Google Study: PPC Ads Do NOT Cannibalize Your Organic Traffic
Though I’ve never met him personally, I admit to being a big Hal Varian fan. For those who don’t recognize the name, Dr. Varian is the Chief Economist at Google and like me, one of the oldest guys in his company. Over the past few years, he and his team of researchers have made my […]
Though I’ve never met him personally, I admit to being a big Hal Varian fan. For those who don’t recognize the name, Dr. Varian is the Chief Economist at Google and like me, one of the oldest guys in his company.
Over the past few years, he and his team of researchers have made my life simpler by providing pithy answers to some of search’s mythically difficult questions, like “How do search auctions work?” and “Does ad position effect conversion rates?”
Last week, his team at Google released the results of their research that answers a question that paid search managers across the world get asked on a regular basis: “Why the [bleep] are we advertising on our own [bleeping] brand terms when we are ranked #1 for those [bleepety-bleep-bleeping] terms already? [Bleep]!”
Though the Google research team posed the question in a slightly more scientifically-fashionable way for their research, they essentially set out to answer the question of whether or not paid search ads cannibalize traffic from corresponding organic listings for the same keywords.
Their findings, in true Varian-esque style, were simple, direct and memorable. They found that paid search ads give you a 89% incremental lift in site visitors – above and beyond traffic you would normally expect from your organic listings.
You can download the study at the Google Research Blog: “Incremental Clicks Impact Of Search Advertising” by David X. Chan, Yuan Yuan, Jim Koehler and Deepak Kumar.
Is A Google Study That Proves Google Paid Search Works Valid?
You don’t have to be a committed cynic or skeptic to question the results of Google’s research on its own search properties. It’s only natural to raise the question of self-interest, but since Google has made no bones about the fact that it is their own research, they are being upfront and candid.
In their report, they provide pretty good detail on their methodology and their statistical methods though it is provided only in summary form.
But, in fact, the study seems to support the prevailing conventional wisdom in our industry and even some earlier studies on the impact of paid advertising on brand terms and natural traffic. It certainly supports Brad Geddes findings in his Search Engine Land column last week, “Should You Bid On A Keyword If You Rank Organically For That Term?”
At most search conferences, and in columns, we often are reminded by experienced search experts such as Sid Shah, George Michie, Mona Elesseily,and Josh Dreller, to name a few, of the importance of managing and bidding on brand terms even when you have good organic positions.
Even when the advice is more anecdotal than data-driven, such as keeping your competitors from dominating the paid ad spots, brand building and controlling messages, most of us buy into the idea that it is a good idea to bid on brand and other high ranking terms.
A related independent research study published in 2008, by a NYU undergrad business student, Priti Kumar also seems to support Google’s conclusions, too.
The study, Search Advertising in Electronic Markets: A Study on the Impact of Keyword Wordographics (PDF) was more generally about the effects of wordographics on search advertising campaign success but in the process Kumar’s research mostly disproved the idea that paid search ads cannibalized brand keyword traffic, at least in the case of the large national retailer involved in the study.
Google’s own study was rigorous. They extracted data from 446 campaigns running in Germany, France, Great Britain and the United States from October, 2010 through March, 2011. They examined campaigns that had been paused after running ads for some period of time and then, using some clever deductive modeling, estimated the incremental impact of paid search ads on total search volume.
If the study has any Achilles heel, it might have been the fact that over half of the campaigns modeled were US campaigns, and were heavily dependant on data in the holiday period. There is some hint that the research is ongoing, and if so, it will be good to see if the same 89% lift holds true across other parts of the year.
Trust, But Verify Using The Nuclear Option
If you are really serious about testing the impact of paid search on your own campaigns, the quickest and most effective test is simply to simply to turn off your brand campaigns for a short period and then evaluate the impact on your traffic and your conversions, which I call the “Nuclear Option.”
I refer to this as the Nuclear Option because it often chokes off so much traffic so quickly that you notice the impact on top-line revenues immediately. We don’t deploy it often because it can have such a detrimental impact on revenues. More often, just threatening to turn off the brand campaigns is enough to dissuade others in your organization who are whining about paying for clicks they believe they should be getting free. They usually back down before the test goes online.
Or, you can take a studied approach along the lines Brad Geddes outlined last week. Both Brad and Google provide formulas for evaluating the economics of your own incremental paid search ad cannibalization studies. The math involved in doing your own testing is straightforward and is actually superior to the Google study, because instead of looking purely at click volume, making it a better truer test of your particular campaign and market space.
Google stops short of recommending taking the campaigns offline, though, and suggests modeling instead of the Nuclear Option. Most of us don’t have in-house economists, however, but if Hal Varian wants to volunteer any of his scientists to to devise models for any of our accounts, we will welcome them with open arms.
Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.