Discover everything there is to know about the Google Panda search engine. See why it was created, what we know about the algorithm, and a timeline.
Google Panda was initially released in February 2011 as part of Google's ongoing efforts to combat black hat SEO and webspam.
User worries about the growing power of "content farms" were common at the time.
The Panda algorithm, which was utilised internally and modelled by human quality evaluations and was added as a ranking element, was used to assign pages a quality classification.
Fast forward to 2021, and you can see how critical it was for Google to prioritise quality and user experience as its primary priority.
Everything you need to know about Google Panda is right here — more information about why it was launched, what you should know about the algorithm, and a chronology
Why Did Google Make Panda?
In 2010, the declining quality of Google's search results and the growth of the "content farm" business model became frequently discussed topics.
The late 2009 "Caffeine" update, which substantially improved Google's capacity to index content quickly, also added "some not so nice" content into their index, as Google's Amit Singhal later told Wired at TED.
According to Google's Matt Cutts, this new content issue isn't really a spam issue, but rather a question of "What's the very least that I can do that isn't spam?"
According to Read Write Web:
“By the end of [2009], two of these content farms – Demand Media [of eHow infamy] and Answers.com – were firmly established inside the top 20 Web properties in the U.S. as measured by comScore. Demand Media is the epitome of a content farm and by far the largest example of one, pumping out 7,000 pieces of content per day… The company operates based on a simple formula: create a ton of niche, mostly uninspired content targeted to search engines, then make it viral through social software and make lots of money through ads.”
The title on Business Insider in January 2011 said it all: Google's Search Algorithm Has Been Ruined, It's Time to Return to Curation.
They noted out in another article:
“Demand [Media] is turning the cleverest trick by running a giant arbitrage of the Google ecosystem. Demand contracts with thousands of freelancers to produce hundreds of thousands of pieces of low-quality content, the topics for which are chosen according to their search value, most of which are driven by Google. Because Google’s algorithm weights prolific and constant content over quality content, Google’s algorithm places Demand content high on their search engine result pages.”
These types of headlines undoubtedly affected Google, which responded by creating the Panda algorithm.
The Google Panda Update Has Been Released
Panda made his debut on February 23, 2011.
Google announced the modification in a blog post on February 24, stating that they "made a rather large algorithmic enhancement to our ranking - a change that visibly effects 11.8 percent of our inquiries."
The following was the stated goal of the update:
“This update is designed to reduce rankings for low-quality sites – sites which are low-value add for users, copy content from other websites or sites that are just not very useful. At the same time, it will provide better rankings for high-quality sites – sites with original content and information such as research, in-depth reports, thoughtful analysis and so on.”
Danny Sullivan, the founder of Search Engine Land, dubbed it the "Farmer" update at first. However, Google later revealed that it was internally referred to as "Panda," the name of the developer who devised the fundamental algorithm breakthrough.
Analyses of the "winners and losers" by Search Metrics and SISTRIX (among others) indicated that the sites that were struck the worst were quite familiar to everyone in the SEO business at the time.
Wisegeek.com, ezinearticles.com, suite101.com, hubpages.com, buzzle.com, articlebase.com, and others were among them.
The content farms eHow and wikiHow, in particular, performed better following the change. Demand Media lost $6.4 million in the fourth quarter of 2012 due to later modifications that harmed these more "acceptable" content farms as well.
The most noticeable change in the SEO industry was how hard it came down on "article marketing," which involved SEOs publishing low-quality articles on sites like ezinearticles.com as a method of link building.
The most highly hit sites also featured less appealing designs, more intrusive adverts, inflated word counts, low editorial standards, repetitious phrasing, faulty research, and didn't come off as helpful or trustworthy in general.
The Panda Algorithm: What We Know
When speaking with Wired about the algorithm's development, Singhal explained that they began by sending test documents to human quality raters who were asked questions such as "Would you be comfortable providing this site your credit card?" Would you feel safe giving your children drugs prescribed by this website?”
According to Cutts, the engineer had constructed "a rigorous series of queries, everything from 'Do you believe this site to be authoritative?' to "Do you consider this site to be authoritative?" Is it okay if this appeared in a magazine? Is there a lot of advertising on this site?'
They then constructed the system by comparing numerous rating signals to human quality rankings, according to the interview.
It's like finding a plane in hyperspace that divides the good from the terrible, according to Singhal.
Singhal later provided the following 23 questions as the algorithm's guiding questions:
- Would you put your faith in the facts stated in this article?
- Is this an article produced by an expert or enthusiast who understands a lot about the subject, or is it more superficial?
- Is there a lot of duplicate, overlapping, or redundant content on the same or comparable topics with modest keyword variations on the site?
- Would you feel safe giving this site your credit card information?
- Is there any grammatical, stylistic, or factual problems in this article?
- Are the themes chosen based on true reader interests, or does the site generate content by guessing what would rank well in search engines?
