The Google Panda algorithm stripped search results pages (SERPs) of spammy, poorly constructed content, allowing higher quality websites to rise to the top. Google launched Panda early in 2011, and it screened out thin and low-quality websites from its search results. That was the beginning of a series of major quality control checks.
The Panda algorithm’s primary target was content farms. These are sites that produced low-quality content but ranked well simply because of their sheer volume. As Google strives to provide high-quality results for an optimal user experience, this was a huge concern. Content spammers were dealt two black eyes through the Panda algorithm, which effectively removed content farms.
Since its launch, Google’s algorithm has become one of its core ranking factors. The system is constantly being improved and will become increasingly sophisticated in its evaluation of what is considered low-quality content, driving up the level required by websites to rank well.
Google Panda: Why It Was Created
There was a lot of talk about the declining quality of Google’s search results and the rise of the “content farm” business model in 2010.
According to Amit Singhal, who spoke at TED, Google’s “Caffeine” update of late 2009 accelerated content indexing and introduced “not so good” content into their index.
During an interview with Wired, Matt Cutts explained that the new content issue was not really a spam concern but was instead a matter of “What’s the bare minimum I can do without being spammy?”
It’s time to move back to curating, says Business Insider in a January 2011 headline: Google’s Search Algorithm Has Been Ruined.
There is no doubt that headlines like these significantly influenced Google, which responded by developing the Panda algorithm.
How Does the Panda Algorithm Work?
Google discussed the development of the algorithm with Wired, in which Singhal explained that they sent test documents to human quality raters who were asked questions such as “Would you feel comfortable giving this site your credit card?”? Do you feel comfortable giving your children medicine prescribed by this site?”
According to Cutts, the engineer had prepared a detailed set of questions. Are you of the opinion that this site is authoritative? Would it be okay if it appeared in a magazine? Is there too much advertising on this site?’
The interview described how they developed their algorithm by comparing different ranking signals to human quality rankings. He described it as finding a plane in hyperspace that separates the good sites from the bad.
Singhal used the following questions in developing the algorithm:
- Can you trust the information presented in this article?
- Does this article come from an expert or enthusiast who knows the topic well, or is it shallower?
- Is the site overflowing with duplicate, overlapping, or redundant articles with slightly different keywords on the same or similar topics?
- Do you feel comfortable providing your credit card information to this site?
- Does this article contain any spelling, stylistic, or factual errors?
- What topics are chosen based on the interests of the site’s readers, or is the site trying to guess what might rank well in search engines?
- Does the article contain any original content or information, original reporting, original research, or original analysis?
- If the page is compared to other search results, does it provide significant value?
- Does the content undergo quality control?
- Does it present both sides of the story?
- Is the source recognized as an authority in its field?
- Are the pages and sites mass-produced or outsourced to a large number of creators, or are they spread across a wide network of sites without individual care or attention?