Rand Fishkin en The Inbounder
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@Randfish Fight Back Against Back RAND FISHKIN #theinbound er Ponencia en inglés - Ponte los
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Transcript of Rand Fishkin en The Inbounder
@Randfish
Fight Back Against Back
RAND FISHKIN
#theinbounder Ponencia en inglés - Ponte los
Rand Fishkin, Wizard of Moz | @randfish | [email protected]
Why the back button has become web marketing’s greatest enemy
(and how to defeat it)
Slides online atbit.ly/backenemy
Let’s Go Back to 2012…
Keywords, content, links, and a crawlable site could get you here… And keep you there.
Even if the experience users had wasn’t superb, so long as you could outearn your competitors’ links, you were likely to stay on
top
On Facebook, the likes and shares determined how often you’d be in
the news feed of your fans.
On Twitter, visibility was entirely determined by publication time.
In 2012, we only had to worry about the path to conversion and CRO on our own sites.
We could let audiences self-select out of these
phases after an initial visit without fear of repercussions
If putting a price here meant 80% of visitors left, no problem. So long as the more qualified ones (those we really wanted)
stayed, we were doing our jobs.
What Happened that Made 2016 so Different?
Google Moved to Learning Algorithms
Early On, Google Rejected Machine Learning in the Organic Ranking Algo
Via Datawocky, 2008
Amit Singhal Shared Norvig’s Concerns About ML
Via Quora
In 2012, Google Published a Paper About How they Use ML to Predict Ad CTRs:
Via Google
Susan Wojcicki, Google SVP, at All Things Digital, 2012
“Our SmartASS system is a machine learning system. It learns whether our users are interested in that ad, and whether users are going to click on them.”
By 2013, It Was Something Google’s Search Folks Talked About Publicly
Via SELand
In October of 2015, they finally revealed RankBrain, an AI-system input to the search rankings
Via Bloomberg Business
As ML Takes Over More of Google’s Algo, the Underpinnings of the Rankings Change
Via Colossal
Google is Public About How They Use ML in Image Recognition & Classification
Potential ID Factors
(e.g. color, shapes, gradients, perspective,
interlacing, alt tags, surrounding text, etc)
Training Data(i.e. human-labeled images)
Learning Process
Best Match Algo
Google is Public About How They Use ML in Image Recognition & Classification
Via Jeff Dean’s Slides on Deep Learning; a Must Read for SEOs
Machine Learning in Search Could Work Like This:
Potential Ranking Factors
(e.g. PageRank, TF*IDF,Topic Modeling, QDF, Clicks,
Entity Association, etc.)
Training Data(i.e. good & bad search
results)
Learning Process
Best Fit Algo
Training Data(e.g. good search results)
This is a good SERP – searchers rarely bounce, rarely short-click, and rarely need to enter other queries or go to page 2.
Training Data(e.g. bad search results!)
This is a bad SERP – searchers bounce often, click other results, rarely long-click, and try other queries. They’re definitely not happy.
The Machines Learn to Emulate the Good Results & Try to Fix or Tweak the Bad Results
Potential Ranking Factors
(e.g. PageRank, TF*IDF,Topic Modeling, QDF, Clicks,
Entity Association, etc.)
Training Data(i.e. good & bad search
results)
Learning Process
Best Fit Algo
Deep Learning is Even More Advanced:
Dean says by using deep learning, they don’t have to
tell the system what a cat is, the machines learn, unsupervised, for
themselves…
We’re Talking About Algorithms that Build Algorithms(without human intervention)
Googlers Don’t Feed in Ranking Factors… The Machines Determine Those Themselves.
Potential Ranking Factors
(e.g. PageRank, TF*IDF,Topic Modeling, QDF, Clicks,
Entity Association, etc.)
Training Data(i.e. good search results)
Learning Process
Best Fit Algo
Last October, Google Finally Went Public with Their Use of ML-Based RankBrain
Via Bloomberg Business
And RankBrain is Clearly Important:
Via Bloomberg Business
Google Leverages the Outputs from RankBrain Despite Not Knowing for Sure What It Uses:
Via SERoundtable
Google’s AI Just Keeps Growing in Power…
Via The Verge
No wonder these guys are stressed about Google unleashing the Terminators
Via CNET & Washington Post
But Google Isn’t Alone
Facebook’s VisibilityAlgorithms
Via Slate
Machine learning based on engagement determines
what appears in our Facebook News Feeds
Twitter’s Emerging Visibility Plan
Twitter’s new home screen will work the
same way – highlighting the “most important” (aka “most engaged-with”) tweets from accounts you follow
Via Mashable
Instagram’s New Algorithmic Feed
Instagram announced the
change March 15th saying they will
“take their time to get this right.”
