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It’s time for media valuations to go beyond the broadcast

In sports, sponsorships are all over the place. Digital rotational signs appear behind home plate in MLB stadiums, logos cover the basket stanchions during NBA games, brands line dasherboards in the NHL, and sponsors pay for prime billing on scoreboards and video boards in the NFL.

Millions of fans get exposed to brands when they watch their favorite teams play on television, but how do we measure the true ROI of these sponsorships now that the internet is such a big part of how people consume sports media?

The global sponsorship market surpassed $60 billion at the end of 2016. With so much on the line, brands need to have an accurate model in place to monitor the total value of their commercial deals. But with technology evolving so quickly, that can be a complicated challenge. With sports and event consumption shifting away from linear TV broadcast, there is tremendous potential in sports media evaluation for sponsors, teams and rights holders to capture the impact of social media, digital exposure and engagement. As digital sponsor media value begins to rival and ultimately surpass that of broadcast, teams and sponsors must ensure they are equipped to measure and optimize digital sponsor media value.

Think of how fractured sports media has become. We don’t just watch games on TV anymore. Twitter live streams NFL games, Yahoo hosts streams for different sports throughout the year, and ESPN is currently developing a premium over-the-top content service. Brands may still be paying for exposure on TV broadcasts, but their logos and ads will increasingly have more impact online. Understanding that value is one of the most important things marketers can do moving forward.

Social sharing is a huge part of this playing field as well. Whenever someone tweets a photo from a game or posts an image to Facebook, there’s a good chance a sponsors’ logo will appear in the background. Depending on how influential the user, or how crucial the moment, one photo or video of a big highlight could drive a tremendous amount of value for a brand.

State Farm’s logo became a part of NBA Finals history when LeBron James’ block helped secure the championship for the Cavs.

In the 2016 NBA Finals, for example, superstar LeBron James made an incredible block that saved his team’s season. Naturally, the replay spread all over social media and was shown nonstop on TV for weeks, not to mention YouTube. And every time the clip was played, aired or shared on social media, State Farm’s logo was right there behind the basket and is forever connected to this iconic moment in NBA Finals history.

This new reality of branding in the digital age means marketers need sophisticated measurement if they’re going to invest in large-scale, media-facing sponsorships. Of course, getting to this point isn’t easy. On social media, most sports posts with sponsor value contain no textual mention of the brand, which makes sense because the initial focus is on the sport, not the logo. Couple this with the sheer number of social media exposures out there, which have proliferated in large part due to advances in technology such as camera phones, faster mobile networks and social media. Staying on top of these hordes of exposures, whether or not they have any identifying text, requires a technology solution. The good news is that there is one.

Thanks to advancements in artificial intelligence — specifically, computer vision or image recognition — the measurement technology is available to finally address the challenge of today’s fragmented sponsor visibility. Until now, most tools only monitor brand mentions from team-owned social media channels. Image recognition technology, however, can see beyond team-owned social media channels by looking inside images and videos for sponsor logos and finding relevant posts even if there is no brand mention. This kind of scalable automation further helps both brands and rights holders track online engagement, with tools that are robust enough to handle it.

For the most part, companies have focused on one medium — either TV or online — but computer vision technology increasingly provides opportunities to develop tech that can identify impact on TV and digital media simultaneously.

For example, at GumGum, we used image recognition technology to look for the Geico brand in Major League Baseball posts to gauge sponsor value, including video clips from the TV broadcast that were shared or used online. The technology looked in pictures not only for Geico’s logo but also for its location on the field. We found that 59 percent of Twitter posts came from outfield shots while only 41 percent featured signage behind the plate. This level of detail helps brands maximize signage placement, develop a thorough understanding of value, and ultimately justify large sponsorship spends.

EMarketer projected that 5.5 million people would stop paying for cable TV in 2016. This year, that number will jump to 6.4 million. If fans continue to watch and react to sports in different ways, then the way brands and rights holders negotiate to reach those fans needs to adapt as well. It’s clear that the traditional game plan for brand exposure is changing, and as a result, it’s time for everyone involved to think beyond the broadcast.

Jeff Katz is vice president of business development for GumGum.

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