Google is PublicAbout How They
Use MLin Image Recognition & Classification Potential ID Factors (e.g.color,shapes,gradients, perspective,interlacing,alttags, surroundingtext,etc) Training Data (i.e.human-labeledimages) Learning Process Best Match Algo
Machine Learning in Search Could
Work Like This: Potential Ranking Factors (e.g.PageRank,TF*IDF, TopicModeling,QDF,Clicks, EntityAssociation,etc.) Training Data (i.e.good&badsearchresults) Learning Process Best Fit Algo
The Machines Learn to Emulate
the Good Results & Try to Fix orTweak the Bad Results Potential Ranking Factors (e.g.PageRank,TF*IDF, TopicModeling,QDF,Clicks, EntityAssociation,etc.) Training Data (i.e.good&badsearchresults) Learning Process Best Fit Algo
Googlers Don’t Feed in Ranking
Factors… The Machines Determine Those Themselves. Potential Ranking Factors (e.g.PageRank,TF*IDF, TopicModeling,QDF,Clicks, EntityAssociation,etc.) Training Data (i.e.goodsearchresults) Learning Process Best Fit Algo
The Query Success Metrics Will
BeAll That Matters to the Machines Long to Short Click Ratio Relative CTR vs. Other Results Rate of Searchers Conducting Additional, Related Searches Metrics of User Engagement on the Page Metrics of User Engagement Across the Domain Sharing/Amplifcation Rate vs. Other Results
The Query Success Metrics Will
BeAll That Matters to the Machines Long to Short Click Ratio Relative CTR vs. Other Results Rate of Searchers Conducting Additional, Related Searches Metrics of User Engagement on the Page Metrics of User Engagement Across the Domain Sharing/Amplifcation Rate vs. Other Results If lots of results on a SERP do these well, and higher results outperform lower results, our deep learning algo will consider it a success.
And Optimizing More for Searcher
Outputs High CTR for this position? Good engagement? High amplification rate? Low bounce rate? Strong pages/visit after landing on this URL?These are likely to be the criteria of on-site SEO’s future… People return to the site after an initial search visit
BTW –This is hard to
replicate.600+ real searchersusinga varietyof devices,browsers,accounts,geos,etc. willnot lookthe same to Googleas a Fiverr buy,a clickfarm,or a bot.And note how G penalizedthe page after the test…They might not put it back if they thoughtthe site itselfwas to blame for the clickmanipulation.
Optimizing the Title, Meta Description,
& URL a Little for KWs, but a Lot for Clicks If you rank #3, but have a higher-than- average CTR for that position, you might get moved up. Via Philip Petrescu on Moz
Every Element Counts Does the
title match what searchers want? Does the URLseem compelling? Do searchers recognize & want to click your domain? Is your result fresh? Do searchers want a newer result? Does the description create curiosity & entice a click? Do you get the brand dropdown?
Given Google Often Tests New
Results Briefly on Page One… ItMayBeWorthRepeatedPublicationonaTopictoEarnthatHighCTR Shoot! My post only made it to #15… Perhaps I’ll try again in a few months.
Speed, Speed, and More Speed
Delivers the Best UX on Every Browser Compels Visitors to Go Deeper Into Your Site Avoids Features thatAnnoy or Dissuade Visitors Content that Fulfills the Searcher’s Conscious & Unconscious Needs An SEO’s Checklist for Better Engagement:
Via NY Times e.g. this
interactive graph that asks visitors to draw their best guess likely gets remarkable engagement
e.g. Poor Norbert does a
terrible job at SEO, but the simplicity compels visitors to go deeper and to return time and again Via VoilaNorbert
If Your Content Doesn’t Fill
the Gaps in Searcher’s Needs… e.g. for this query, Google might seek content that includes topics like “text classification,” “tokenization,” “parsing,” and “question answering” Those Rankings Go to Pages/Sites That Do.
Moz’s Data Science Team is
Working on Something to Help With This The (alpha) tool extracts likely focal topics from a given page, which can then be compared vs. an engines top 10 results
Data from Buzzsumo & Moz
show that very few articles earn sharesAND that links & shares have almost no correlation. Via Buzzsumo & Moz
I suspect Google doesn’t use
raw social shares as a ranking input, because we share a lot of content with which we don’t engage: Via Chartbeat
Google Could Be Using a
Lot of Other Metrics/Sources to Get Data That Mimics Social Shares: Clickstream (from Chrome/Android) Engagement (from Chrome/Android) Branded Queries (from Search) Navigational Queries (from Search) Rate of Link Growth (from Crawl)
BTW – GoogleAlmost Certainly Classifies
SERPs Differently & Optimizes to Different Goals These URLs have loads of shares & may have high loyalty, but for medical queries, Google has different priorities
We Don’t Need “Better” Content…
We Need “10X” Content. Via Whiteboard Friday Wrong Question: “How do we make something as good as this?” Right Question: “How do we make something 10X better than any of these?”
10X Content is the Future,
Because It’s the Only Way to Stand Out from the Increasingly-Noisy Crowd http://www.simplereach.com/blog/facebook-continues-to-be-the- biggest-driver-of-social-traffic/ The top 10% of content gets all the social shares and traffic.
Old School On-Site Old School
Off-Site Keyword Targeting Link Diversity Anchor Text Brand Mentions 3rd Party Reviews Reputation Management Quality & Uniqueness Crawl/Bot Friendly Snippet Optimization UX / Multi-Device None of our old school tactics will get this done.
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 Get SearchersAccomplishing Their Tasks Faster
Broad search All the sites
(or answers) you probably would have visited/sought along that path Completion of Task This is Their Ultimate Goal: