Machine
learning is more of a statistics-based approach to AI than a lot of
people are used to. “Classic AI,” the type that people think about when
they think of the horn-rimmed glasses wearing, pocket-protector bearing,
MIT or Caltech classic nerd, is about as hip as the outfit they’d be
wearing. That was known as
“Symbolic” AI, because symbols were used for concepts, and many
researchers thought the brain itself was structured this way.
Neurobiologists actually joined the party in the 1990s; the field is
called Computational
ML
also applies to people who are accessing data on the internet. You know
that any networked GPS game (like Pokemon Go, perhaps) is a
geo-specific search, possibly geo-spatial. Geo-spatial means coordinates
mapped onto a sphere, with a height component. It’s increasingly common
for databases to include geo-search capacities right in their query
languages (for example, PostgreSQL stands out here).
OK, so what does ML mean to SEOs? Keywords will become less effective over time. Keywords are the SEOs most influential friend right now, and a lot of less knowledgeable SEOs rely on them exclusively (to the detriment of themselves and their clients).
Geoff
Hinton and Jeff Dean at Google have said that algorithm updates Panda
and Penguin were based on machine learning systems they designed. The
arms race of search algorithms is guaranteed to always put pressure,
even the vanguard, to constantly innovate. And
as the core ranking systems of search engines get updated with newer
systems, they will continue to get exponentially smarter. SEOs
themselves should not become machines, but they must harness them.
An Ever-Evolving Search Algorithm
With
that in mind, it seems clear that Google’s ultimate aim is to apply
machine learning so that its search algorithms will be able to learn and
update themselves automatically, and it’s here where the real impact
will be felt.
The
most noticeable impact, from SEO’s perspective, is that there would
likely be much fewer updates such as last year’s “Mobilegeddon” when
Google started ranking sites on smartphones and tablets according to
their “mobile friendliness.” That major update was implemented by
humans, and happened suddenly and all at once. With a machine
learning-based search algorithm, it’s likely to evolve more gradually
instead of making such sudden changes.
Aside
from that, machine learning should be a welcome boon for reputable
SEOs, as it will effectively give them a license to continue doing the
good work they’ve already started. Google has long stated it requires
two things from websites – that they meet its technical requirements,
and they also serve as great resources, which means they should contain
lots of relevant and knowledgeable content.
Google
has always said that websites should first and foremost try to serve up
useful content, instead of just keyword-stuffed fluff. It’s likely that
machine learning will soon make it even more critical that those
requirements are met. Indeed, the evidence suggests that keyword
stuffing has already become much less important, as a recent MarketingProfs study points out:
The
correlation between keywords and high search rankings has decreased
across the board. More and more high-ranking sites are not using the
corresponding target keyword in the body, description, or links, the
analysis found. Sites are also using keywords less in URLs themselves,
with only 6 percent doing so in the 2015 study.
SEOs
have long used keyword targeting as a central part of their strategies,
but with the introduction of machine learning, keywords simply won’t be
necessary anymore. Machine learning means Google will be better be able
to understand which are the most authoritative sites for any search
phrase, regardless of if they actually use that specific phrase or not,
because it will soon be able to understand the actual content on each
site.
There’s a reason why Google keeps on pumping out major updates such as Panda
and Pigeon. And it may come as a shock to some, but Google doesn’t do
it just to frustrate SEOs (that’s just a bonus for them). Rather, it’s
all about Google cementing its dominant market share in search, by
serving up the best possible results for customers, so they don’t need
to look elsewhere. Every single algorithm update has been done with this
goal in mind, and the introduction of machine learning has been done
for the same reason. Indeed, every search is individualized now, so that
when you see results, they are unique to you, but you don’t know why.
As
such, maybe all SEOs need to worry about is ensuring their websites are
packed with high-quality content that users want to reach and share
with their friends. No matter what role machine learning comes to play
in Google’s search rankings, that will never change.
