Did Social Media Affect the Super Bowl Outcome?

In an age where machines are now learning how to engage in group activities and take over and automation being applied to industries once manned by humans, there lies an interesting intersection of reality and projections. Fake news and alternative facts have become a matter of great concern and a cause for anxiety among brand marketers about where their ads appear. This concern lingered throughout the Super Bowl, the biggest and most talked about event of the year for Americans.

Data “listening” and tracking company Taykey analyzed data and conversations around the Super Bowl and gleaned several insights. Some results were more surprising than others but given the latest debates around online influence and persuasion a couple points stuck out particularly with how others engaged with sharing data online during the Super Bowl.

Being Talked About Is Better Than Not

There’s a circle of debate around the power of “noise” and some conspiracy theorists that believe being talked about in general is better than not. Budweiser stumbled across some luck with its Super Bowl commercial with an immigrant themed trailer; the timeliness of it couldn’t have been better planned given the current political sentiment in the United States as its own immigration policies change directions per its new administration and president. The video itself was produced and filmed nearly six months before the Super Bowl so the topic may have been pure luck. Whether or not there was data involved in Budweiser’s strategy, Taykay was able to run the following numbers around the conversation of Budweiser’s Super Bowl commercial.

Fans and Politics

Interestingly enough, data around sports fans is also helping identify who sports fan are, and what they relate to philosophically speaking. For instance, Falcons fans were less likely to tweet or speak negatively about Donald Trump and almost 3x as likely to say something positive about him when Patriots fans were generally Negative with social engagement and with a 75% chance of their Trump conversations likely to be negative or neutral. This is interesting because it means there is often a solidified correlation between a brand or political stance, and another brand or political stance, meaning if you sided with one set of brand or politics the likeliness of others of that same view would view other things the same as you. For marketers and politicians this means you may be able to use data to hone in on certain fans of certain sports or topics, versus trying to find that fan base from current followers or supporters.

Gender and Brand Engagement

Mr. Clean this year somehow became “Mr. Sexy” engaging much of women online. Mr. Clean made his “sexy” debut in a hilarious yet quirky cleaning commercial which generated a whopping 77% positive online sentiment across both genders. Since data points to millennial women talking more about the Super Bowl ads and performances than they did about the game itself, Mr. Clean might have been the overall attention grabber of the night.

Mr. Clean shows his sexy and likeable skills across both genders:

The Momentum of ‘Winning’

Similar to when machines are put in a simulation of game playing, when a certain player is winning or senses a path to “winning” the machine will pick up momentum until it comes out on top. Data says the same about humans even related to sports. Team fans where the team was winning were more likely to be vocal online:

All this data seems cute and interesting, but when you think about what companies like Taykey and others are providing the value of what people are saying and why becomes immensely powerful. You can end up knowing exact data outcomes of communications which sometimes influence an outcome. You have to wonder what is a simulation and what isn’t? Do projections affect outcomes or are outcomes the results of projections? Are we examining data of something we are projecting and becoming, or can we use data and change the momentum of paths that we are on?

While Facebook begins to test sounds and sending audio related communications* are we going to simulate what we want or simulate what we don’t want? And who’s simulating what and who will come out on top? Since winning teams tend to be more active, and team support does increase with social media sharing, its possible too fans projections became reality so maybe social media affected the Super Bowl outcome more than we thought.

*link formerly available online

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