- Is there any original content or information in the piece, as well as original reporting, research, or analysis?
- When compared to other pages in the search results, does the page provide significant value?
- How much content is subjected to quality control?
- Is there a description of both sides of a storey in the article?
- Is the site a well-known authority on the subject?
- Is the content mass-produced or outsourced to a big number of creators, or distributed across a broad network of sites, with individual pages or sites receiving less attention or care?
- Is the essay well-edited, or does it appear sloppy or rushed?
- Would you trust the information on this site if you had a health-related question?
- When this site's name is mentioned, do you think you'll recognise it as a reliable source?
- Is this article a complete or comprehensive treatment of the subject?
- Is there any insightful analysis or fascinating information that isn't clear in this article?
- Is this a page you'd like to bookmark, share, or recommend to a friend?
- Is there an excessive amount of advertising in this article that detracts from or interferes with the core content?
- Do you think this article would appear in a printed magazine, encyclopaedia, or book?
- Is the content of the articles brief, unsubstantial, or otherwise missing in useful details?
- Are the pages made with great care and attention to detail, or are they made with less care and attention to detail?
- Would users be offended if they came across pages from this site?
It's also worth thinking about what Google's human quality raters were asked to think about. This is an important quote about low-quality content:Consider this example: Most students have to write papers for high school or college. Many students take shortcuts to save time and effort by doing one or more of the following:
- Buying papers online or getting someone else to write for them.
- Making things up.
- Writing quickly, with no drafts or editing.
- Filling the report with large pictures or other distracting content.
- Copying the entire report from an encyclopedia or paraphrasing content by changing words or sentence structure here and there.
- Using commonly known facts, for example, “Argentina is a country. People live in Argentina. Argentina has borders.”
- Using a lot of words to communicate only basic ideas or facts, for example, “Pandas eat bamboo. Pandas eat a lot of bamboo. Bamboo is the best food for a Panda bear.”
Panda, according to most SEO experts, works by employing machine learning to create accurate predictions about how humans would assess article quality. What is less obvious is which signals would have been used in the machine learning algorithm to decide which sites were of poor quality and which were not.
Google E-A-T and Panda:
Google's E-A-T principles, which emphasise on Expertise, Authority, and Trustworthiness, were added in its search quality criteria in 2014.
Marketers have been focusing on these ideas more and more since 2018.
Following Panda's lead, subsequent updates and key algorithmic adjustments have a strong focus on content quality and user experience.
And, like Panda, the emphasis is on staying away from:
- Content is thin and uninformative.
- There aren't enough reliable sources.
- Content that isn't trustworthy and links that aren't trustworthy.
Panda Recoveries on Google
Myths about Google Panda
Google's John Mueller stated in 2021 that duplicate material is not a ranking issue.
Is It Necessary to Delete Content in Order to Resolve Panda Issues?
“We don't recommend eliminating content in general for Panda, rather add more HighQ stuff,” Google's Gary Illyes said on Twitter in 2017.
On YouTube, John Mueller said the same thing:
“Overall, the quality of the site should be significantly improved so we can trust the content. Sometimes what we see with a site like that will have a lot of thin content, maybe there’s content you are aggregating from other sources, maybe there’s user-generated content where people are submitting articles that are kind of low quality, and those are all the things you might want to look at and say what can I do; on the one hand, hand if I want to keep these articles, maybe prevent these from appearing in search. Maybe use a noindex tag for these things.”
Google's response has always been to noindex or improve content, never to remove it totally unless it's a branding move.
In general, eliminating content should be considered in terms of your site's overall branding, not as a way to get rid of a Panda penalty.
User-Generated Content (UGC) and Panda
Panda does not expressly target user-generated content. Panda can target user-generated content, but it is more likely to affect sites that produce low-quality content, such as spammy guest posts or spam-filled forums.
If you hear something is "bad" or touted as a "Panda proof" solution, don't remove your user-generated content, whether it's from forums, blog comments, or article submissions. Instead, consider it from the standpoint of quality.
Many high-ranking websites rely on user-generated material, and removing that type of content would result in a big drop in traffic and rankings. Possibly comments on a blog post can help it rank and even be highlighted in a featured snippet.
Timeline
Panda almost definitely has the most comprehensive public record of update release dates. Part of the reason for this is because Panda was developed independently of Google's main algorithm, and as a result, content scores were only affected on or near the dates of fresh Panda updates.
While Panda was not directly included into Google's core algorithm, its data was updated weekly and rolled out progressively over the course of the month, ending the dramatic industry-wide consequences associated with Panda changes.
As a result, Panda announces his disappearance after 2017.
The numbering system is a little perplexing.
Core Panda algorithm updates should correspond to 1.0, 2.0, 3.0, and 4.0, but there is no update referred to as 3.0, and 3.1 was not, in retrospect, a core Panda upgrade.
