Failure to be relevant can have devastating consequences in paid search.
Practitioners of SEO (define) talk a lot about the signals search engines use to determine whether one page or site is more relevant than another. Although this topic is rarely discussed with respect to paid search, it should be considered when planning and executing your own search campaigns as well as when evaluating your competitors' campaigns. By understanding relevance all the way through the search experience -- from the moment the searcher starts filling out that search box till the time she leaves your site (assuming she got there at all) -- you can put yourself in the shoes of both the search engine and the consumer.
Search engines care a lot about the consumer experience and have editorial policies in place to set a baseline for ad relevance, as well as algorithms that use signals to determine if the ad is in fact relevant to the search query. Failure to be relevant can have devastating consequences in paid search. You might think that you are getting free branding if your ads are not clicked or your landing pages hawk a solution that doesn't match the keyword. However, Google, Yahoo, and Microsoft all have their own versions of the Quality Score assigned to ad-keyword combinations as well as at the ad group, campaign, or account level.
Today, let's look at some signals the search engines probably -- or definitely -- use to determine the relevance of your paid search ads for specific search queries.
Normalized Predicted Click-Through Rate
Obviously, ads with high positions are more likely to get the highest CTR (define), but the search engines need to grade, compare, and score ads on a level playing field. So they use various normalization tables and formulas to normalize your predicted CTR. In one of Google's iterations to its Quality Score formula (which isn't shared publicly), Google announced that it calculates a new Quality Score for ads on a query-by-query basis. To illustrate this fact:
You'll see that the position of your ad is often higher on exact match than phrase or broad match. This is because your ad is more relevant for that exact query.
Keyword Use in the Ad
One reason exact match CTRs are high is that a well-crafted AdGroup makes use of the exact match term in the ad creative, reinforcing the searcher's belief that she have found a good match. Search engines may simply rely on historical CTR data (which bakes in the benefit of keyword use in the ad) or attribute an even higher score to well-crafted ads.
Domain Affinity to the Search Audience
Does your domain name have brand value? I certainly hope so, because your predicted CTR is higher when your brand both is recognized and has an affinity to the keyword. So big brands get a leg up here. But a descriptive domain or prefix to a domain can help the CTR, and then you can factor in either directly or perhaps as a signaling data point for the engines.
Click-Back Rate or Bounce Rate
Engines know that consumers unsatisfied with a landing page or site often click back to the SERP (define). So do whatever you can to engage consumers on your site. It's win-win.
Landing Page Triggers
Google has listed the landing page as a factor in its Quality Score algorithm for some time. Unless your landing pages are heavy in rich media, it makes sense for you to include body copy that resonates with your ad.
If the search engine toolbar policies permit the use of aggregated data or if the search engines were to buy data from large panel-based research firms, the search engines could add further signals to their relevance scores. For example:
It's in your best interest to optimize around these relevance score drivers regardless of whether search engines are paying attention or not. When you construct and optimize campaigns, think about relevance and all the ways it can be measured and optimized. Your bottom line will grow right along with your ad relevance.
What do you need to know about real-time bidding (RTB) to start using it? Join us on Thursday, October 15, 2009, at 1 p.m., for a free Webinar on the basics of real-time bidding to help advertisers and their agencies understand RTB's capabilities and advantages.
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.
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