New Data On How Paid Ranking Translates Into Traffic
A new study from Atlas DMT tries suggests that top rankings do indeed equal lots of clickthrough and traffic, at least in terms of paid listings.
A new study from Atlas DMT tries suggests that top rankings do indeed equal lots of clickthrough and traffic, at least in terms of paid listings.
A common question many have is whether rank makes a difference. Is it better to be number one on a search engine, or is just being in the first page of results good enough?
A new study from Atlas DMT tries to answer the question in terms of traffic and for paid listings. The answer seems to be, if you want lots of traffic, then pay the premium to be listed number one.
Traffic, of course, isn’t the same as conversion and return-on-investment. Being number one might get you more visitors, but the higher cost might hurt your ROI. I’ve also heard anecdotal evidence that some people not being in the first results can help improve conversion because you are less likely to get “impulse clickers.”
The report, “How Search Engine Rank Impacts Traffic,” is available in PDF format for anyone to read, but I found it short on details about methodology. Fortunately, this ClickZ article sheds light. The study involved an analysis of about 60,000 paid listings on Google and Overture in May and June of this year.
The heart of the survey is two tables that show how traffic is estimated to drop off for ads place on the networks run by Overture and Google.
For example, being ranked second on Overture is estimated to provide 97.2 percent of the impressions compared to being ranked first — in other words, a drop of 2.8 percent.
Knowing impressions is fine, but what about clickthrough — that’s what you need to know if you are trying to understand potential traffic. Well, the clickthrough rate on an ad in second position is estimated to be 80 percent of the rate for an ad in the top position — in other words, a drop of 20 percent.
Both figures are multiplied to come up with a “click potential” rate for each position. So the second position for Overture has a click potential rate of 77.7 percent, compared to the top rate.
This click potential rate is the key figure for using the study’s data to predict traffic. Assume you know you maintained an average position of second in Overture over a period of time, such as a week, and generated 4,000 clicks during that time. What would happen if you paid more to rise to first or paid less to drop to third? Use the click potential rate to predict like this:
click potential of position you want / click potential of current position x clicks = predicted clicks
So to predict the rise to first, you’d use the click potential for the first position on Overture (100) divided by the click potential of the second position that you’d been averaging (77.7) times the clicks you’d generated in the time period (4,000) to get a predicted number of clicks if you moved up for the same time period, like this:
Similarly, the drop to position three would work like this:
It’s crucial to remember that the figures to do nothing to take into account the average cost to move up or down into these other positions nor any up or down in conversion rate. That will only come from your own real time data. And to be honest, rather than trying to predict clicks using these tables, you might just find it easier to do some actual testing of your own. Spend a bit more and move up; spend a bit less and move down, then monitor everything to see what gains or losses resulted.
Going back to the tables, a big surprise is how the impressions drop off so dramatically by rank in Google. It’s also surprising to see the dropoff even to a much lesser degree with Overture.
For example, virtually anyone who sees the number one listing from Overture should also see the second. After all, Overture’s two largest partners, Yahoo and MSN, both have traditionally shown at least the top three listings — if not more — on their search results pages.
Given this, the number of impressions — the number of times the ads appeared — for position 1 and 2 ought to be about the same. Instead, the Atlas report implies an ad is position two would only show up about 97 percent of the time. What’s happening to cause it not to appear the other 3 percent of the time? And what causes a third place ad not to show up over 5 percent of the time?
At Google, this is more pronounced. A second place ad is estimated not to show nearly 23 percent of the time. But Google and its major partner AOL almost always show more than just one ad, if there are multiple advertisers. If position one is showing, position two should also be showing at both places.
The author of the Atlas report, Nico Brooks, emailed these possible explanations:
One known factor that contributes to this result is the fact that we are reporting on average ranks, not absolute ranks. Therefore, a keyword ad reported as being in an average position of two may include some serves in positions one, three, four and so on. If some distribution partners only display positions one, two and three, this will impact the number of impressions for that ad. Since it is only really possible to manage average rank in Google, I don’t feel that this lessens the value of the research.
Another important consideration is the fact that we analyzed all Google AdWords traffic, including content ads. Some AdSense publishers only display one ad. My impression is that the performance of content ads has been improving over time, so this may be an area advertisers want to examine more closely.
One other factor that may contribute: Google’s budgeting algorithm can prevent keyword ads from getting 100 percent of available impressions. It seems to me that this could/should have the opposite effect, as higher ranked listings generally cost more in Google, but I have always found this algorithm to be unpredictable.
I cant say if these factors sufficiently explain the drop in impressions. What I can say is that the data consistently supported the finding.
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