For those brands willing and able to pay the $5 million price tag, the Super Bowl will marry Americans’ love for football and creative advertising. Of course, the playoffs and championship games always spell big money for the NFL, teams and athletes. But scoring touchdowns and having a winning season aren’t the only way to drive revenue.
Applying advanced analytical techniques to better engage fans throughout the season is proving to be a key driver in a successful season, regardless of your win-loss record.
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For many pro sports franchises, analytics means more than Moneyball. Many teams have been using analytics to better understand fan preferences and behaviors. This same type of insight can also enable teams to attract and retain highly recognized – and deep-pocketed – brands.
A recent PwC Sports Outlook report pegs 2013 brand sponsorships at nearly $14 billion in just North America. By 2018, expect that figure to climb to $17.5 billion. The NFL alone commands a cool $1.5 billion in sponsorship annually. Teams that linger in the middle of the pack need evidence that their organizations should command top dollar for sponsorships.
A panoramic fan view
Each fan has a distinct personality. Let’s take season ticket holders, for example. It’s not just Team A vs. Team B or New York vs. Boston. The Team A fan may be a 26-year-old finance professional whose loyalty is a generational tradition. The Team B fan could be a 43-year-old mother of two who learned the game from her kids’ Pop Warner days and preaches it like a convert.
A savvy sales team enters a meeting with a potential sponsor armed with deep knowledge about both. With data backing up their pitch, the team can make a clear case that the sponsor will find their desired demo right in the stands – or watching on the small screen.
For both team and sponsor, this is no guessing game. The fan profile draws from multiple sources – from concession or merchandise purchases at the stadium to social media channels and online shopping habits. This data drives predictive analytics that might result in texting Fan A a high-performance sportswear ad, or posting a pizza chain offer on Fan B’s Facebook page.
Accurately understanding each fan also helps football teams to a bigger piece of the $1.5 billion sponsorship pie. Investing in technology that can store pertinent data centrally and analyze it to create the panoramic fan profile is where teams are headed. And not just the NFL – advanced analytics are bringing big dollars into soccer, hockey, basketball and other sports leagues across the spectrum.
A brand blitz
The fan profile unlocks unique opportunities for brands to connect with their target demographics, reaching far beyond online advertising or in-stadium signage. With Fan B in mind, the team could partner with the pizza restaurant brand to host a pre-game event where her kids meet the mascot. Or Fan A could see his tickets upgraded for a key matchup against a division rival, courtesy of that high-performance sportswear’s sponsorship.
A unique, memorable experience is worth premium dollars to brand partners, because it secures greater fan loyalty. So rather than blanketing all season ticket holders with a meet-the-mascot offer, the fan profile limits the target to those most likely to respond.
Beyond matching the fan to the right marketing tactic, analytics also accurately tracks a sponsor’s ROI. Sophisticated brand partners know their demographics just as well – or better – than the team does. They will expect reports that include much more than ad impressions or ticket counts. Advanced analytics offer brands insight into what’s really resonating, with robust, relevant reporting that lets them slice the data however they like.
Showing the pizza restaurant brand the data behind the marketing – from the number of campaigns, a tally of click-throughs, total offer redemptions and more – helps them hone and optimize their campaigns as well.
Better data translates to ROI for brand sponsors, increased revenues for teams, and a more personal fan experience. Together, it’s a touchdown for the industry.
Jim Tobin (@jimtobin) leads the Sports Industry Practice at analytics software giant SAS. He is responsible for developing relationships with professional sports teams, leagues and venues that use analytics for everything from how to improve fan engagement and build sponsorships to making better draft picks and predicting injuries. Prior to SAS, Tobin held positions at software and IT services firms including SAP, B4 Consulting, TheNextRound, IBM and Lotus Development Corp. He’s is an avid sports fan, youth sports coach and Ironman finisher.