Data refreshes, which updated the search results but not the Panda algorithm, were usually numbered as software updates would be (3.2, 3.4, 3.5, and so on). However, due to the large number of data refreshes for version 3 of the algorithm, this naming standard was abandoned for a time, and the industry simply referred to them by the total number of Panda updates (both refreshes and core updates).
Even after figuring out the naming convention, it's still unclear whether all of the smaller Panda changes were simply data refreshes or if some of them included new signals.
Regardless, the Panda update schedule is well-known, and it is as follows:
1.0 was released on February 23, 2011. The initial iteration of an unidentified algorithm update was released (12 percent of queries were affected), startling the search engine optimization industry and several major players, and thus putting an end to the “content farm” business model as it was known at the time.
2.1 (#2):11th of April, 2011. The Panda algorithm's core was updated for the first time. Additional signals, such as sites that Google users have blacklisted, were included in this version.
2.1 (#3): 9th of May, 2011. This was dubbed Panda 3.0 by the industry, but Google explained that it was simply a data refresh, as would be the case with future Panda 2.x releases.
2.2 (#4): 21 June 2011
2.3 (#5): 23 July 2011
2.4 (#6) The international date is August 12th, 2011. Panda was made available in all English-speaking and non-English-speaking countries around the world, with the exception of Japan, China, and Korea.
2.5 (#7) and Panda-Related Flux: September 28, 2011. Following this update, on October 5, 2011, Cutts announced to “expect some Panda-related flux in the next few weeks.” Confirmed flux dates were October 3 and October 13.
3.0 (#8): October 19, 2011. Google added some new signals into the Panda algorithm and also recalculated how the algorithm impacted websites.
3.1 (#9): November 18, 2011. Google announced a minor refresh, impacting less than 1 percent of searches.
3.2 (#10): January 18, 2012. Google confirmed a data refresh occurred on this date.
3.3 (#11): February 23, 2012. A data refresh.
3.4 (#12): March 23, 2012
3.5 (#13): April 19, 2012
3.6 (#14): April 27, 2012
3.7 (#15): June 8, 2012. A data refresh that ranking tools suggest was more heavy-hitting than other recent updates.
3.8 (#16): June 25, 2012
3.9 (#17): July 24, 2012
3.9.1 (#18): August 20, 2012. A relatively minor update that marked the beginning of a new naming convention assigned by the industry.
3.9.2 (#19): September 18, 2012
#20: September 27, 2012. A relatively large Panda update also marked the beginning of yet another naming convention. The industry recognized the awkwardness of the 9.x.x naming convention and recognized that updates to what they called Panda 3.0 could continue to occur for a very long time.
#21: November 5, 2012
#22: November 21: 2012
#23: The 21st of December, 2012. A data refresh with a little more oomph.
#24: The 22nd of January, 2013.
#25: 14th of March, 2013. This update was pre-announced, and tools indicate that it took place on this day. Cutts seemed to imply that this was the final update before Panda was fully integrated into Google's algorithm. But, as time went on, it became evident that this was not the case.
The premiere of “Dance” will take place on June 11, 2013. This isn't the release date of a new version. Even yet, Cutts explained the day that Panda wouldn't be put directly into the algorithm, but rather that it would be updated monthly with significantly slower rollouts than in the past.
“Recovery” was released on July 18, 2013. This update looks to be a minor fix to address some unusually harsh Panda behaviour.
May 19, 2014, 4.0 (#26). On this date, a substantial Panda update (affecting 7.5 percent of queries) was released. Given Cutts' warnings about gradual rollouts, most in the industry assume this was an upgrade to the Panda algorithm, not just a data refresh.
4.1 (#27): September 23, 2014. Another major update (impacting 3 to 5 percent of queries) included some changes to the Panda algorithm. Due to the slow rollouts, the exact date is unclear, but the announcement was made on September 25.
4.2 (#28): July 17, 2015. Google announced a Panda refresh that would take months to roll out. Due to the slow nature of the rollout, it’s unclear how substantial the impact was or precisely when it occurred. It was the final confirmed Panda update.
Core Algorithm Incorporation: January 11, 2016. Google confirmed that Panda had been incorporated into the core Google algorithm, evidently as part of the slow July 17, 2015 rollout. In other words, Panda is no longer a filter applied to the Google algorithm after it does its work but is incorporated as another of its core ranking signals. It has been clarified, however, that this doesn’t mean the Panda classifier acts in real-time.
Today is 2021 for the Panda.
Panda is already deeply ingrained in Google's machine learning algorithms, therefore Panda-related upgrades will no longer be considered separate.
Panda updates are no longer independent because Panda has become part of Google's core algorithm. In theory, ‘Panda' updates are related to core algorithm improvements, particularly those that focus on quality and content.
Next Steps
Panda's key themes should be remembered in 2021.
Focus on quality material for the user and their experience rather than black hat practises and spam links. These principles are still followed by Google's usage of machine learning and technology.
The Panda principles are still valid today, even though the term Panda does not appear.
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