Google Panda Update – Short Clicks and Long Clicks / Pogosticking

Google Panda Update: Short Clicks and Long Clicks / Pogosticking

OK, Folks, we have some old words, and old signals that have become more popular in the days of Post-Panda.
“Short Clicks – Long Clicks” – and “Pogosticking”.
Add these to your SEO dictionary if you don’t have them in there already.

I’ve started reading In The Plex (April 2011) by Steven Levy, and I came to a couple of interesting paragraphs that I’d like to share:

On the most basic level, Google could see how satisfied users were. To paraphrase Tolstoy, happy users were all the same. The best sign of their happiness was the “long click”. this occurred when someone went to a search result, ideally the top one, and did not return. That meant Google has successfully fulfilled the query.  But unhappy users were unhappy in their own ways, most telling were the “short clicks” where a user followed a link and immediately returned to try again. “If people type something and then go and change their query, you could tell they aren’t happy,” says (Amit) Patel. “If they go to the next page of results, it’s a sign they’re not happy. You can use those signs that someone’s not happy with what we gave them to go back and study those cases and find places to improve search.”

We’ve known that Google has been looking at “Short clicks” and “long clicks” for years…I just think that with the Google Panda Updates, the measurement of those signals became much much stronger.

There’s 2 old articles worth reviewing as well . The first is by everyone’s favorite search patent translator, Bill Slawski (SEObytheSea). Bill wrote about Search Pogosticking and Search Previews in reference to a Yahoo patent back in November of 2008, where Bill says:

Search pogosticking is when a searcher bounces back and forth between a search results page at a search engine for a particular query and the pages listed in those search results.

A search engine could keep track of that kind of pogosticking activity in the data it collects in its log files or through a search toolbar, and use it to rerank the pages that show up in a search for that query.

And the second article is from Blind Five Year Old, from back in 2009, where he wrote about “Short Clicks vs. Long Clicks“.

They’re not peeking at bounce rates. Instead Google is measuring pogosticking activity by leveraging their current tracking mechanisms. Remember, Google already tracks the user, the search and the result clicked. All Google needed to do was to accurately model the time dimension.

Just a few days ago Microsoft was granted a patent called Automated satisfaction measurement for web search where Bill nicely translates this patent, and in his paper, Bill states:

Implicit feedback about how satisfied a searcher is with a web page that they found in a search result might be collected by a search engine. This kind of information isn’t provided explicitly by a searcher, but rather is implicit in the searcher’s actions or inactions.

And also in that same paper, Bill concludes:

Google’s Amit Singhal and Matt Cutts told us in The ‘Panda’ That Hates Farms: A Q&A With Google’s Top Search Engineers that the Panda update looks “for signals that recreate that same intuition, that same experience that you have as an engineer and that users have.” It’s possible that these signals are using some kind of classification system that might either incorporate user behavior signals into page rankings, or use it as feedback to evaluate the signals chosen to rerank pages in search results.

The kind of algorithmic approach that I pointed to in Searching Google for Big Panda and Finding Decision Trees may be in part what’s behind the Panda update, but it’s clear that user behavior plays a role in how a page or site might be evaluated by Google.

I also thought I’d include another paragraph from the In the Plex book worth noting:

In between the major rewrites, Google’s search quality teams constantly produced incremental improvements. “We’re looking at queries all the time and we find failures and say , ‘why, why why?'” says Singhal, who himself became involved in a perpetual quest to locate poor results that might have indicated bigger problems in the algorithm. He got into the habit of sampling the logs kept by Google on its users’ behavior and extracting random queries. When testing a new version of the search engine, his experimentation intensified. He would compile a list of tens of thousands of queries, simultaneously running them on the current version of Google search and the proposed revision. The secondary benefit of such a test was that it often detected a pattern of failure in certain queries.

I don’t have much to add to all these quotes… except that I still support my original theory that the biggest factor to the Panda update was the Tweaking of the importance of this factor:
Those who search Google…click on a search result listing…then go back to Google, and click on some other result….I think this is what can hurt you the most…. this in not bounce rate (bounce rate is when someone leaves your site and goes anywhere)… I am only concerned with those who leave your site, and go back to the Google search and click on someone else. ….Google can give all all sorts of great content advice…and we’ll take it and say “Thanks for the tips”…but I still think  that the biggest factor to Panda is “short clicks” and “long clicks” and Pogosticking.

I’ve been writing a lot lately on the Google Panda Update…including a few posts that I did on on Saturday and Sunday that you may have missed… see these:

• Google Panda Update – User Behavior and Other Signals – Examines user behavior as a factor, query entry, the
  SERP behavior, and click backs. Also looks into when you can get out of being Pandasized.
• Thoughts and Solutions from Jim Boykin – Post discussing the background of the Panda Update, including the supplemental
  results, caffine, and beyond. This post also looks at, " if I were Google what I would look at," and at solutions.
• Google Panda Update – A Overview of Analytics of 5 Panda II Affected Sites – This post discusses the analytics
  of five affected sites
• Google Panda Update – Google’s Content Guidence and Jim’s Take – This article goes over the list of 23 questions of
  the ‘Google MMindset’ for the Panda Update and outlines Jims thoughts for each.
• Google Panda Update Panda’s Punitive Punishment of Good Content – This post discuses how the Panda will punish your
  good content if fyou have bad content as well
• Losing Clients to Panda. I Just Lost $17,500/Month – Sharing of experience on the Panda Update as well as reflection
  on previous updates
• Google Agent Rank and Reputational Scores…It’s About Content and Writers and Panda! – Breakdown of what ‘agent rank’ means
  and a view from a Google Panda lens.
• Google Panda Update: Content + Design = Usable, Trustworthy Websites – discussion of website usability and implications
  on Google Panda Update
• Google Panda Update: Your Site is Going to Survive (funny) – Jim’s Panda Update remake of, "Country Boy Can Survive"

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