I was thinking the other day about how "The Terminator" is a good analogy for digital media targeting. If you remember the movie plot, Skynet, a self-aware defense platform gone wrong, sends a cyborg assassin from the year 2029 back in time to 1984 to locate and kill Sarah Connor. The problem was, even with all of its advanced technology and a steroid-pumped Schwarzenegger, it had very little actionable information and was always one step behind the mother of the unborn savior of humanity.
Fast-forward to 2009, when nascent demand-side platforms made relying on editorial content as a proxy for in-market audiences a thing of the past. Seemingly overnight, it became easy for media agencies to leverage tracking cookies to locate humans who visited their brands' Web properties and target them with cheap remnant inventory. With the addition of third-party data, media agencies began to scale up their laser-targeted campaigns with "look-alike" audience segments.
The problem was, these display programs didn't perform any better than traditionally purchased media because the algorithms powering the campaigns were fueled by data that was misused or too unreliable to be an effective predictor of consumer behavior—especially when compared with data that can be gleaned from a live shopping session. As it still stands, we entrust our media programs to automated buying platforms that leverage suspect data to optimize the past to predict the future, and are completely blind to the opportunity of the here and now. This threatens the very existence of humanity. Locating Sarah Connor is our only hope!
The Signal and the Noise
It's easy to dismiss data fails as anything less than life-threatening—after all, who hasn't gotten a chuckle from auto correct fails in our texts, or when Google tries to guess our search terms before we finish typing. But it does get serious when misinformed algorithms bring down financial systems or airliners.