If you work in advertising, you probably already know a thing or two about marketing attribution. Simply put, marketing attribution is the process of tracking and crediting the various tactics that lead to a conversion.
Yet not all marketing attribution models are made alike. When it comes to display advertising, click-through attribution turns out to be a notoriously unreliable way to measure a campaign. The vast majority of users never click on a display ad. Those who do click on them tend to do so at random, often by accident.
Even worse, click-through attribution only gives credit to the last click, in what might be a long chain of messages directed at users. It creates a distorted picture of what works and what doesn’t, and many an effective ad has been overlooked because the last click was getting all the credit.
Take the case of John Doe, who came to a technology company’s website for the first time from an SEM ad and then filled in a form. Let’s say we also know that John became a client after attending a webinar. If we rely on click-through thinking, we’ll credit the last actions in the chains: the click on the SEM ad and the webinar.
But what if John Doe had seen lots of their display banners before ever clicking on that SEM banner or attending that webinar? Did those banners really have nothing to do with the final action? It seems highly unlikely, but with click-through attribution, those banners get none of the credit.
Fortunately for the display world, other attribution models have been developed to assess the value of display campaigns. View-through attribution, in particular, has made it much easier for marketers to understand how their display campaigns are working. With view-through attribution, a marketer tracks whether a user has been exposed to a display ad — regardless of whether he or she clicks on the ad. In other words, view-through acknowledges what offline advertisers have always known: an ad can work even when it’s not clicked on.
But just as display is beginning to solve some of its attribution problems, content marketing is beginning to run into some of the very same problems.
Let’s return, for a moment, to the example above. What if John Doe had been exposed to content marketing, as well? What if he had read the company’s long article in a publication he loves and it referenced the power of the technology he is after? That would almost certainly be the most powerful marketing of all, the most critical link in the chain, and yet it would receive not an ounce of credit for the conversion.
And we’re not only talking about articles here. John Doe may have been exposed to lots of different types of content along the way. What about the brand tweets and Facebook posts he looked at but never clicked on? What about the sponsored ads he saw on LinkedIn? Sophisticated brands today are using a wide range of channels to deliver content to customers, and most of those channels will never get credit with today’s attribution models.
So, why haven’t these companies made more progress in tracking and crediting content? Why are non-clicked based tactics still ignored? At the moment, we tend to track and credit merely what’s easy to track and credit. This is why marketing automation companies are sometimes referred to as “email platforms on steroids.” Email marketing is the focus because it’s the easiest tactic to track.
This isn’t to say no one is trying to do a better job. We’ve seen some efforts from marketing automation companies to offer multiple touchpoint analyses that look at multiple click-based tactics. But these efforts don’t go far enough. These systems tend to be cumbersome to set up, and, more troubling yet, they’re not always very reliable.
So, yes, there are still some obstacles to better attribution models. But these are solvable problems and content marketers will need to demand more from their marketing automation vendors in 2014.
Content marketing is just too valuable to be ignored. Let’s hope that content will get the credit it deserves next year.
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