The view-through is the honorable concept of giving credit where credit is due. The idea is if a media buy on a particular site or network influenced consumers to engage in search, direct navigation, then purchase (or registration for a lead), the referrer should get credit for influencing the purchase behavior. The media and creative used in the buy push and propel the consumer down the buying funnel and closer to the purchase.
While the original intent behind the view-through may have been noble, it's misapplied, misused, and abused. Unfortunately, if misused in conjunction with PPC (define) search, the view-through metric can lead to disastrous media buying decisions and a misallocation of media dollars. Other ill effects include duplicate attribution of orders and other conversions to media that had no influence whatsoever on the final consumer behavior (the purchase, lead, or registration).
If you use view-through conversions and SEM (define) concurrently, this column could be very important.
Obviously, other media influence search behavior. There's no argument from any marketer watching the interaction effects between media and search query inventory. For larger media spenders, the Yahoo Buzz Index can be an indicator of the success of offline media and marketing campaigns at the macro level. The realization that there are interaction effects among media has lead to increasing use of the view-through metric, particularly the view-through conversion. This use has spread to the search world, where marketers seek to understand the interaction effects of display media and search.
One way in which view-throughs are exploited is by giving a site or network credit for a purchase when other fundamentals of the media buy aren't sound. For example, assume you structured a deal to give a network or publisher credit (and a bounty of some sort) for view-through conversions. Any of the large networks will have significant reach into the intent population, particularly the most active consumers. However, reach doesn't necessarily equate with influence. Impressions that set a cookie for the purpose of calculating and attributing a view-through could, in fact, occur below the fold, in a layer on the screen, or on a browser tab not in a top layer, with zero likelihood the impression actually made an impression.
Larger ad networks have a monthly reach far in excess of 50 percent of U.S. Internet population. So with little or no targeting, the network could guarantee sufficient impressions to leave a cookie trail across a large percentage of your existing customers, and therefore claim credit for influencing their purchase behavior. With a bit of targeting, any of these networks as well as any agency working on a performance deal could buy extremely inexpensive small banner placements on very cluttered large pages on sites that are highly visited, purely for the purposes of tagging customers who would have purchased from you anyway.
Unifying reporting in a single advertiser-side ad server is insufficient. Similarly, setting short cookie lengths only forces the impressions to be higher within the network. It doesn't matter how proximal an impression was to a sale if that impression didn't actually influence the sale. Clearly, the last click before the sale can be more accurately determined if one inbound ad server is used, but the whole idea of the view-through was supposed to be to quantify influence that didn't result in a click and instead manifested itself through a latent behavior.
If your agency or media buyer includes arrangements that sound like it's using view-through conversions and taking monetary credit for the sales originating from those conversions, you may be being duped every day.
Don't get me wrong. The view-through has value as a metric when the best practices in media buying are applied with the view-through. Know the placements you're getting, look at relative CTR (define) on banner placements between media where you control placement on the page. If the CTR is dramatically lower or even slightly lower on some of your view-through-dependent buys, consumers aren't actually noticing your ads.
An even better way to use view-throughs is to look at audience affinity to your site. I have my team experimenting with an improvement on the view-through: the view-around (if the term catches on, I'll take credit), where the system of measurement (and the reporting technology) doesn't care whether the media impression happens before or after the site visit and simply looks at and compares the percentage of impressions that result in a view-around. The higher the correlation between a method of targeting (site, channel, behavioral targeting, etc.), the more likely you are to find new customers using the same targeting parameters. Your customers are probably similar in a set of behaviors or preferences, and this information can be leveraged. Then you can look at interactions between search and impressions while using other metrics such as CTR to make sure your banners or rich media advertising are actually being seen.
There are other ways of constructing media experiments to determine if banner views are influencing search and direct navigation, but these aren't search related, so I'll leave them to the other ClickZ experts to cover.
When search and other media are combined and measured properly, they make a killer combination. When your agency or ad network takes advantage of the view-through without adding value, you're getting killed.
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Kevin Lee, Didit cofounder and executive chairman, has been an acknowledged search engine marketing expert since 1995. His years of SEM expertise provide the foundation for Didit's proprietary Maestro search campaign technology. The company's unparalleled results, custom strategies, and client growth have earned it recognition not only among marketers but also as part of the 2007 Inc 500 (No. 137) as well as three-time Deloitte's Fast 500 placement. Kevin's latest book, "Search Engine Advertising" has been widely praised.
Industry leadership includes being a founding board member of SEMPO and its first elected chairman. "The Wall St. Journal," "BusinessWeek," "The New York Times," Bloomberg, CNET, "USA Today," "San Jose Mercury News," and other press quote Kevin regularly. Kevin lectures at leading industry conferences, plus New York, Columbia, Fordham, and Pace universities. Kevin earned his MBA from the Yale School of Management in 1992 and lives in Manhattan with his wife, a New York psychologist and children.
March 19, 2014