Last year, I had to do an extensive online reputation management job for a client. While I was able to outrank most of the other websites already in search engine results pages (SERPs), one specific issue presented a higher difficulty: Two top spots were occupied by some very old (c. 2005–2006) articles.
My task was to override those results, growing the digital properties owned by my client. Unfortunately, even after employing a link-building strategy on the digital properties, I was unable to reach my goal.
So I decided to test a different strategy: Remembering the numerous theories about the influence of click-through rate on the search results pages, I hired a certain number of people on a “micro jobs network” and made them click on the digital properties.
In a matter of few weeks, the digital properties were able to overtake the newspaper articles.
The result was so interesting that I decided to do an experiment with my friend, Andrea Scarpetta, in order to validate the hypothesis of the click-through rate as a ranking signal.
We developed a software tool which could simulate a random sequence of clicks on a query, with these characteristics:
We know that Google takes into consideration hundreds of factors in order to calculate the ranking of a single URL; therefore, we tried to exclude many on-site and off-site elements which could have influenced the test. After a long debate, we agreed on the following features:
In order to monitor the changes, we used two different methods:
After a week of activity, the clicked URL improved its ranking from the 10th to the 3rd position and maintained an average rank for the rest of the time between the 4th and 5th positions.
We weren’t completely sure of the results shown by Pro Rank Tracker; the service is usually accurate enough, but we know that Google is changing the results depending on the location of the users. In order to have a proper rank check, we recorded the position of every URL clicked by the software.
We noticed an interesting trend: the average rankings were shifting back and forth a lot more than we imagined!
Even after the experiment, we can’t definitively say that the click-through rate is a ranking factor. We agree with AJ Kohn‘s vision that it’s probably an “offset” which changes the results depending on specific interests shown by an audience. We could say that there is correlation between the clicks and the “visible ranking” of a query.
We can’t say if this kind of “offset” is stable or degrades over time, but at least we can affirm that an interesting title and meta description influence the click-through ratio, and therefore, it’s an indirect way to influence the “visible ranking.”
We intend to do some other tests in the future to measure if the “pogosticking” effect is real and influences the rankings of a page.
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