Lot’s of people, and AOL is a well-documented party here, are trying to figure out how to cut the number of ad views on a page and increase the CPM they charge advertisers while not drastically reducing their page CPM. Similarly, decreasing low quality “picture galleries” or breaking articles into numerous pages, can decrease “available pages” while increasing the quality of the product being sold.
Unfortunately, that is incredibly effective and easy to execute in straightforward direct sales, but has relatively low perceived value in the world of exchanges. In exchanges, where people are typically buying audiences, one impression feels as good as another to most advertisers. When Fetchback wades into an exchange bidding $2.00 CPMs and charging their advertisers $6.00 CPMs, it doesn’t matter if there are 8 ads on the page or two ads on the page. The biggest challenge in a retargeting campaign is acquiring volume, so they are probably happy to get it any way they can. Generally, this ends up being true for lots of advertisers seeking audiences.
Further, advertisers have very little data about aggregate ad frequency per user (is this the hundredth ad they have seen on the site, on the exchange, or on the network today?) That data would help in the valuation process and is notoriously absent. Of course, as we discussed, only the most sophisticated advertisers would be able to value it.
Finally, were one to be one of those sophisticated advertisers, it would probably be all about the performance. Determining lift in performance for pages as the ads on them change is critical to effectively managing an exercise to decrease aggregate ad views across a web site. Split testing is important and I can tell you from experience that it needs to be a real split test. Simply changing and comparing a past period to the present exposes the test to too much variability of advertising supply.
Most publishers will struggle to justify the resources to conduct an exercise like this. Particularly when, unfortunately, given the simplistic perspective of many advertisers, there are reasonable odds that this will not move the needle at all in increasing the true net value of their sites inventory.
While it is in everyone’s best interest (theoretically) to have fewer, better performing ads on a page, in an exchange where little is known about any given placement, a bad actor can exploit good actors in the system to unfairly maximize his yield at the expense of other players. This results in a prisoners dilemma situation. The result is that, in many tests, publishers may find themselves in a death spiral of adding more ads to inventory to increase the effective yield of a page.
It will be interesting to see how we evolve the Internet to be a good place for advertisers and readers.