.

There’s a limit to how much you can pay for a 30-second spot before it’s a diminishing return. In-venue sponsorships and integrations that are on camera for hours instead of seconds simply provide more ongoing awareness among viewers and will be key to mindshare during social sharing of the game.

It will require a third party to measure sponsorship valuation, and the market is ripe for a solution that does the job smarter and quicker and analytics that confirm that sponsorship buys are wise investments. We believe that as sponsorship continues to grow and audiences turn off spots that are oversaturating game coverage, successful new uses of data sets and technology can deliver winning combinations to leagues, teams, and brands.

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Jay Prasad

Jay Prasad is CEO of Relo Metrics, the leading AI-powered sponsorship analytics platform for real-time data decisions, and Relo Census, the first sports sponsorship valuation data set and methodology offering broadcast and social media sponsor valuation for all assets and brands of all games in the NFL, MLB, NBA, NHL, and MLS.

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