2013 Search Ranking Factors by Matthew Peters
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Transcript of 2013 Search Ranking Factors by Matthew Peters
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SEARCH
RANKING
FACTORS
2013
#
Matthew Peters
Moz
@MattTheMathMan
#SMX #13B
October 1, 2013
#
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@mattthemathman
Lead Data Scientist at Moz
Data science is responsible for all of
Moz’s metrics: Page/Domain/Social
Authortity, etc.
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@mattthemathman
Different feature types include: On-page, links, anchor text, social
signals and properties of the URL
URL www.mrqe.com
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@mattthemathman
Different feature types include: On-page, links, anchor text, social
signals and properties of the URL
On-page
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@mattthemathman
Different feature types include: On-page, links, anchor text, social
signals and properties of the URL
Links
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@mattthemathman
Different feature types include: On-page, links, anchor text, social
signals and properties of the URL
“movie reviews”
Anchor
Text
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@mattthemathman
Different feature types include: On-page, links, anchor text, social
signals and properties of the URL
“movie reviews”
Anchor
Text
Social
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@mattthemathman
Which factors are important?
What Google says
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@mattthemathman
Which factors are important?
What’s in the algorithmWhat Google says
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@mattthemathman
Which factors are important?
What’s in the algorithmWhat Google says
What SEOs say
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@mattthemathman
Which factors are important?
What’s in the algorithmWhat Google says
What SEOs say
Characteristics of sites
that rank well
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@mattthemathman
Survey
Thanks to everyone who participated and Cyrus Shepard and Matt Brown for organizing
120 professional SEOs
surveyed in mid-June
2013
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@mattthemathman
Survey
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@mattthemathman
Survey
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@mattthemathman
Correlations
• 14,000+ keywords from Google Adwords, all
categories/search volumes
• Top 50 de-personalized, de-localized results from
Google US
• Mean Spearman Correlation – compute for each
keyword then average
• Measures extent to which increases in one factor are
related to rank
• Correlations between -1 and 1. Values of 0.1 - 0.3
are common.
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@mattthemathman
"Correlation is not causation but it sure is a hint" -
Edward Tufte
Links
Correlation and causation
Higher
rank
??
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@mattthemathman
"Correlation is not causation but it sure is a hint" -
Edward Tufte
Links
Correlation and causation
Higher
rank
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@mattthemathman
"Correlation is not causation but it sure is a hint" -
Edward Tufte
Links
Higher
rank
Correlation and causation Correlation, but causation?
Higher
rank
More words
on page
??
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@mattthemathman
"Correlation is not causation but it sure is a hint" -
Edward Tufte
Links
Higher
rank
Correlation and causation Correlation, but causation?
Higher
rank
Higher
qualityMore words
on page
??
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@mattthemathman
"Correlation is not causation but it sure is a hint" -
Edward Tufte
Links
Higher
rank
Correlation and causation Correlation, but causation?
Higher
rank
Higher
qualityMore words
on page
Links
??
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@mattthemathman
"Correlation is not causation but it sure is a hint" -
Edward Tufte
Links
Higher
rank
Correlation and causation Correlation, but causation?
Higher
rank
Higher
qualityMore words
on page
Links
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@mattthemathman
Survey: Overall
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@mattthemathman
Survey: Links
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@mattthemathman
Correlations: Links
Overall PA our highest correlated factor.
Page link correlations higher then domain.
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@mattthemathman
Correlations: Anchor Text
Partial and exact match have same correlation.
Internal anchor text correlations significantly lower then external.
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@mattthemathman
Survey: On-page keyword usage
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@mattthemathman
Correlations: On-page keyword usage
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@mattthemathman
Relevance vs Ranking
See http://moz.com/blog/determining-relevance-how-similarity-is-scored
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@mattthemathman
Relevance vs Ranking
Relevance
See http://moz.com/blog/determining-relevance-how-similarity-is-scored
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@mattthemathman
Relevance vs Ranking
Relevance
Ranking
1
2
See http://moz.com/blog/determining-relevance-how-similarity-is-scored
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@mattthemathman
Survey: On-page Keyword Agnostic
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@mattthemathman
Correlations: Site speed
Zoompf to provided the speed data.
Response time has negative correlation, but total load time does not!
See: http://moz.com/blog/how-website-speed-actually-impacts-search-ranking
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@mattthemathman
Speed and Users
Jonathon Colman: http://www.slideshare.net/jcolman/seo-site-speed-and-battlestar-galactica-searchfest-2012-11735155
• 40% of customers will abandon any site
that takes longer than 3 seconds to load
• Conversion rate drops by 7% for every 1
second of load time
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@mattthemathman
Survey: Brand metrics
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@mattthemathman
Correlations: Brand metrics
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@mattthemathman
Correlations: Brand metrics
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@mattthemathman
Survey: Exact/partial match domain
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@mattthemathman
Correlations: EMD/PMD
Query: “adidas sneakers”
Exact Match Domain (EMD): www.adidassneakers.com
Partial Match Domain (PMD): www.adidas.com
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@mattthemathman
Exact match domain over time
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@mattthemathman
Exact match domain over time
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@mattthemathman
Exact match domain over time
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@mattthemathman
Exact match domain over time
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@mattthemathman
Exact match domain over time
Removal of low
quality EMDs??
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@mattthemathman
Survey: Social
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@mattthemathman
Correlations: Social
Google +1’s second highest correlation metric (behind PA)!
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@mattthemathman
Correlations: Social, 2013 vs 2011
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@mattthemathman
+1’s are not used in ranking
Similar to Facebook Shares, Google +1’s are not used in ranking:
Matt Cutts: https://news.ycombinator.com/item?id=6243451
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@mattthemathman
Google+ provides SEO benefits
Followed links, relevant anchor text, priority crawling
Cyrus Shepard: http://moz.com/blog/google-plus-correlations
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@mattthemathman
Correlation vs Causation revisited
Higher
rank
Higher
qualityMore +1’s,
Shares or
Tweets
Links
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@mattthemathman
Multivariate correlations
Spearman correlations between links and social shares
Page level links and social shares are correlated
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@mattthemathman
Partial correlations
Partial correlations controlling for links, anchor text, keyword usage
A simple linear model with a handful of factors removes much of the
social correlation with search position.
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@mattthemathman
Overall algorithm
Link factors still very important, followed by on-page page.
SEO’s don’t think Social important, but it has high correlation.
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@mattthemathman
1. Quality, authorship,
structured data,
social all predicted to
increase in
importance.
Future predictions
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@mattthemathman
1. Quality, authorship,
structured data,
social all predicted to
increase in
importance.
1. EMD, paid links,
anchor text expected
to decrease.
Future predictions
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@mattthemathman
Final caution
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