Superbowl Ads and Social Data: Where’s the End Zone?

585061_85722682Let me preface this  by admitting that I’m not an American football fan. Sorry. But I do love the window-dressing of the Superbowl: the inane commentary, the screams of joy and agony from the living room (and neighboring houses), the lame excuse to eat fried food and stuff wrapped in bacon, the over-the-top ads. And what goes better with fried food and extended primal screams than cold, bubbly beverages, whether of the alcoholic or non-alcoholic variety? Apparently nothing, if this data (supplied by Brandwatch) is any indication. (NB: If you’re just looking to see who won on the conversation volume front during the game itself, you can stop reading in 3, 2, 1…)

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But when you dig in a bit, you can see that there was very little momentum from that social conversation once the game ended: it went…flat. Unless you’re Coca-Cola…

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…in which case you also had to contend with the highest negative sentiment in terms of pure volume. So, aside from the obvious rout on conversation volume, and the high amount of negative feedback about the Coca-Cola ad, who would you say are the winners and losers here?

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My answer: it depends. I’m sure the folks at Budweiser are thrilled to have dominated the conversation during the game. I’m not so sure they would have expected that conversation to extend past the final seconds of play. Awareness and brand preference, pure and simple.

I’d like to think that The Coca-Cola Company, which is firmly defending its ad (along with many others) might be happy to have reached a segment of Americans who it might otherwise be at risk of losing based on health concerns. But let’s take a look at some of the other contenders on the sentiment front.

Screen Shot 2014-02-03 at 2.51.34 PMWhile AdAge ranked Radio Shack’s ad the top of the pack from a creative standpoint, the people’s choice was T-Mobile. And it was Axe, not Coca-Cola, that led in negative sentiment as a percentage of total volume.

Bottom line: does any of this matter? The truth is, we’d need a whole lot of proprietary data to know that for sure. But here are some questions I’d ask:

  • What was Budweiser’s conversation volume last year? Is this higher or lower? Do they care that conversation dropped off after the game, or were they hoping for a longer tail?
  • Was Coca-Cola surprised by negative reations to their ad? After all, they did make the classic “I’d Like to Teach the World to Sing” commercial back in 1971, which in many ways is internally consistent with the current one.
  • Does–or should–Axe care that its ad offended a whole bunch of people? If we could drill into the demographics, I’d look for correlation between age, gender and sentiment. Middle-aged mothers of four are not too relevant to this segment, unless Junior isn’t old enough yet to buy his own body spray. Did Axe simply do a brilliant job of speaking to its audience, damn the consequences?
  • How’s Chobani’s creative team doing today? Are they feeling whomped by Dannon/Oikos, or did their results correlate decently with expectations based on creative budget and ad spend?
  • What about the middle-of-the-pack brands? What were their goals and how will they evaluate their performance? Was it too much to be drowned out by puppies, Clydesdales and David Beckham’s abs, or was it worth it for an–abeit brief–shot at reaching such a huge audience?
  • Finally, as Ken Wheaton asks in his Budweiser review, “Has a Clydesdale ad ever sold a single Budweiser?” I don’t know, and I don’t know if Budweiser knows either. That is an awfully long (and interrupted) chain of causation. In the end, does it matter?

This is what makes The Advertising Superbowl so different from The Football Superbowl: in football, you know where the end zone is. It’s always in exactly the same place and you pretty much know when you get there. But the end zone in advertising is a moving target, and sometimes you don’t know whether you reached it–if ever–until many months later.

About susanetlinger

Industry Analyst at Altimeter Group
This entry was posted in Analytics, Big Data, Real-Time Enterprise, Sentiment Analysis, Social Analytics, Social Data, Social media, Social media measurement, Uncategorized. Bookmark the permalink.

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