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How Does Machine Learning & Artificial Intelligence Affect SEO? - Nashville SEO
How Does Machine Learning & Artificial Intelligence Affect
SEO? - Nashville SEO
What Does Machine Learning & Artificial Intelligence Mean For SEO?
Google and other search engines use machine learning and artificial intelligence to present a user
with the most relevant search. How does this affect SEO in the future?
You may have asked yourself at a time, How does Googles search algorithm work? Why is my
website not ranking? Well, youre right there with thousands of other businesses who have been
stumped by the search engine giant. How and why Google works the way it does are important
questions to ask yourself when trying to rank your website. Its crucial to keep in mind that SEO isnt
just a bunch of fairy dust. Its also not simple. There are many essential elements to take into account
when trying to rank your website. Just remember its not an overnight process.
A Simpler Time for SEO
Lets take a step back about five to ten years. An archaic time for SEO and internet marketing. The
term internet marketer back in 2005 was almost derogatorily segregating a clique of spammers,
phishers, and anybody who wanted to shove product in your face online. Heres the kicker, it worked.
Many people could rank their site within days simply by spamming, keyword stuffing, and building
completely irrelevant backlinks.
The Downfall of Black-Hat Techniques
Moving to 2012, Google decided to make semantic search more relevant and announced use of AI &
ML. This means no more spam content, no more links that were unrelated to your website, no more
ghost pages & island pages on your site, and the downfall of keyword stuffing, metadata
manipulation, and irrelevant traffic manipulation.
How Googles Algorithm Works Now
Googles search algorithm is broken down into many components. This is the only way Google can
stay on top of the webs 60 Trillion+ individual web pages. Google uses artificial intelligence to
discover elements that, in a way, create a flow of ranking factors. So how can we really understand
how Google decides to rank a website? We start with Crawling & Indexing
Understanding How Google Works to Perspicaciously Optimize Your Website
Crawling & Indexing
Google navigates the web by crawling This means following internal website links from page to
page. As a site owner or webmaster, you can choose which pages you want Google to crawl, or you
can deindex your entire site with robots.txt if you wish. Google uses their bot (googlebot) to sort
pages by content, links, anchor text, and more.
Formulas & Algorithms
This is where it gets interesting. Google writes programs and formulas to deliver the best search
results possible to the user. Algorithms work by looking for clues to understand relevantly what it is
that youre searching for, then they use these components to pull relevant results from the index.
After Google has used crawling, formulas, and algorithms, they decide how to rank a website. Now,
Google has an unknown amount of ranking factors for a website, but we know its pretty high. I can
most likely list over 250 of them. All of these also have their own factors within. For the sake of your
sanity, Im only going to mention the top 5 ranking factors. These are open to interpretation as well.
Backlinks & Social Signals
I realize that backlinks is a very broad factor. There have also been debates about backlinks losing
their value. Though, we have seen time and time again that a website with a great link profile and
the authority of sites linking to them, seem to take precedent in rankings. This means that you need
to build backlinks at a natural pace that are also relevant to your site in some way. If you are a
company that sells cats, and your content on your website is all about cats, you probably shouldnt
have a backlink from a website that is all about dogs. Google will not see that as relevant to your
company, and like discount the link or possibly penalize you for it (if there are enough bad links).
This is part of Googles AI process to decipher content, photos, and more. Social signals are also very
important for Google to see that users are engaging in your brand.
See This Video On Backlinks
More backlink factors:
RelevanceVariety & Unnatural BuildingAuthority (DA/PA of linking site)IP & Subnet
DiversificationLoss of BacklinksContent
You may often here the phrase content is king when it comes to SEO & Digital Marketing. And as
previously stated, ranking elements have factors of their own associated with them. Content doesnt
just mean throw 500 words on a page with a picture. Google also now uses keyword phrases,
frequency, and relevance to determine the quality of your content. This doesnt mean length isnt
More Content factors:
Internal LinkingUsers Commenting & InteractionDuplicate ContentAuto Generated ContentContent
Updates Anchor Text Profile
Anchor text is the text that creates a hyper link. You most likely use this often when creating your
backlinks (even if its accidental). The anchor text you use when creating backlinks is a critical part
of linking. Google also uses this to determine what keywords you are trying to optimize for.
More Anchor Text factors:
Keyword DiversityUsers Commenting & InteractionDuplicate ContentAuto Generated
ContentContent Updates Onsite SEO
Onsite is an important part of your SEO strategy. The simplest explanation of onsite is optimizing for
your keyword. This consists of title tags, metadata, H1 tags, and more. Its also important to
understand why you are optimizing that title for your keyword, and how to generate it in a way that
gives a positive user experience. If your keyword is credit repair, you wouldnt want to just have your
title tag as Credit Repair Company. You want to give Google and your users an explanation of your
business with onsite.
More Onsite SEO factors:
Friendly URLsNumber of PagesKeyword Frequency In ContentImage Optimization (Alt & Title)Over
Using technical SEO to show Google who you are, and what your business offers is also very
important. This is done by optimizing for broken links, HTTP status code errors, schema &
microdata mark-up, mobile friendly, page speed load time, and more. The technical side of SEO is
more for search engines than your users. This lets search engines know that your site is complete for
lack of a better word. Learning the basics of Googles Search Console will help you with a lot of this
side of things.
