More data is always better, so long as the data are actionable.
Advertisers familiar with offline advertising metrics will now find a recognizable metric available in their Google AdWords interface: a share of voice (SOV) proxy called impression share (IS).
According to Google, SOV is "a relative portion of inventory available to a single advertiser within a defined market sector over a specified time period." The search giant defines "inventory" as the impression inventory available against your campaign based on your keyword and campaign settings. In addition to IS, Google has also released two related metrics: Lost IS (Rank) and Lost IS (Budget).
You won't find the new metrics in AdWords' campaign management section at either the ad-group or campaign level, but under the Reporting tab. To see IS data:
SOV has long been used in offline advertising. It was typically calculated as a percentage reflecting your total ad spend against your competitors' total ad spend. A more accurate measure of SOV in offline advertising would be to base the share calculation on the share of ad impressions against the target audience. Alas, this number was far more difficult to calculate, so percentage of total spending within your competitive set became the standard.
No one in the mainstream agency world ever had a satisfactory answer as to why one wouldn't adjust for efficiency. After all, if you were twice as efficient in buying media, your true SOV would be twice that of your competitive set when calculated using media spending. This is an important point to remember when using IS and the other new metrics provided by Google.
Using Google's New Metrics
In Google's case, the IS and lost IS metrics are useful in ways similar to the offline SOV. However, there are limitations in how you might use this data, not the least of which is the dramatic difference in the value of PPC (define) ad impressions within a SERP (define) based on position.
Common sense, CTR (define) data, and the eye-tracking study we did with Enquiro a couple years back all prove top center positions are far more likely to be noticed by searchers, making this impression dramatically more valuable. This goes back to that question to my supervisors years ago: why don't we adjust for efficiency in SOV?
Yet the data can be very useful in identifying poor campaign settings that may be causing low-value impressions while missing more valuable impressions (and clicks). If you have plenty of budget to spare, don't really care about efficiency, and have a high IS, congratulations. You're in the minority. Most advertisers are stretching their limited budgets as far as possible.
If your impression share is low, consider weeding out less valuable or (even better) less relevant impressions from your campaign. These search impressions could be tuned out by dayparting, ad scheduling (days of the week), geotargeting, adjusting match types, or keyword tuning. By eliminating impressions from the bottom (based on click profitability or relevance), you raise your IS without actually spending any more.
A side benefit may be impressions lost due to a low AdRank (based on Quality Score times bid) improve due to enhanced relevance. Google specifically identifies which impressions were lost due to low rank and which were lost due to campaign budget caps. If the lost impressions were due to a poor AdRank, raising the bid would help, but it's always cheaper to look for Quality Score improvements. Of course, you must take into account the value of the time spent tuning the campaign for improved Quality Score, but the benefits of an improved Quality Score are cumulative for as long as any campaign is active. This can be quite significant on high-volume campaigns.
More data is always better, so long as the data are actionable. When looking at Google's new SOV metrics, start on the most material sections of your campaign first and experiment with tuning there, where it matters most. The ad groups in your campaign's tail may be less significant in the overall picture and can probably wait. Those tail ad groups may also be less competitive, meaning your SOV is already higher.
My team and I have been using and will continue to use SOV and share of clicks data we have in a proprietary system that uses both client and comScore data. It's nice to see the engines are finding ways to make this data available as well.
Join us for SES Travel on July 26-27, in Seattle, WA.
Want more search information? ClickZ SEM Archives contain all our search columns, organized by topic.
Join the Industry's Leading eCommerce & Direct Marketing Experts in Chicago
ClickZ Live Chicago (Nov 3-6) will deliver over 50 sessions across 4 days and 10 individual tracks, including Data-Driven Marketing, Social, Mobile, Display, Search and Email. Check out the full agenda and register by Friday, Oct 3 to take advantage of Early Bird Rates!
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.
IBM Social Analytics: The Science Behind Social Media Marketing
80% of internet users say they prefer to connect with brands via Facebook. 65% of social media users say they use it to learn more about brands, products and services. Learn about how to find more about customers' attitudes, preferences and buying habits from what they say on social media channels.
An Introduction to Marketing Attribution: Selecting the Right Model for Search, Display & Social Advertising
If you're considering implementing a marketing attribution model to measure and optimize your programs, this paper is a great introduction. It also includes real-life tips from marketers who have successfully implemented attribution in their organizations.
September 23, 2014
September 30, 2014
1:00pm ET/10:00am PT
October 23, 2014
1:00pm ET/10:00am PT