The Increasing Value of the Ad Network

Interesting article about the shift in advertising to the web and how its Return On Investment (ROI) is becoming ever more important. I think I told the guys from Google about this prediction in 2003. The time has come Cost Per Acquisition (CPA) is the way to go, not Cost Per Click (CPC) will eventually become less and less relevant.

The reasons ad networks are thriving are price and improved technology. Ad networks charge much lower cost per thousand ads served (known as CPMs), as low as $4 on an ad network with some targeting, compared with $40 and up for some ads on premium sites like MSN or Yahoo.

Google Testing Pay for Performance Ads

What would happen if the largest online advertising network in the world decided to skip past issues like click fraud by integrating an affiliate style advertising program straight into their already popular network? Apparently, Google is ready to ask that question and everyone else is awaiting the answer.

Phillip Lenssen reports that some AdSense partners are receiving email invitations from Google to participate in a test of a new pay for performance (also known as CPA - cost per action) style advertising system. According to the invitation, the ads will not be sent as part of the existing contextual ad network, they're an entirely new system that site owners can opt into and can separately integrate into their site. In fact, it sounds like site owners can even hand-pick the ads that they'd like to run on their sites.

David Jackson at Seeking Alpha has a copy of the email from Google with more details on the program. The email notes that the program is currently open to only those that receive the invite from Google. It goes on to offer some tips on "optimizing" the CPA ads, like selecting ads that are topical to a publisher's site, or that blend well into the existing design. The email notes that the ads are currently running in a separate system than the existing Google AdSense ads and thus, will not compete with CPM and CPC ads for placement.

Efficient Frontier Pay Per Click Advertising Purchases

I have worked on a Wall Street trading desk and have also done a fair bit of Internet marketing. With the prices of prices cost per click (CPC) advertising going through the roof and the additional networks being added by MSN and Ask, it has become much more difficult to effectively execute a profitable CPC campaign. In a lot of cases I have suggested to my clients that we focus our efforts on other forms of marketing because CPC is just not making the ROI hurdles.

I read this article in Business 2.0 today and was intrigued by Efficient Frontier's approach to CPC advertising. I strongly believe that Efficient Frontier is worth a look for large advertisers. Below is an excerpt from the article that I found most intersting:

So Siminoff was intrigued when she met Efficient Frontier's founder, Anil Kamath. A Stanford computer science Ph.D. and the founder of eBoodle, a comparison-shopping startup ultimately acquired by BizRate, Kamath was creating a system to help advertisers more effectively place their text ads on Google and Yahoo, both of which conduct online auctions of search keywords that determine where the ads appear. Employing vast computing power and fiendishly intricate algorithms, Kamath's system would indicate which keywords to bid on and the optimal amount to bid--based on countless variables, from past click-through performance to the number of rival bidders, while taking account of constant fluctuations in auction prices.

All this should sound familiar to anyone acquainted with the incursion of computer-driven quantitative methods that transformed high finance in the 1990s. As Siminoff puts it, "Anil's approach was based on the same sort of math they use on Wall Street." (Before starting eBoodle, Kamath was a vice president at D.E. Shaw, a hedge fund that specializes in applying quant-jock models to program trading.)

"Google and Yahoo are like exchanges, so the analysis is essentially similar," Siminoff says. "You're studying all of the potential scenarios and choosing the ones likely to yield the best ROI in aggregate. Then you just keep iterating and refining the analysis."

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