One of the most impactful updates at Google was the Panda Update, released into the world in February of 2011, and affecting almost “12%” of all search results. In a Wired interview of Google’s Amit Singhal and Matt Cutts, TED 2011: The ‘Panda’ That Hates Farms: A Q&A With Google’s Top Search Engineers, the name of the update was revealed to be taken from a Google Engineer that played a significant role in its development:
Wired.com: What’s the code name of this update? Danny Sullivan of Search Engine Land has been calling it “Farmer” because its apparent target is content farms.
Amit Singhal: Well, we named it internally after an engineer, and his name is Panda. So internally we called a big Panda. He was one of the key guys. He basically came up with the breakthrough a few months back that made it possible.
In January of 2011, Google’s Matt Cutts published a blog post on the Official Google Blog, titled Google search and search engine spam, which told us:
One misconception that we’ve seen in the last few weeks is the idea that Google doesn’t take as strong action on spammy content in our index if those sites are serving Google ads. To be crystal clear:
- Google absolutely takes action on sites that violate our quality guidelines regardless of whether they have ads powered by Google;
- Displaying Google ads does not help a site’s rankings in Google; and
- Buying Google ads does not increase a site’s rankings in Google’s search results.
These principles have always applied, but it’s important to affirm they still hold true.
I’ve been seeing a few long posts lately that list ranking signals from Google, and they inspired me to start writing a series about ranking signals over on Google+. Chances are good that I will continue to work on the series there, especially since I’ve been getting some great feedback on them.
This post includes the first seven, plus an eight signal – the Co-Occurrence Matrix described in Google’s Phrase-Based Indexing patents.
I’m also trying to include links to some of the papers and patents that I think are among some of the most important to people interested in SEO that support the signals that I’ve included.
Here are the first 8 signals:
When I’m looking for something at a search engine, I will often start out with a particular query and then depending upon the kinds of results I see I often change the query terms I use. It appears that Google has been paying attention to this kind of search behavior from people who search like me. A patent granted to Google earlier this month watches queries performed by a searcher during a search session, and may give more weight to the words and phrases used earlier in a session like that, and might give less weight to terms that might be added on as a session continues.
This patent seems like part of an evolution of algorithms from Google that has brought us to their Hummingbird update.
On April 9th, 2009, many people developed an interest in speeding up their websites, after reading a post on the Google Webmaster Central Blog – Using site speed in web search ranking.
On the same day, Google’s Matt Cutts published Google incorporating site speed in search rankings on his blog. These posts introduced site
speed as a ranking signal that Google would be using.
Matt Cutts told us that it wouldn’t be an earth shattering signal. And that it might not have an impact within a large set of rankings. But he did stress that speed has benefits other than just ranking, including improved user experience.
Many words found on a web page are much easier to understand given the context of the page itself, as described in a Google patent granted last week. For example, take the word “bank,” which can mean a financial institution, one side of a river, or the turning of an airplane. Without the context of the word itself within the setting of a page, it’s fairly impossible to determine what the meaning of the word might be with any certainty.
I usually include a section within site audits that dealt with the structure and organization of a site. This looks at how things are connected together by virtue of links from one page to another, and the use of anchor text to describe those sections and sub-sections within the sections.
It explores the use of a hierarchy of categories nested into subcategories, and sometimes into even smaller groupings of categories, and how those might be linked together.
The example for the post I was writing for today appears to have been hijacked by the Simpsons. They made an apology to Judas Priest, after referring to the band as a death metal band. The image below is from a Guardian news article on the apology which is presently highly ranked on a search for the word “Judas”. See the search results below:
I wanted to show a set of search results from Google that may have been based upon Google matching the topic of a post rather than keywords, which might help improve the relevance of search results for videos and media rich results, according to a Google patent granted on the last day of 2013, which uses that example.
When we talk about how web sites are related, it’s not unusual for us to talk about links between sites and pages. Google pays a lot of attention between such links, and they are at the heart of one of its most well known ranking signal – PageRank. PageRank is now more than 15 years old, predating the origin of Google itself in the BackRub search engine.
Google is exploring other signals that may be used to rank pages in search results, including social signals that may result in reputation scores for authors, in relationships between words that might appear together on pages ranking for the same queries, and in relationships between pages that show up in the same search results and in the same search sessions. The Google paper presented at an October 2013 natural language processing conference, Open-Domain Fine-Grained Class Extraction from Web Search Queries (pdf), provides some interesting hints at a possible Google of the future.
Google also seems to be very interested in building a knowledge base of concepts that better understands things like what different businesses or entities are ‘Known for’ or by defining entities better in ‘is a’ relationships. Sometimes pages for specific entities show up at the top of search results because they seem to be the page that people are looking for when they include that entity within a query, like the first two results on a search for [Roald Dahl], as seen in the image below: