Return on invest for a Super Bowl ad used to be constrained to a scant 30 seconds to impress your captive audience, and, if you were lucky enough to make it into the top 10, you might recoup your multi-million dollar cost. But a little thing called the World Wide Web, with its social networks, videos and hashtags, has changed the game. The Super Bowl is no longer a one-night affair, but rather the centerpiece in a longer, more thoughtful and engaging strategy. Unfortunately, marketers still don't understand the nuances of a multi-device world, treating social media as an afterthought, instead of a way to make a bigger impact.
Years ago, there was a time when comedy meant something. There was Animal House, which explored the importance of brothership and male bonding with raw honesty; there was Office Space, which spoke to dissatisfied workers everywhere in a way that no film had before; and, of course, there was Groundhog Day.
Groundhog Day is one of the all-time great comedies, and it shouldn’t surprise you to hear it’s not just some goofy Bill Murray vehicle engineered for big laughs and steady DVD sales. No, when you really think about it, Groundhog Day is a film that resonates deeply with nearly everyone that views it. The movie speaks to an ever-growing generation of Americans that hates their jobs, their lives and pretty much everything around them that contributes to the agonizing dullness of their existence. Best of all, it speaks to these people with a positive message—one that empowers them to ignite change in themselves.
That's right, watching Groundhog Day can make you a better person, but the bigger question is: can it make you a better marketer?
The Super Bowl is known for bringing out the best (and worst) in advertisers around the globe. This weekend, you'll see viral sensations, spots that completely miss the mark, and more than a few ads that aim to push the boundaries of good taste. If you look closely, far past the gray area between funny and offensive, deep into the realm of misogyny and exploitation, you'll more than likely find a commercial from GoDaddy.com.
I’ve always been a huge fan of Charles and Ray Eames. Their contributions to design, architecture, filmmaking and furniture are unparalleled in our nation's short history. So, it was a huge honor to launch a digital campaign to help preserve one of their most important works, the Eames House.
Like many things in life, this campaign never would have happened if it were not for a chance encounter that took place two years ago.
The climate of the 1960s bears an unfortunate resemblance to the state of our country today. We are dealing with issues of political and urban unrest, race baiting and gun legislation. We live in a polarized nation of red state vs. blue state, gay vs. straight, black vs. white and the haves vs. the have nots. Citizens in some states are even petitioning to secede from the nation. What is truly amazing and inspiring, however, is that someone would combat these issues not with a closed fist of hyper aggression and willful ignorance, but an open hand of love and understanding.
“Those numbers are skewed.” “That survey is biased.” “Heresy!” These are explanations we’ve all used to excuse away numbers proving our theory or belief to be incorrect. While our skepticism is usually justifiable given the ease with which data can be manipulated and repackaged, we still don’t know when or why to believe in statistical results.
These same responses to unpopular statistics can often be heard coming from the mouths of website data analysts. Other than, “the tracking code didn’t fire correctly,” one of the most common web analyst defenses might be, “but it’s not statistically significant.” Given the general distaste among the marketing community for anything suggesting scientific leanings, these rationalizations are usually accepted without further comment or debate.
What’s interesting about this particular self-defeatism is that by refusing to delve into what the numbers mean, CMOs and even CEOs are handing control of their marketing efforts over to a data analyst who may not even know what their goals are.