Sponsorships Get Performance-Based Makeover

  • by , Op-Ed Contributor, October 1, 2018

For an industry that lives and dies on performance, live sports are late to the game when it comes to metrics that reflect the performance of brands’ sponsorships.

Players know their compensation is based on their performance. Sports franchises know their teams’ performance influences in-person attendance and TV viewership. And brands know that with increased player and team performance comes increased sponsorship costs. But how can brands tell if all of this good performance is translating into value for them?

Brands have traditionally made sponsorship decisions based on where their logos will get the most on-camera visibility. They consider factors like a team’s popularity, its high-profile players, in-person attendance and live TV viewership.

This no longer fully reflects how TV events are consumed. Viewers still watch sports during live broadcasts and in-stadium, but just as many watch on their own time through social media and other digital channels.



Sponsors’ expectations have also evolved. They’ve become accustomed to digital metrics that don’t just track views and impressions (awareness), but also track the actions taken as a result of awareness (attribution).

This is the long way of saying that sponsorship metrics need a performance makeover.

To provide value and relevance to brands, they must accomplish three things: 1) Allow brands to make buying decisions and incentivize based directly on the properties’ performance. 2) Take into consideration both in-game and out-of-game exposure across digital, offline and traditional TV channels. And 3) understand what actions viewers took as a result of exposure to sponsorships.

1. Whose performance should be incentivized?

Anheuser-Busch InBev recently took matters into its own hands by introducing its own incentive-based sponsorship model. The beverage company is now working with team and league partners to reimagine its payment model. Instead of a flat sponsorship fee, it has begun paying a base compensation plus incentives for good performance by the team—and, by association, the sponsorship itself.

For instance, making the playoffs or attracting increased attendance could trigger increased sponsor dollars for a team.

This model gets closer to rewarding direct impact on the brand but is still rewarding awareness rather than direct brand KPIs. That’s because it’s based, at least partially, on traditional thinking: good performance by teams and players leads to more exposure.

A more direct approach would be to implement a measurement model that rewards the performance of the sponsorship itself by tracking and correlating key factors related to a viewer’s screen: a logo’s persistency (length of time on screen), and its size and position on screen, across all in-game and out-of-game appearances.

2. How do you measure the full scope of sponsorship performance?

Sponsorship measurement currently focuses on in-stadium activation while only beginning to scratch the surface of TV and social audience measurement.

Today’s sports fans leverage multiple devices across multiple channels and platforms (sometimes simultaneously) while spectating at home. This dynamic viewing environment requires a holistic measurement model to best understand how TV, digital and social relate and influence one another.

Finally, out-of-game sponsorship appearances are rarely, if ever, included in performance metrics. Given the number of replays, rebroadcasts, highlight reels and post-game shows around any major league sport, brands are missing half the story.

3. What will success look like?

For athletes, success is pretty black and white. For advertisers, it’s always been about awareness, but only because awareness leads to action, which TV advertisers haven’t traditionally been able to measure.

As TV continues retroactively adopting and applying digital-like metrics, however, brands are getting closer than ever to attributing TV exposure to specific viewer actions, such as sales or direct engagement.

The ideal scenario is for advertisers to be able to start, not end, with the question, “How many times did my target audience see my logo?” The natural follow-up questions they should be able to ask are: “What did viewers do next: visit a nearby store? Go to our website? Follow us on social? Buy something?”

Understanding TV viewers at this level of granularity is far more difficult than understanding their digital counterparts, but TV data providers have already made it a reality  —  one that should only keep getting better.

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