Sports sponsorship has changed. Once upon a time, the focus fell on exposure gained in-venue and through broadcast but the dawn and rapid expansion of digital channels over the last decade has shifted the landscape considerably.
Now website visits, app downloads, social media following and engagement, and a whole range of other metrics all contribute to the value rights owners and brands generate through sponsorship. The celebrity-driven success of Wrexham underlines how drastically the game has changed.
As sponsorship has evolved so too has the nature of activations and the methods required to measure them. Getting a clear view of sponsorship impact in this complex, multi-touchpoint landscape is difficult but possible thanks to sponsorship analytics.
What is sponsorship analytics?
As the name suggests, sponsorship analytics is a methodology that helps rights owners and sponsoring brands understand the impact of partnerships, both in terms of raw visibility and monetary value.
Using data analysis and modeling techniques, it brings together a wide range of metrics from multiple touchpoints, for example: video views, impressions, shares and likes across social media, as well as viewership across traditional TV coverage and streaming platforms.
This provides an understanding of exposure, but not all exposure is equal. Time on screen and the size and clarity of an asset are all important too. The longer an asset is visible, the more prominent it is, and the clearer the creative is the more likely it is to make a lasting impact on the watching audience and deliver what truly matters: potential value.
For example, an MLB team may hit a dramatic late home run in a big match. The game is viewed by a large audience on traditional TV and streaming, and the team’s jersey patch sponsor is seen clearly. It’s great exposure for the sponsoring brand.
But the story doesn’t end there. The big moment is clipped by the broadcaster, the league and the team, and posted across Instagram, Facebook, Twitter and TikTok. Every like, share and comment on each platform adds further exposure and so greater value.
And it goes further. Sports news sites and blogs feature photos of the moment, the static imagery providing an even clearer view of the jersey patch and so even more exposure and value for the brand. Again, further shares mean greater value.
Traditional thinking would struggle to capture this web of exposure, but sponsorship analytics platforms have everything they need to capture holistic numbers and deliver an accurate picture of performance.
How does sponsorship analytics help?
Sponsorship analytics helps rights owners and sponsors build better partnerships in a number of ways. Here’s how:
Set and measure against realistic KPIs
Some brands can be discouraged from getting involved in sport sponsorships. Without clear and accurate results to back up decision-making and demonstrate performance, the area has been easily labeled a risk by brands with a keen eye on ROI.
But sponsorship analytics firms up the landscape at every stage. Brands and rights owners can work together to share reliable and holistic data, understand what it means, and arrive at meaningful and – above all – accurate valuations for sponsorship packages.
In turn, this allows both parties to enter into a more transparent, trusting partnership and agree on realistic KPIs. So, when they’re looking at performance, they’re well placed to measure success.
Sponsorship is no longer measured by finger-in-the-air estimates, but the rich, reliable data needed to make smart decisions.
Analyse and optimise quickly
Under the old model of sports sponsorship measurement, brands would have to wait until the end of a season or tournament to understand performance.
This may have worked back then, but the fast-paced landscape that digital media has created has upended the dynamic. It’s simply not good enough to wait; delays mean mistakes can’t be fixed, opportunities can’t be seized and value is left unrealised.
Sponsorship analytics opens up the opportunity to review activations rapidly: days after each game, for example, rather than after a whole season. In doing so, brands can understand if their placement is working out or their creative is striking enough and adapt accordingly before it’s too late.
Look at the MLB’s introduction of jersey patches this season as an example. In under 24 hours after the opening games, we were able to analyse results, deliver reliable data and identify actionable insights.
Armed with this intel, rights owners and teams can inform activation through the rest of the season and make sure they’re getting as much out of the partnership as possible.
Unlock unrealised value
Sponsorship analytics doesn’t just help with measuring deals that are already in place, but understanding deals that could be struck in the future for activation areas that are currently going unmonetised.
This process is called ‘whitespace analysis’. Sponsorship analytics companies explore areas that could be rich in potential, and provide estimates for the visibility and value that area could deliver if it’s properly activated.
A soccer team, for example, may notice that the area behind the manager and coaches in a dug-out is being picked up by cameras and therefore represents an opportunity. Sponsorship analytics can be used to properly assess this opportunity and give the club reliable guidance on valuation.
The result? Like everything else we’ve discussed in this post: better deals, better activations, and – most importantly – better value across the board.
Learn more about sponsorship analytics and understand how DataPOWA can help you in your activations by emailing us at [email protected]