Advertisers know that sporting events present some of the best times to get in front of a massive audience. And you and I, as those viewers, expect to be “wowed” with new and exciting creatives that we can talk about at work the next day – c’mon, how long was “Whassup?” part of your vocabulary?
But for an advertiser the only thing that really matters is the impact a spot had. Did it drive sales, search, site visits, registrations, foot traffic? When Super Bowl ads run between $4-5M a pop, and even the Olympics, while considerably less expensive, command $100K+, advertisers are under pressure to prove that spots drive revenue.
With the rise of digital and the age of active-participation viewers – those second-screening when watching TV – advertisers are thinking differently about TV as a marketing channel. Thanks to new analytics platforms, savvy advertisers are no longer just blasting out spots and hoping they’ll drive engagement. Rather, they are taking advantage of TV’s wide reach, but incorporating a level of precision to target the right people, in the places and times they are most likely to respond.
So how does this relate to advertising during sporting events? Well, with timely data analysis, advertisers measure the impact of TV spots on KPIs – whether that is site visits, registrations, charity donations, sign-ups, etc. – and identify not only the games, but even the times within those games, that drive the greatest response.
For example, we looked at UK search traffic for Betway and Bet365 during the England vs. Slovakia match from this summer’s Euros tournament. Spots ran at the times they would drive the most response: before the event started and at halftime. Not coincidentally, those are the times that people are most likely to place bets. Both companies saw measurable uplift in online traffic corresponding with their TV ads, which ran shortly before the start and at halftime, respectively.
This type of analysis can be generated immediately after a spot airs, which is a big deal for advertisers. They can measure the immediate impact of spots, and not just online, but SMS, mobile, call centers, retail sales, app activity and more. They can understand the networks, days, times and programs generating response and improve the efficiency of underperforming spots while they’re on-air. The impact for TV advertising, a $180 billion global industry, is huge!
Now to the fun stuff. Who were the biggest ad winners for two of the U.S.’s most high-profile sporting events this year: Super Bowl 50 and the Rio Olympics.
Super Bowl 50
The chart above shows the brands that had the largest increase in search traffic, corresponding with TV spots during the Super Bowl.
Amazon Echo had the biggest increase in search traffic in New York, Chicago and Charlotte. Budweiser – a Super Bowl ad staple – took Denver, Los Angeles and Seattle. And Fitbit emerged as the winner in Dallas-Ft. Worth.
Rio Opening Ceremonies
While the Super Bowl is a four-hour block, the Olympics is a 14-day event, so showing immediate impact can be harder. An advertiser might see a carryover effect from a spot, with viewers visiting a site or making a purchase influenced by TV in the days or weeks after initial exposure.
That’s not to say there weren’t ad winners. During the opening ceremony, Chobani saw the most web traffic in New York, Miami, Chicago and Los Angeles. In fact, it pretty much dominated U.S. search traffic compared to other advertisers and sponsors. Samsung won response in Houston, as did Coca-Cola in Seattle.
Advertisers that make the biggest impact during sporting events – and across TV – typically leverage data analytics technology and follow similar best practices:
They plan based on response, not ratings. Major sporting events attract a lot of viewers, but that doesn’t mean that this untargeted, mass audience will engage with a brand. Ratings data tells advertisers nothing about campaign performance. Rather, advertisers analyze spot and response data to plan TV based on efficiency and performance – the actions generated from an ad. Analytics identify the creatives, games (and the times within those games) that result in the most response via web, call centers, search, app activity, SMS, retail sales, etc. For example, the Super Bowl brought you 114 million viewers, but data might show that Game 2 of the NBA Finals drew 3xs the amount of response to a certain spot.
They make changes in-flight. A growing number of advertisers are leveraging more flexible buying opportunities to make day, daypart, network and creative changes to improve the efficiency of on-air spots – especially during multi-day/week sporting events. During the Olympics, same-day spot and response analysis could show an advertiser that swimming events aired between 2:00 p.m.-4:00 p.m. on CNBC drive the greatest response. They can then make day-of changes to improve spot effectiveness.
They inform media-mix strategies. Advertisers leverage data analysis to understand how TV influences other online and offline channels, like digital, radio and print. Some even conduct “what if” scenarios to test mix changes leading up to an event to ensure effectiveness. This is especially important in the age of the connected consumer – when some 57% of viewers second-screen when watching TV and, if interested, immediately engage with a brand.
So what does all this mean for advertisers wanting to get the biggest bang for their TV buck during sporting events? The answer is to let the data guide you and not make assumptions. After all, with all that budget at stake why guess if you don’t have to?
About the Author
Kevin O'Reilly, CTO at TVSquared
For more than 15 years, Kevin has been helping companies navigate the path from data and analytics to insight and strategy. As CTO at TVSquared, Kevin brings his skills in coding, modeling, team building and leadership to ensure the company continues to provide the industry’s most accurate, same-day TV measurement and optimization technology.
Previously, Kevin was the vice president of marketing sciences at TWO NIL, a media-marketing and advertising agency. While there, he led a team of senior analysts and marketing scientists to build advanced optimization and marketing-mix models for measurable and effective TV and digital media investment strategies. Kevin has also acted as a private consultant for social media, online gaming and electronic retail companies, helping them leverage data to optimize marketing programs.
Additionally, Kevin has held analytical leadership positions at MediaBrands (Spring Creek Group), Expedia and T-Mobile.
Based in Los Angeles, Kevin can be found jogging (slowly) between Venice and Santa Monica and, occasionally, kayaking or sailing on the Pacific.