Don't rely on first impressions when it comes to ad impressions. Columnist Andrew Edwards explains how to dig deeper with analytics to uncover greater value in your PPC campaigns.
Recently, a customer suffered a costly setback in a CPM campaign -- and I suspect they're not the only ones with the problem. In fact, I think there's ample evidence to suggest the CPM and PPC world is rife with opacity and strange artifacts.
Here's what happened: the advertiser runs a professional services firm and wanted their ads to appear at certain sites where they believed customers might be found. That sounds simple enough. They contacted a relatively small ad network that claimed to specialize. The CPM program (which charges per impression, not per click-through) ran for several months and cost nearly twenty thousand dollars. It was canceled due to non-performance.
Why did this happen?
A review of the firm's Google Analytics revealed the traffic sources from the campaign and the amount of impressions from each venue. It turned out that over twenty per cent of the impressions delivered came from a site owned by the ad network itself. This seemed an anomaly. Upon further investigation, the site proved to be a page full of videos for a variety of brands. It had no other content besides the videos and there seemed little reason for anyone to actually visit the site. So where did all the impressions come from?
It's really anyone's guess. But one might conclude this URL was used simply to generate impressions with no actual visitors or at least, no visitors relevant to the campaign. When the facts were presented to the network, they credited the customer for all the impressions from that site.
Score a win for analytics!
But what if you're running multiple campaigns and don't have time to run down each and every bad batch of impressions? How would you know where your impressions were coming from, whether they were actually visible, and whether the site was of any real quality relative to your goals?
comScore, the well known media measurement firm, may have some answers. While they recently came out with a product called Validated Media Essentials (vME) designed to help media sellers increase advertising inventory and revenue, they also have a product called Validated Campaign Essentials (vCE) that is designed to help buyers fight opacity in networked advertising.
Here are some of the things it can do:
The net result of these kinds of insights is that the buyer can increase campaign effectiveness and, just as importantly, they play an important role in decreasing wasted impressions (and dollars).
In the newest version of vCE, you can gain access to important data based on an accounting of impressions delivered across a variety of dimensions, such as ads delivered in-view, in the right geography, in a brand safe environment and absent of non-human traffic. It also evaluates the degree to which validated impressions reached the campaign target audience.
Why does this matter?
Geographic data is key because ad networks use a wide variety of sites to deliver impressions. But if you have an interest in generating traffic within a specific region, your ad network won't necessarily target geography, or at least not with sufficient accuracy. Tools like vCE 2.0 will help you understand where the traffic is coming from. This is accomplished by comScore because they rely in part on a panel of known users. By extrapolating data from these users (there are over a million in the US), they can give you a good idea of what the geographic profile looks like for your impressions.
Viewability is also a key metric, yet your typical analytics tool will not provide any insight into this. The term refers to whether or not your ad, even if served, actually showed up in the screen seen by the user. Think of it this way: many pages are longer than a single screen, and often you have to scroll to see the entire page. What if your ad was served, but was too far down the page? And what if the user left the page without ever seeing it? vCE lets you know whether or not the ad was actually capable of being seen, or if it was instead hidden "below the fold" (to use an old newspaper phrase) and never actually viewed by a person. You should not have to pay for ads never capable of being seen.
Brand safety is often overlooked, but it's the equivalent of insisting that your billboard for milk does not appear on top of a slaughterhouse. How can you know that the sites where your ad is seen don't in fact make your ad reflect poorly on your company? What is the quality of that site? Does it have lots of negative comments in its forums? Is it badly formatted, possessed only of thin, irrelevant content? Does it seem to present an unsavory image for your brand? Make sure your ads are appearing only in places that make you seem both relevant and elegant.
Non-human traffic is also a major problem, as pointed out in my example above. There's no single reason why a particular ad network might generate impressions to non-human traffic, and we're not here to determine whether this is ever done on purpose to inflate impressions. But it's not an insignificant number of impressions in many cases. And without a way to track it down, you'll pay for ads that somehow got served, but in a manner not associated with human activity. Unfortunately, bots today do not buy things. Perhaps one day they shall (as we enter the Age of Drones) but right now they are not very good prospects. There is no reason to pay for these impressions.
Piercing the Veil
Many buyers believe, mistakenly, that CPM campaigns are a set-it-and-forget it proposition, and that they are getting a clean deal from their ad network. But there are too many variables involved, and ad networks sometimes prefer opacity to accountability.
You may not need a specialized tool like vCE -- as indicated above, you can certainly learn much just from reviewing your standard analytics with care. But vCE and tools like it go beyond what analytics alone can provide. Especially if you're managing high-volume campaigns, it would be a mistake to rely simply on reporting from the ad network. Self-reporting is too one-sided. You need a way to arbitrate your buy. Using third party tools to measure ad buys is just as important as using third party analytics to understand traffic patterns.
Don't rely on first impressions when it comes to ad impressions. Dig deeper and you'll uncover more value.
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Andrew is a digital marketing executive with 20 years' experience servicing the enterprise customer. Currently he is Managing Partner at Efectyv Digital, a digital marketing consulting company, and Managing Partner at Technology Leaders, a web analytics consulting firm he founded in 2002. He combines extensive technical knowledge with a broad strategic understanding of digital marketing and especially digital measurement, plus hands-on creative in the form of the written word, user-experience and traditional design.
His practice is dedicated to building customers' digital marketing success and helping them save money during the process.
He is a writer, a public speaker and a visual artist as well.
His book "Digital is Destroying Everything—and What Comes Next" will be published by Pearson in the Spring of 2014. He writes a regular column about Analytics for ClickZ, the 2013 Online Publisher of the Year. He wrote the groundbreaking "Dawn of Convergence Analytics" report which was featured at the SES show in New York, and the second report in the series will be featured at the same show in San Francisco.
In addition to speaking at SES, he has presented at eMetrics; and his session was voted one of the top ten presentations at the DMA show in Las Vegas. He is speaking again at the DMA in Chicago in the fall of 2013.
In 2004 Andrew co-founded the Digital Analytics Association and is currently a Director Emeritus. He has designed analytics training curricula for business teams and has led seminars on digital marketing subjects.
He was also an Adjunct Professor at The Pratt Institute where he taught Advanced Computer Graphics for 3 years. Andrew is also an award-winning, nationally exhibited painter.
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