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RSSThree times in the past two weeks, I have been asked my opinion on the current state of "view-thru" conversion tracking. It seems that lots of people these days are concerned that view-thru tracking has gotten a bit out of control and is distorting the connection between the actual effectiveness of individual media properties and their "apparent" contribution to driving conversions for advertisers.
What is view-thru conversion tracking? Simply put, it is a technique designed to quantify the downstream value of online ad impressions. As we know, many people don't click on banners. However, many of those same people eventually surf to promoted sites on their own and convert. View-thru tracking associates the delivery of ad impressions to specific browsers, with eventual conversions by those users on the advertisers' Web sites. Thus, when agencies and advertisers evaluate which of their ad impressions were most effective, they can track conversions back to the Web sites or networks that delivered the ads, whether or not there was an initial click.
Typically agencies and advertisers establish specific rules as to who and how they will give credit to view-thru conversions. The complicating factor is that most sites and networks have overlapping audiences, so someone who eventually converts on a marketer's site is likely to have seen ads on several different sites or networks. Who gets the credit in the case of a view-thru? Some will give credit to everybody that served ads to the converting person within a certain amount of time, such as in the last week. However, the industry standard (established by the third-party ad servers) is to give credit only to the last site that served an ad to the user, thus nullifying the value contribution of all of the other ads served to that person. In addition, there is concern that crediting only the last site rewards media and media practices that can drive great view-thrus, but maybe don't deliver much real advertising value.
Sites and networks can get the credit for any of their visitors' ultimate conversions whether or not the ads are in places where they can actually get noticed, or whether or not the content that they are embedded in is even conducive to ad viewing (like on instant messengers where lots of users show up). This means that a bottom-of-the-page ad -- stuck below even the sites' text ads or a rotating ad in an instant messenger, which was the last thing that users closed out when packing up their laptop for home -- will get credit for users' subsequent conversion even if another site had just delivered three rich media, above-the-fold ads to the user only minutes before.
Is there a better way? I'm very interested in your ideas and opinions to help solve this problem, but here are some of mine to start the ball rolling:
- Sunshine. Let's try to bring some industry light on this topic to better understand it and to see if there is really a problem here or not.
- Best practices. Maybe there are some best practices that could be defined industry-wide for this practice, such as only allowing view-thru pixels on IAB standard ad units delivered above the fold (maybe some do exist already, but I am not aware of anything comprehensive) that could be put in place.
- Find alternatives. There may be some other methods out there to better measure post-view behaviors. I know that several of the measurement firms are building offerings in this space.
What do you think?
1 person recommends this article.
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Increasingly, online, print, broadcast, direct mail, and event media are being converged into marketing campaigns maximize impressions to the target audience. Perhaps in the future, the effectiveness of the campaign as a whole will be measured?
We've developed our own set of best practices to address the value of view-through conversions. Part 1 of the question is to review a Time-To-Convert analysis (both Atlas and DCLK offer ways to address this), both from a click and view-through perspective. TTC lets you see how many conversions in a given week (or almost any time frame you specify) took place within the last 24hrs, 48hrs, 72hrs, 7 days, etc. In general (although results will vary!!!!), the more view-throughs that are bunched towards 24-72 hrs, the likelier they are to have been influenced by your advertising activity. This doesn't address the other part of Dave's article, which is about 'who gets credit.' Over the last year we've worked with Atlas for one our clients to address unique conversions vs. overlapping conversions when trying to address the 'last impression' conundrum. We are able to look at a given cookie pool, see where the overlap takes place between sites and/or networks (after all, no site is an island!), and then post-hoc rebuild our campaign and see which site or network had the greatest influence on unique conversions. Again, results will vary and the devil is in the details, but this analysis provides a much more informed perspective on what media entity or entities provide the greatest value in the view-through equation.
Eric Porres Partner, COO Underscore Marketing LLC
As usual, your column is information-packed. I think that you raise very valid issues with View-thrus right now and there isn't a simple solution.
With the current technology, the best solution may very well call on psychology's conditioning principles to administer ratios of "worth" to each particular view.
In general culture, the "first impression" we always hear about is most important. Well, in psychology, that is true as well - it has the highest level of association to a particular instance of learning.
Additionally, the last view before they purchase may very well be the "closed the laptop and never saw the ad on the bottom" situation, but what about the last THREE ad impressions that user saw?
So it should be the largest payout to the originator, marginal payouts to the in-betweens who just continued the path of "learning" association, and a slightly higher (though lower than the first) payout for the last three displayers of that ad.
Eventually, science and tech may yield a better way of appropriating exact percentages, but this can be a good guide to start with.