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I’ve got a thousand sound bites about Super Bowl advertising: It’s basically selfies for brands. It’s the opposite of 1:1 marketing. It’s a cross-category free-for-all, growing in risk rather than opportunity given its price tag.
$5M is a lot of money by any standards, even more so when it’s for 30 seconds of airtime on broadcast TV. Who can forget Super Bowl XXXIV way back in 2000 when E*Trade’s dancing monkey seemingly wasted $2M?
There are a lot of ways to evaluate that investment. Here’s one you maybe haven’t considered:
With the proper machine learning horsepower, it’s possible to discern singular affinities between groups of people based on their online commentary. We use the technique in our Data Design practice among other things to match brands to sponsorship opportunities with specific eSports games, teams, tournament locations, etc. We also use it in combination with other types of analyses to optimize email content, CRM programming and to build look-alike audiences.
A Super Bowl analysis done this way would reveal among other things whether your spot connected with your baseline engaged consumers, what kind of consumers engaged with your spot and depending on what kind of brand you manage, the resulting lift in e-commerce. Thanks to the miracle of social data, you could even go back a Super Bowl or two and look for common ground (note: given the changing slate of advertisers it’s never a direct comparison)
Deploying is a little like tagging wildlife and then tracking them through the backcountry. If you map baseline traits of the people who are engaged online with your brand beforehand, you can sift through the Super Bowl commentary and see what people with those same traits were engaged with. Did your ad engage them? What was it about your ad? Or was it other brands’ ads, and if so, what was it about their ads? I suspect Audi would hope to see their people engage more deeply with their spot and display a decreased engagement with their ongoing crisis.
You can also work it the other way, tracking the people who gravitated to your ad & digging into who they are. Budweiser’s immigration spot appears to have garnered this kind of widespread engagement, with many tweets expressing renewed interest in drinking a Bud.
If you’re the patient type with the right kind of brand, you can lurk around e-commerce sites & look for reviews from a particular bunch of consumers and then draw some conclusions regarding lift. Here’s looking at you, LifeWtr. Here’s looking at you, Fiji Water.
If you’re the opposite of the patient type, you could kick up your tracking up to real-time & be able to respond smartly in the moment, which in retrospect might really have helped out Snickers.
No matter how you slice it, that’s a lot of intelligence to bring to your next steps whatever they might be – revisiting creative, working out the budget for next year, leveraging structured data to begin to understand the size of the opportunities these engaged consumers represent, etc.
Epsilon’s Data Design team was created to ensure our focus is laser-sharp from the outset, so insight and strategy development start together and from the right place. The team specializes in this particular kind of “data Tetris” because we’re able to integrate the worlds of structured and unstructured data so we can create data-driven insights, perspective and momentum, which we as an agency then leverage across the spectrum of communications and marketing activity.
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