Google’s blog post on how AI powers search results and what it means for SEO – Marie Haynes

Google is understanding language better than ever before

Pandu Nayak says, “Thanks to advancements in AI and machine learning, our Search systems are understanding human language better than ever before.” The more Google understands language, the better they are at determining what it is that the searcher really wants and connecting them with the right content. 

In the early days of Search before Google used advanced AI, they relied heavily on matching keywords in queries with keywords on pages to determine relevancy. Over time Google likely began to introduce some feature engineering into the mix. Dawn shared with me this video in which Google engineer Paul Haahr talks about how Google has improved search over the years. For example, by learning to interpret the order of words, they improved their systems beyond simple keyword matching. 

Haahr is speaking about how Google has improved search. He discusses some case studies demonstrating how search has evolved and says he realized that all of them are in one way or another about language. When it comes to search, “language is really important to understanding what we do.” 

In the last few years as AI, and in particular unsupervised learning have been added to Google’s capabilities, they are getting better and better at understanding what it is the searcher is trying to accomplish and in turn, connecting them with relevant, helpful and trustworthy content. 

As Google improves in this area, the focus has become less and less about matching individual keywords. In better understanding a searcher’s query, Google’s algorithms can now look at things like whether the query is ambiguous, what the intent is behind the query, whether there are contextual details about the user that matter such as their location, and more. As language on pages is better understood, this helps Google connect the most relevant content with the query.

It also becomes harder, if not impossible, to game rankings via traditionally used SEO methods, especially for sites operating in verticals in which they have no real life subject matter expertise or authority. In the past, a good SEO could make content rank even if it wasn’t the best of its kind. Paid links from the right sources could trick Google’s algorithms into considering content as authoritative. When you combine authoritative links with good on-page optimization, success has historically followed. 

I’m not saying that link building is dead, but I do believe that Google is getting better at determining which links they should count as authoritative recommendations in their algorithms. Dawn had some interesting thoughts to add here: “One could argue simple classification algorithms can determine easily nowadays whether a link is paid, spam, or poor quality when enough ‘guest blog posts’ have been seen in data for example.  The more data, the more the probability accuracy is likely to grow in classifying whether a link is genuine and valuable (e.g. editorially added on a voluntary basis to indicate a worthwhile source)”.

Links do still matter, and Google has not denied this, albeit they do claim content can rank without links. From Dawn, “Hardly surprising, given the Power Law distribution curves of the internet overall and the Zipfian nature of this.” (Note, you can, and probably should read more about Zipfs law and its importance to SEO in Dawn’s presentation. The vast majority of content on the web is in the ‘tail of the web’ where links may not be as important .  As per Dawn, “However, in the most competitive head areas of the web links are likely still a strong differentiating factor.”

A 2020 Perficient Digital study showed that links can help drive rankings, but really only links from authoritative sites. I have theorized for some time now that Google is adding more nuance to how they use PageRank in their algorithms as they get better at understanding language.

We know that PageRank and authority are closely related. In Google’s documentation on how they fight disinformation, they tell us that PageRank is one of the signals that correlates with trustworthiness and authoritativeness (two components of E-A-T).

PageRank may be the best known signal Google uses to determine authority, but it is not the only one! For years, it was the most important metric, at least as far as we know. Perhaps it still is, but personally, I think Google has additional ways to determine authoritativeness. I think a lot of how E-A-T is measured on the web relates to Google gathering and understanding entity information. 

Dawn shared this video from a 2015 Stanford lecture in which Google’s Xin Luna Dong discusses how algorithms can take entity information on the web and do cross checking and gauge truthfulness. “Validity determination based on probability takes place to estimate confidence on information discovered in web pages.

I’ll share more on entities soon.

My thought is that links are still important to many parts of Google’s algorithms, but when it comes to authority, Google is learning to understand the web beyond the flow of PageRank. Five years ago (which is quite a while in terms of search innovation), Search Engine Land wrote about authority, saying, Google has no single authority metric but rather uses a bucket of signals to determine authority on a page-by-page basis. They stated that while links were still important, AI, and in particular RankBrain, was another important factor.