Getting Acquainted With The Latest Google Algorithm Updates

Are you finding it more and more difficult to rank your webpages on the first page of Google? If you answered yes, then you are riding the same boat as countless other webmasters out there. Over the years, Google has become way smarter when it comes to understanding the context behind webpages and providing the most accurate results for their users. This is made possible by the constant development of their search algorithm. If you are not a beginner in SEO, then you probably know about some of these updates. Following are some of the most prominent Google algorithms you should know about.







Google Panda Update

Released back in 2011, the Google Panda update produced shockwaves felt by nearly all webmasters. This algorithmic update helped Google determine what sites to remove in their search index. In particular, this update targeted thin websites, or those that did not really offer anything valuable to search engine users. Before Panda, it proved quite easy to rank a webpage on the first page. It was a matter of stuffing your keywords in the content, even though the rest of the text isn’t out of the ordinary.

Thanks to Panda, the search results have become way more accurate and relevant. Websites that were obviously made for the sole reason of making money on AdSense got wiped out. Perhaps the biggest lesson learned by webmasters after Panda was to focus on providing real value to users instead of simply creating content just for the sake of it.

Google Penguin Update

A year after releasing Panda, Google decided to release the Penguin update. This time, they focused on penalizing websites that utilized various link building techniques. According to Google’s quality guidelines, any form of manual link building should be avoided. However, most SEOs know that links are among the most powerful ranking signals. For this reason, many were able to rank quickly by simply pointing countless back links to their webpages.

The Penguin update made it possible for Google to penalized websites that only relied on such shady link building practices. Their algorithm has since given higher importance to links from relevant, authoritative and contextual sources. Links that are created in an attempt to rank quicker are devalued.

Google Mobile Friendly Update

Another important update released by Google is their mobile friendly algorithm. More than two years ago, the number of mobile searches has finally surpassed the number of desktop searches. Clearly, Google needs to address the needs of their mobile users. This came in the form of the mobile friendly update, which gave a ranking benefit to websites that use mobile friendly design.

Recently, this has become even more important following the announcement of Google regarding their mobile first index. Google plans on looking at the ranking factors found on the mobile version of a website instead of evaluating its desktop version.

There are plenty of other algorithm updates you should know about. However, these three prove to be the ones that had the most impact on webmasters. By having a thorough understanding of the different Google updates, you should be able to formulate a more effective SEO strategy.


Google representatives have said very little about how the Penguin algorithm works. This means the Penguin algorithm is a more or less a mystery to the search marketing community.

However I believe there is enough evidence out there to define what Penguin is and how it works.

The purpose of this article is to investigate available clues and begin the process of understanding the Penguin algorithm. Additionally, I believe a patent published by Google in late 2015 that was briefly discussed within the SEO community and quickly forgotten, may be the key to understanding Penguin (more on this later).

Some may question the need for this.  In my opinion it is literally our business as SEOs to have at least a cursory understanding of how search engines work. This is what our industry has done from day one. No part of Google has gone unexamined. So why stop at Penguin? There’s no point in working in the dark. Let’s throw some light on this bird!



What Penguin is… Not

Is Penguin a Trust Algorithm?

In order to know what something is, it helps to know what it is not. There has been speculation that Penguin is a “trust” algorithm.  Is it?

The truth about trust algorithms is that they tend to be biased toward large sites. Which is why the original Trust Rank research paper was superseded by another research paper, Topical Trust Rank. Topical Trust Rank was 19- to 43.1% better at finding spam than plain vanilla Trust Rank. However, the authors of that research acknowledged certain shortcomings in the algorithm and that further research was necessary.

There are statements from Googlers as early as 2007 making it clear that Google does not use Trust Rank. Additionally, in 2011 the point was made by Google that trust was not a ranking factor in itself, that the word “trust” was merely a catchall word they used for a variety of signals. The statements make it clear with absolutely no ambiguity that Google does not use a trust rank algorithm.

No patent application, no Google blog post, no Twitter tweet or Facebook post indicates that Penguin is a kind of trust-ranking algorithm. There is no evidence I can find that Penguin is a trust-based algorithm. It is therefore a reasonable observation that Penguin is not a trust rank algorithm.



Does Penguin Use Machine Learning?

Gary Illyes confirmed in October 2016 that Penguin does not use machine learning. This is an incredibly important clue.

Machine learning is, in a simplified description, a process where a computer is taught to identify something by giving it clues to what that something looks like. For a simple hypothetical example, we can teach a computer to identify a dog by giving it the clues that something is a dog. Those clues can be a tail, a dark nose, fur and a barking noise.

For machine learning, those clues are known as classifiers. The SEO industry calls those classifiers signals. A typical SEO tries to create “signals” of quality. A machine learning algorithm uses classifiers to understand if a web page meets the definition of a quality web page. This can also work in reverse for spam.

Does Penguin Use Statistical Analysis?

There is frequent reference to the possibility that statistical analysis plays a role in Penguin. Statistical analysis identifies variables that are common to normal sites and spam sites. Variables range from anchor text ratios to the percentage of inlinks to the home page to the rest of the site. When the entire web is analyzed, the abnormal (spam) pages stand out. These (spam) pages are called outliers.

The use of statistical analysis as a spam fighting technique was confirmed at Pubcon New Orleans 2005 when it was openly discussed by Google engineers at a keynote presentation. Thus, we know that statistical analysis has been a feature of Google’s spam fighting since at least 2005.

One of the most well-known research papers on statistical analysis is a research paper published by Microsoft in 2004. This research paper is titled, Spam, Damn Spam, and Statistics.

Statistical analysis has revealed that there are patterns in the way spam sites build links. These patterns are symptoms of their activities. Penguin does more than identify the symptoms of the activities.

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