Google recently announced a new automated click-discounting system for AdSense. The "Smart Pricing" system will adjust Google's click prices for some contextual clicks. If your contextual ad campaigns didn't work in the past, it's time for a fresh look with Smart Pricing.
Google acknowledges not all clicks are equal. Some contextual clicks will now be billed at a lower cost, after normalizing (factoring in quality). Details of Google's normalization formulas haven't been shared publicly. But a system that estimates a click's "true worth" and bill a lower amount is admirable. Under the new pricing system, AdWords search engine marketing (SEM) campaigns must focus on strategic and tactical implications. Google may even roll out the normalization algorithms within AdSense's "pure search" segments.
As I previously wrote, Overture's solution to click value variability is more marketer controlled. It allows marketers to set contextual click value in a pure auction. Marketers must have analytics and automation in place to take full advantage and place bids based on true measured value. Yet even within a market's contextual segment, variations between publishers, placements, and pages exist. This was the driver behind Smart Pricing.
Below, a tactical guide for deciding whether to opt in to AdSense in the Smart Pricing environment. AdWords has several settings, including an opt-in to AdSense. Luckily, after a campaign has run, you can pull reports from Google to determine the average CPC paid for pure search traffic and for contextual AdSense traffic. With Smart Pricing in place, depending on the pages your ad was displayed and clicked on, contextual ad costs could drop further below your max bid price than pure search clicks (which may be closer to your max bid).
To track and optimize bids for content inventory, marketers must currently rely on the HTTP referrer to make informed decisions about contextual ads. The referrer is captured in log files (and by some campaign management systems). When Google AdWords clicks originate from the content network, most show a "googlesyndication.com" domain in the HTTP referrer. Analytics or campaign management software can often run reports on this traffic.
Clicks are often without referrers, however. Even with tracking URLs, these clicks are indistinguishable in log files from pure search clicks.
Determining Content ROI
With the right tools you can calculate approximate return on investment (ROI) on the AdSense content segment. Determine the conversion rate (percentage) for traffic that contains the "googlesyndication.com" referrer, and, using the average CPC on content traffic as reported by Google, calculate ROI (cost per order/action, return on ad spend, etc.).
With Smart Pricing, your content network CPC may be lower than that of your pure search inventory. Therefore, a lower conversion rate may still result in acceptable ROI. Though an imperfect exercise (some clicks without referrers will end up in the pure search bucket), this process provides an approximation for making smart decisions.
Conversion on identifiable AdSense traffic is 4 percent. Conversion on all the other traffic (mostly pure search) is 5.5 percent. If Google's new Smart Pricing bills a CPC 25-30 percent less on average within content, ROI between both programs will be similar.
The Economics of Pricing and Value
Marketers set their max prices in a campaign based on the conversion and value they're able to identify. Not all listing clicks are equal. Value-altering factors include position, time of day, day of week, network partner (within a network), pure search typed (the user filled out a search box), pure search linked (the user navigated through a search directory to a link), contextual keyword match, quantity of content on a contextual page, reputation of the site on which contextual inventory sits, and hundreds of other possibilities.
In a fully efficient market, marketers with the right tools would measure every factor, then set each click's pricing based on a formula. Networks and systems would necessarily be very complex. Marketers would pay very high prices for valuable inventory as a result. Less-valuable inventory would omitted, allowing others to bid.
On the other hand, a publisher and ad network such as Google could save marketers the difficulty of building such marketing automation systems and relieve them from the burden of controlling all those factors. Instead, the network would assume there are common factors that can be measured by its spiders and correlated with quality for all marketers equally (i.e., there are no differences in click quality from one profile for marketer A and marketer B).
If that's true, Google can normalize the billed amount for clicks. If Google discounts poor-quality clicks, marketers feel empowered to raise their bid max, knowing Google will only charge what a click is worth based on a normalized quality profile. Google and publishers with good quality make more money. Lesser publishers get what their clicks are actually worth.
Do marketers prefer control or simplicity? Both, probably. Or, a compromise in which major factors are under their control and minor variables that influence quality are automatically adjusted for in a publisher's pricing scheme. There's room for a variety of solutions that combine marketer control and publisher/network administration. Continued innovation is almost certain.
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.
May 22, 2013
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June 5, 2013
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