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Rand Fishkin, Wizard of Moz | @randfish | rand@moz.com
Ranking Signals of the Future
A look at what inputs search engines may adopt in the future
and how it impacts the marketing we do today.
Find These Slides Online at:
bit.ly/futuresignals
#1
Usage Data of Pages and Sites
10,000 visits/day
+50% growth last 6 months
3.7 pages/session
3 visits/unique user/month
6,000 visits/day
-10% growth last 6 months
1.2 pages/session
1.4 visits/unique user/month
Maybe I should send
searchers to the page w/
the greater visitor loyalty &
engagement.
Patent, Analysis on SEO by the Sea
Ha!
This type of ranking input could be
behind the strong performance of
popular brand sites on queries
where classic SEO elements are
lacking
Poor keyword targeting, crap relevance, few
links, but the sites probably have stronger
traffic/engagement than the competition.
Via Searchmetrics’Ranking Factors
Click-Through-Rate showed a 0.67
correlation
This May Explainthe High Correlationof CTR w/ Rankings
#2
Accuracy vs. Popularity of
Information
Nailed It! Rank ‘em
high, boys.
As Google’s research showed,
PageRank and accuracy of
information have a poor
correlation on the web.
By looking at multiple sets
of data across sites &
pages, an algorithm could
determine the consistency
of accuracy shown by a
site.
Paper from Google Researchers, Analysis by NPR
Consistently accurate facts could raise a site’s
rankings, especially in areas (like health) where
Google weights accuracy more heavily.
Less likely to rank.
More likely to rank.
#3
Query Structure as an
Anchor-Text-Like Signal
Many searchers using query structures in a
particular fashion could connect brands and
modifiers to keywords
Looks familiar
Popular searches around a brand
could indicate associations that
manifest in ranking inputs.
That ranking might be at partially, causal,
rather than mere coincidence.
#4
Brands as Entities, Entities
as Answers
More and more brands are becoming entries in
Google’s Knowledge Graph
IMO, these brand
dropdowns suggest an
implicit bias toward
accumulating brand
associations and showing
them off to searchers
In many competitive
SERPs, there seems
to be a correlation
between brand
dropdowns and
ranking higher.
Some brands get so tightly connected to
keywords, they become nearly analogous
with the query
Suggest also shows us brand queries that
earn strong connections to URLs
Even some generic queries bring back
branded domain suggestions
an experiment!
Let’s try
Call Out Your Answer:
What site would you expect to see
when you searched for this?
Yup.
Yup.
Yup.
Yup.
Weird.
Call Out Your Answer:
What site would you expect to see
when you searched for this?
Yup.
Yup.
Yup.
Yup.
Yup.
Yup.
Yup.
Call Out Your Answer:
What site would you expect to see
when you searched for this?
Maybe?
Yup.
Yup.
Yup.
Maybe?
Call Out Your Answer:
What site would you expect to see
when you searched for this?
Maybe?
Yup.
Yup.
Yup.
Yup.
Best Way to Rank in 2018?
“Yup.”Find a way to be the first
on everyone’s
mind.
#5
Tracing the Visit Path to an
Answer
Problem-solving on the web often looks
something like this:
Broad search Narrower search
Even narrower search
Website visit
Website visit Brand search
Social validation Highly-specific search
Type-in/direct visit Completion of Task
Google wants to do this:
Broad search
All the sites (or answers) you probably would
have visited/sought along that path
Completion of Task
If Google sees
that many people
who perform these
types of queries:
Eventually end
their queries on
the topic after
visiting:
The Ramen Rater
They might use the
clickstream data to help
rank that site higher, even
if it doesn’t have
traditional ranking signals
They’re definitely getting and storing it.
Google was just granted an interesting patent that
suggested a similar process
Patent Application from Google, Analysis by Bill Slawski
#6
Weighting Elements of User
Experience
Patent Application from Google, Analysis on SEOByTheSea
Ever since Panda, Google’s been
trying to surface not just quality
content, but “high quality
websites.”
If they aren’t already
doing it, Google’s at
least thinking about
how to measure UX
and rank sites that do
it better, higher.
#7
Replacing Flawed Humans w/
Deep Learning Machines
Jeff Dean’s Slides on Deep Learning
Are a Must Read for SEOs
Google’s Deep Learning system studied YouTube
clips and eventually invented its own
classification/concept of “cats”
Replace YouTube with the Web and cats with any given
search query, and it’s not hard to imagine Google creating a
deep learning ranking algorithm
Google knows there’s two, but based
on my footprint, it biases to the one
matching my behavior, past queries,
geography, etc.
In the future, even Google’s search
quality engineers may have no idea
why something ranks or whether
they’re using a particular factor in the
ranking algorithm.
The machine will simply ask “what algorithm
produces results that searchers engage with
best?” then make it.
strange path…
Google seems to be going down a
Total searchers, number of searchers, &
searches per searcher are all going up
Via RKG’s Quarterly Digital Marketing Report
Is Google sacrificing ad impressions to make searchers happier?
Are they willing to take away queries that provide revenue?
These searches could have created revenue, but Google’s
pre-empting w/ direct navigation to URLs
I am too.
Skeptical?
IMO, Google’s thinking long
term. They want addicted
searchers providing data
about themselves so they
can charge more per ad
unit.
Via Search Engine Land
Via RKG Report
Facebook has
shown Google that
more data about
users yields more
dollars per
impression and
click.
I think Google will chase better UX to almost any extent in order to keep
searchers & get data, even at the cost of their existing model.
Almost unreal
that Google
does this w/o
AirBnB paying
for an ad.
Via Tom Anthony’s Post
Google will chase better UX to almost any extent
in order to keep searchers & get data, even at the
cost of their existing model
My Guess:
Rand Fishkin, Wizard of Moz | @randfish | rand@moz.com
bit.ly/futuresignals

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