Google Panda Algorithm: Filtering Low Quality in Search

In February 2011, Google launched the Panda algorithm to combat black-hat SEO and spam sites. At that time, many users were complaining about “content farms” that were filled with worthless material. Panda was introduced to assign a quality score to each page—a score resembling the genuine opinion of real people about that page! This score later influenced Google’s rankings. In short, its goal was to eliminate low-quality content and boost sites that truly added value

What Is the Panda Algorithm?

The Panda algorithm is a content quality filter within Google’s ranking system. Its primary goal is to reduce the visibility of websites with weak, duplicate, or low-value content in search results. The algorithm identifies sites that produce unhelpful content and lowers their rankings.

Why Did Google Create Panda?

In 2010, the state of Google’s search results was somewhat chaotic. The overall quality had dropped, and numerous sites known as “content farms” were flooding the results. These were sites that produced a lot of low-quality content solely to rank high.

The issue began when Google, in 2009, released an update called “Caffeine” that greatly accelerated the indexing of content. However, it had a drawback: every piece of content—even those that weren’t particularly interesting—was quickly indexed.

At that time, Matt Cutts, one of Google’s managers, explained that this problem wasn’t pure spam—but it had a spam-like quality. In other words, there were sites that employed any trick possible to rank high despite offering minimal quality. That’s when Google decided to devise a solution and introduce the Panda algorithm to tackle this kind of content.

History of the Panda Algorithm’s Introduction

The Panda algorithm was first introduced on February 23, 2011. A day later, Google announced on its official blog that this update was “a very significant algorithmic change” affecting 11.8% of searches, and it was expected to noticeably improve search results.

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What Was the Goal of the Panda Update?

This algorithm was designed to lower the rankings of low-quality websites; namely, sites that:

• - Have copied or duplicate content,
• - Do not add any special value for the user,
• - Or, in general, do not offer any useful information.

Conversely, Panda helped high-quality sites achieve better rankings. This included sites that provided original content, in-depth research, and practical analysis.

Why Is It Called “Panda”?

Initially, some experts—such as Danny Sullivan (founder of Search Engine Land)—referred to this update as the “Farmer Update” because it mostly affected content farms. However, later Google announced that the official name of the algorithm is Panda; it was named after one of the engineers who originally proposed the idea.

Which Sites Fell Victim to Panda?

After the rollout of this algorithm, websites with weak content experienced a significant drop in their rankings. Analyses by SearchMetrics and SISTRIX revealed that the following sites were among the biggest losers:

• - wisegeek.com  
• - ezinearticles.com  
• - suite101.com  
• - hubpages.com  
• - buzzle.com  
• - articlebase.com  

Although some sites like eHow and wikiHow initially fared better, later updates by Google also penalized them. This eventually led Demand Media (the owner of eHow) to suffer losses of about $6.4 million in 2012.

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The Blow Panda Dealt to Black-Hat SEO

One of the most significant changes was the impact on article marketing. Before Panda, SEO specialists would publish low-quality articles on sites like ezinearticles.com in order to obtain backlinks. However, after this update, that method no longer worked.

Characteristics of the Sites That Experienced a Drop

The sites that suffered the greatest drop in rankings typically had the following issues:

• - Poor and unattractive design

• - Excessive and intrusive advertising
• - Content that is long-winded yet lacks substance
• - Incomplete research and superficial information
• - Low standards in editing and writing
• - Repetitive, spam-like phrases

The Panda algorithm was one of Google’s most significant changes, greatly impacting the world of SEO and content marketing. It forced low-quality sites aside while enabling sites with valuable content to thrive. After Panda, SEO was no longer just about building aimless backlinks—it increasingly focused on content quality and user experience.

What Do We Know About the Panda Algorithm?

When Google discussed the development of the Panda algorithm with Wired, Amit Singhal from Google explained that they sent test materials to human evaluators and asked them questions such as:

• - Would you feel comfortable giving your credit card information to this site?
• - Would you feel comfortable giving the prescription medications from this site to your children?

Additionally, Matt Cutts mentioned that the engineers designed a precise set of questions, including:

• - Do you consider this site trustworthy?
• - Would there be any issue if this site were published in a magazine?
• - Does this site have excessive advertising?

They then developed the Panda algorithm by comparing various ranking signals with human quality ratings.

Amit Singhal compared this process to finding an airplane in a cloudy sky that distinguishes the good from the bad.

In the end, Singhal published the following 23 guiding questions upon which the Panda algorithm was built:

1. - Do you trust the information presented in this article?
2. - Was this article written by an expert or a knowledgeable enthusiast, or is it superficial and lacking in detail?
3. - Does the site feature duplicate, overlapping, or excessive articles on similar topics with only minor keyword variations?
4. - Would you feel comfortable providing your credit card information to this site?
5. - Does this article contain spelling, stylistic, or factual errors?
6. - Are the topics in the article written based on the genuine interests of the site’s users, or is the site merely trying to guess what might rank well in search engines?
7. - Does the article offer original content, reporting, research, or insightful analysis?
8. - Does this page offer significantly more value than other search result pages?
9. - How much quality control is applied to the site’s content?
10. - Does the article present both sides of a story?
11. - Is the site recognized as an authoritative source in its field?
12. - Is the site’s content produced by a large number of writers or spread across a large network of sites, such that each page or site receives less attention and care?
13. - Is the article well-edited, or does it appear hastily and carelessly written?
14. - For health-related searches, do you trust the information on this site?
15. - Is this site recognized as a reliable source?
16. - Does this article provide a complete and comprehensive overview of the topic?
17. - Does the article offer insightful analysis or interesting information beyond the obvious?
18. - Is this the type of page you would want to bookmark, recommend to your friends, or share?
19. - Does this article contain excessive intrusive advertising that diverts your attention from the main content?
20. - Would you expect this article to be published in a magazine, encyclopedia, or book?
21. - Are the site’s articles short, unsubstantial, or lacking in useful details?
22. - Are pages produced with meticulous attention to detail, or do they appear to receive less care and attention?
23. - Do users complain about the pages on this site?

It is also important to consider which factors Google’s human quality raters use when evaluating low-quality content. This point about low-quality content is very significant.

Example

Many school and university students face challenges when writing their papers. Some of them, in order to save time and effort, resort to tactics such as:
- Buying articles online or outsourcing their paper writing.
- Fabricating information.
- Writing quickly without drafting or editing.
- Filling the paper with large images or distracting content that diverts attention.
- Copying entire articles from encyclopedias or paraphrasing their content by merely changing a few words or the sentence structure.
- Using common facts like “Argentina is a country. People live in Argentina. Argentina has borders.”
- Using a large number of words to express simple concepts, such as: “Pandas eat bamboo. Pandas eat a lot of bamboo. Bamboo is the best food for pandas.”

A Note on Machine Learning and Panda

In March 2011, the SEO By The Sea site introduced Panda’s engineer as the potential mind behind the algorithm bearing the same name.

In one of the articles, this engineer helped the writer explain how machine learning algorithms can be used to accurately classify user behavior on landing pages.

Although this article was not directly about the Panda algorithm, given the engineer’s involvement and the subject of the article, it is likely that the Panda algorithm is also based on machine learning.

Most professionals in the SEO industry have concluded that the Panda algorithm, through the use of machine learning, makes precise predictions about how humans evaluate content quality. What remains not fully clear is which signals in this machine learning algorithm are used to distinguish between low-quality and high-quality sites.