Fans have enthusiastically embraced the return of live sports, with a pandemic-influenced twist. Digital habits, intensified by stay-at-home orders, look set to stick as audiences increase their diet of online media, alongside broadcast TV. All of which is great news for content distributors, but what does it mean for marketers aiming to get back in the sports advertising game and adjust to the digital media renaissance of anytime, anywhere consumption?
Opportunities to engage large sporting audiences via streaming platforms are growing fast. Last year, viewing figures for live highlights of England’s four-test series against India reached 2 million on All 4 — marking the platform’s biggest ever week. The BBC also saw a record-breaking 100 million online viewing requests during the Tokyo Olympic Games — up from 68.3 million for Rio 2016 — while at a wider level, studies show 73% of UK fans would be happy to only view streamed sports. In just a few weeks, live coverage of the upcoming Beijing Winter Olympics will be delivered across an array of broadcast and online channels, including Sky, Eurosport, BBC iPlayer, NBCUniversal and its own streaming platform, Peacock.
Yet complexity has developed too. Live sports always had both positives and pitfalls, including broadcast TV’s scope for instant mass reach and difficulty achieving precise measurement across ever-changing ad slots. Now, the move to streaming has introduced new challenges and opportunities; less capacity for these large scale ‘reach moments’, but also substantially improved audience segmentation and message variation potential.
Making the most of soaring streaming adoption is going to mean taking a smarter approach to ensure ads can adjust to unpredictable play and ad breaks.
Keeping up with shifting goalposts
Marketers have heard plenty of advice about the need for nimbler tactics amid COVID-19, with events delayed by restrictions and subject to last-minute cancellations. For many, efforts have centred around increasing scatter market spend for performance campaigns to buy ad space nearer to programming, rather than via traditional upfronts. But pandemic pressures have also seen some switch attention from content context to focus more on who ads reach.
This shift has tallied with rising diversification of TV activity, enabled in large part by ongoing CTV evolution — including greater focus on performance-based advertising, as well as brand building campaigns and lower funnel tactics aimed at driving results across online video and social. As increased engagement with digital content and live streams has delivered better audience insight, TV’s addressable capabilities have grown, opening up opportunities for advertisers to not only reach more refined viewer segments, but also select media placements with the highest likelihood of hitting specific KPIs. In the face of pandemic budget pressures, the scope this varied approach offers for higher ROAS, and overall efficiency, has made it particularly appealing.
The problem, however, is that audience targeting goalposts are continuously shifting. As well as the common issue of unscheduled break patterns, OTT streams often experience sudden spikes at unpredictable times, and from a diverse set of viewers. Consequently, even the most carefully laid data-based targeting plans can go awry if the makeup of fans streaming particular events changes unexpectedly on the day.
Bringing more flexibility to ad schedules
Controlling live action isn’t feasible, but there is room to bolster advertising adaptability by improving coordination between systems. Conventional broadcaster approaches to linear OTT scheduling and ad break implementation have long provided little flexibility — making it difficult to achieve synchronisation with programmatic mechanisms. This limits scope for the dynamic ad decisioning and serving needed to stay aligned with unfolding sports events.
Technological innovations, however, are opening up ways to overcome efficiency barriers. For instance, the Smart TV booking APIs are enabling broadcasters to automatically import schedules into ad platforms without changing intricate workflows, allowing them to identify which slots are adjustable and increase availability of addressable inventory. Combined with predictive modelling developments, these advances are poised to fuel a major leap forward in ad break management that will bring enhanced guarantees in terms of delivery and yield.
Using newly accessible scheduling data, artificial intelligence and machine learning (AI + ML) tools can leverage historic information to make accurate predictions about key factors for specific sports events, including audience size and composition. This insight paves the way, not only for pre-selection and purchasing of media — similar to upfronts — but also more efficient programmatic buying and targeting.
Where is dynamic delivery headed?
For marketers, the main upshot is the expanded opportunities for data-powered live campaigns. But, in particular, it will be worth watching out for two options: single and multiple advertiser slot optimisation (SASO and MASO).
Also known as creative versioning, SASO (Single Advertiser Spot Optimization) will allow buyers to replace one ad with another in the same slot. Tapping individual and household-level data, they can match ads for better relevance. Meanwhile, MASO (Multiple Advertiser Spot Optimization) primarily benefits sellers — enabling them to swap in creative from varied buyers in line with what suits their current audience — but it also stands to benefit buyers by increasing capacity for open real-time bidding on specific ad space.
With events only recently recovering from 2020’s hiatus, we’re just now seeing the full effects of digital-first engagement on sports. The evolved live event advertising landscape offers huge reach across self-selected – and potentially even more valuable – audiences, as well as granular audience activation and targeting. There are certainly plenty of reasons to get back in the game, and the marketers and broadcasters who move fastest will take pole position.