Matt Cayless
Matt Cayless 7 August 2018

Three Major Google Algorithm Updates That Changed SEO - Are You Compliant?

Search Engine Optimisation has become so much more than fitting keywords into the page and fine-tuning your meta data. In recent years, Google has introduced a series of algorithms that take machine learning to new heights of sophistication.

We're going to look specifically at the three major algorithms  - Panda, Penguin, and Rank Brain. Each of these updates has had its own unique impact on the history of SEO.  

Google Panda

Panda was first introduced in February 2011. Google stated that Panda's purpose was to reward websites with high-quality content and to diminish the visibility of sites that exploited SEO criteria, cheating searchers into following a high-ranking link that turned out to be irrelevant to their search.

Panda was able to identify -

  • Thin content - pages that profess to satisfy a search term but contain very little by way of useful content.
  • Duplicate content - If a company, such as a house removal service, have almost identical web pages to cover different geographic areas - just replacing the city name on each page - this would be considered low-quality.
  • Keyword stuffing - pages created solely to attract traffic with researched keywords, offering little value to human readers.
  • Lack of trustworthiness/authority - it's tricky, perhaps, for new sites to gain authority, but Penguin (and later algorithmic updates) represented a general encouragement to fill the web with high-quality, well-researched information. 
  • Content farming - sites that employ writers to produce short, non-authoritative articles, with the intention of loading popular SEO keywords; full of bad grammar and spelling.
  • Ad-to-content ratio - click-bait sites that offer little of value, other than the opportunity to present paid advertising.
  • Mismatched query results - sites that promise to answer relevant questions, but don’t.

For content creators, Panda's intention was to up the game. For consumers, Google wanted to become the search engine that people could rely upon.

Google Penguin

Penguin was the natural sibling of Panda and sought to refine the algorithm further, identifying the sites that had learned to hurdle Panda. The initial roll-out of Penguin in 2012 targeted sites that used manipulative linking schemes, and those that continued to keyword stuff.

Link Schemes

A practice had developed of acquiring or purchasing back links from unrelated, low-quality websites that offered little value to readers.

For example, a plumbing business in Norfolk could spam discussion forums, referring to themselves as the "best plumbers in Norfolk". The more they spammed, the more often their company name would be associated with the keywords "best plumbers in Norfolk".

Alternatively, they might pay for a back-link that quoted their name, alongside "best plumbers in Norfolk". Often these back-links were on sites that were entirely unrelated to plumbing services and therefore a low-quality link.

Keyword Stuffing

High volumes of unnatural keywords appearing within a site triggered the Penguin algorithm.

I.e., Looking for the best locksmith in Pudsey? We have the best locksmith in Pudsey if you live in Pudsey locksmith best. Pudsey home-owners need the best locksmith in Pudsey, and the best locksmith in Pudsey is Pudsey Locksmiths.

It's nonsense.

Moreover, Penguin, over its ten iterations between 2012 and 2016, became more adept at recognising and penalising these practices.

Rank Brain

Rank Brain represented a real jump in machine learning, surpassing the sifting algorithms of Panda and Penguin, by observing how people search; interpreting and predicting search terms to send users to the most relevant content-base.

Introduced in October 2015, Rank Brain incorporated an "interpretation model" that combined search terms with other factors such as location and personalisation. This was Google's concerted effort to decode clumsy search terms so that they could recognise the user's true intent. By identifying true intent, Google could deliver the most relevant results.

Google fed Rank Brain with data from various origins as a starting point, after which they left the algorithm to grow: calculating and learning over time to identify the signals that help it understand what the user wants.

So it seems that Google really is watching you!


Say, for example, you search for “world cup location”.

Rank Brain attempts to pre-empt the true intent of the search. Do you mean world cup 2018 or 2022; or are you looking for the historical locations of world cups of years gone by.

Is the searcher sitting in a hotel in Russia, trying to find directions to the latest match?

Previous algorithms could only answer that query using simplistic algorithmic rules and signals - the quality of content, the volume of links to a high-ranking page. They could send the searcher to the highest ranking site, based on a set of rules that were relatively straightforward to bypass.

Rank Brain can mathematically deduce results based around patterns that the learning algorithm has observed in broader search behaviours, using the Google "answer box" to provide a solution that it thinks you're looking for.

So, search terms alone no longer determine what response you get from a Google search; signals such as user location and freshness of content are taken into account to deliver results it "thinks" is most likely to satisfy the query.

Here is an infographic showing a timeline and history of these and many more algorithmic updates!


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