See This Video On Search Console
More Technical SEO factors:
Robots.txt fileXML SitemapDomain History &
StatusBreadcrumbs & SitelinksCode
Now that we understand a little better how
Google works, we can determine what about
our site is initiating or devastating your overall
rankings. The next step would be
understanding how users view your site, as
well as Google, to give the best possible experience for both search engines and users. Google is
determined to give the best possible result to the user. This is how Google uses neural networks to
attempt to ascertain what a user wants to see.
How does Google use machine learning to calculate the best search result?
This is a great question to ask ourselves. Understanding how Google uses these methods can help us
decide what we have to do to (hopefully) rank for our keyword. Many search engines use these
methodologies for their algorithms. They use machine learning and artificial intelligence for pattern
detection in many ways to understand what the user is searching for.
It may help to understand how neural networks work, and how computers learn things. The flow of
information in an Artificial Neural Network (ANN), works in two ways which is similar to an organic
brain. When it is being trained, informational patterns are fueled into the network by input units.
This triggers layers of concealed units which in turn reach the output units. For an artificial network
to learn, an element of feedback must be involved similar to how our children learn between right
and wrong by their parents.
So how does Google use this process of feedback and backpropagation for search? There are many
ways Google can use this process to antiquate previous search techniques to reveal a better system
for their users. Most importantly is how they user correlation between multiple variables to predict
the outcome of future results. ANNs are fed scripts that can be used to supervise learning on past
outcomes to hypothesize a prediction. Combining variables is also important mathematically. There
must be a distinction between multiple variables to provide an outcome. Decision learning works
easiest with the least amount of possible outcomes. Outcomes are predicted by layers. If you want to
learn a bit more of the technical side of things, please visit this paper by Google and watch this video
by Stanford. Google tells us that they use 4 main layers in their machine learning process (cited from
Speech Recognition Google has developed and officially launched a new system that uses a muilt-
layered deep learning neural network to cut down on errors by 25 percent. The whole area has still
seen a hand-engineered approach to structure that looks for nouns, verbs, something to indicate its
a question, etc., but Google is still working on developing a more sophisticated approach to natural
language.Natural Language & Search - If you think about a Google search, you type words or
phrases and get back relevant results. It seems simple. However, machines have always just
matched keywords; when you type, how to change a tire, it looks for results with that phrase or
synonyms like repair. Researchers are now trying to advance machines to actually understand
natural human language instead of approach it like a bag of words. This will help machines generate
answers to more complex questions like, Whats a school near me that would be good for my
daughter with special needs?Sentence & Shape Translation - Every single sentence has a completely
unique shape, and similar sentences have similar shapes. For example, the shapes of the following
two sentences would be extremely close: Id like to change my tire. I want to repair my tire. Identical
sentences expressed in different languages have identical shapes. So, once a machine knows the
shape of a sentence in one language, it can use that to look for the same shape in any other to get
the translation.Imagine Captioning - Theyve trained a neural network to recognize images very well
by feeding it good examples. The image is the input and the caption is the output, and the more
images they feed it, the better the captions become.
Google has also given us access to their Prediction API. The Prediction API provides pattern-
matching and machine learning capabilities. Given a set of data examples to train against, you can
create applications that can perform the following tasks:
Given a user's past viewing habits, predict what other movies or products a user might
like.Categorize emails as spam or non-spam.Analyze posted comments about your product to
determine whether they have a positive or negative tone.Guess how much a user might spend on a
given day, given his spending history.
Please see this large scale deep learning Slide Share by Jeff Dean for more information.
See this Slide Show on Machine Learning
To learn more about how machine learning works for search engines, please read Googles research
How does Machine Learning & AI affect SEO?
I think one of the most important questions to ask here is this: Does machine learning and artificial
intelligence affect SEO in a negative or positive way? My philosophy on this may be different than
other people in the SEO world, but personally I believe this helps us. If you are using White-Hat SEO
techniques, you shouldnt have any reason that youre not ranking on Google. Optimizing onsite and
generating great, sharable, user engaging content is what Google really wants to see. The rest
should not be manipulated. It may take you a while to rank, but let it come naturally. This is what
will help ensure your ranking to be static in Google. Remember, Google doesnt like Spam!
The only specific negative I see in this is that eventually, Googles algorithm may grow at a pace that
even Google developers cannot keep up with what it is doing. At this point, we would have to work
on generating experiments as to what ranking factors truly matter to Googles brain. We may
eventually finding that SEO & site optimization are much more difficult than we could anticipate.
This also means that it could become easier. In my opinion, its easier to give users exactly what
theyre looking for than to give search engines exactly what theyre looking for. If you have great
content and a great user experience, I wouldnt worry as much about what Google wants. Your
customers will be happy! And well, customers being happy is never a bad thing. Here is another
great resource for SEO & Digital Marketing.