Via Mashable
Engagement is Becoming the Web’s Universal
Quality Metric
Google Suggest
The order of suggestions is based on engagement w/
those queries
Chrome Autocomplete
Ordered by what I (and others) have engaged with most that contain
these letters
Google Maps & Local Results
Search volume, driving directions, and SERP engagement are all
elements of local rankings
Social Networks’ “Trending” Content
Suggested Accounts to Follow
What’s “Important” in Gmail
If lots of folks ignore, delete, or report spam on your emails, you won’t get this label anymore
Sites & Brands Earn an Engagement Reputation that Determines Visibility
Quantity of Posts/Emails/ Pieces of Content/ Rankings/etc
Quantity of clicks/likes/shares/reactions/etc
EngagementReputation=
Every Time a Visitor Clicks that Back Button, It Saps Away at our Reputation
How Do We Fight Back Against Back?
Understand & Serve All of Your Visitors’ Intents#1
Ask “What Are All the Needs of These Searchers?” Then Serve As Many as Possible
You might be trying to sell desks, but searchers are seeking answers to all of these and more.
If the Competition Delivers Value to Searchers Who Aren’t Buyers, But You Don’t…
They’re Likely to Win the Engagement Battle
Via JustStand.org
Outearn Your Ranking’s Avg. Clickthrough Rate#2
Optimize the Title, Meta Description, & URLa Little for Keywords, 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 URL seem
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…
It May Be Worth Repeated Publication on a Topic to Earn that High CTR
Shoot! My post only made it to #15… Perhaps I’ll try again in a few months.
Driving Up CTR Through Branding Or Branded Searches May Give An Extra Boost
#1 Ad Spender
#2 Ad Spender
#4 Ad Spender
#3 Ad Spender
#5 Ad Spender
With Google Trends’ new, more accurate, more customizable ranges, you can actually watch the effects of events and ads on search query volume
Fitbit was running ads on Sunday NFL games that clearly show in
the search trends data.
Optimize Signal:Noise Ratio on Every Channel#3
Better Content > More Content
A lot of SEO used to be about establishing authority through brute quantity, but Panda,
and now Rankbrain, are changing that.
Better Social Shares > More Social Shares
Via Rand’s Facebook Page
When I have a successful post on Facebook, it boosts
Facebook’s likelihood to show my posts in the
future…
Better Social Shares > More Social Shares
High engagement grows my reach potential.
Low engagement shrinks my reach potential.
Better Emails > More Emails
Via Pinpointe.com
Better Emails > More Emails
Via CrazyEgg.com
Better Rankings >More RankingsA brand that consistently gets on page 1
but isn’t holding searchers’ interest or develops a negative brand reputation in SERPs may find those page 1 rankings
are hurting their ability to get #1 rankings!
Put User Experience First in Your Marketing#4
Speed, speed, and more speed
Delivers an easy, enjoyable experience on every device
Compels visitors to engage, share, & return
Avoids features that dissuade or annoy visitors
Authoritative, comprehensive content that’s uniquely valuable vs. what anyone else in your space provides
The Marketer’s User Experience Checklist
Uniquely Valuable Content
Via R2D3
Lots of articles try to explain machine learning, but this one SHOWS how it works in a way anyone can
grasp.
Speed, Speed, and More Speed
Via Moz
Easy, Enjoyable Experience on Every Device
Via CNN
Via CNN
Easy, Enjoyable Experience on Every Device
Nothing That Dissuades Or
Annoys Visitors
Ads, more ads, distractions, and no salary numbers? It’s a
miracle they rank at all.
This might convert more visitors to email subscribers, but it might also convert many more visitors to back-button-clickers
Cyrus May Have Gone a Little Overboard…
Via Cyrus on Twitter
Craft Compelling CTAs at the Top of the Funnel#5
Top-of-Funnel Content Can’t Be Used Solely to Filter Out the Non-Customers
Trying to rank w/ content that only serves one niche of your search audience
may be a recipe for failure
Fighting Against Back Means Serving a Broader Audience
AngelList’s tool makes salary comparison
easy, fast, and serves a huge range of roles,
locations, and markets
Via AngelList
Or, Getting More Precise with Your Search Query -> Content Targeting
By targeting a less competitive, lower volume query, Compass can reach
the audience they’re seeking
Either Way, Engagement Metrics on Content Must Become KPIs
Improving Pages/Session and lowering Bounce Rate should probably play a “link-building-like” role in your SEO arsenal
Our Content CTAs Deserve to Be Customized, Tested, & Refined
(just like conversion-focused landing pages)e.g. I bet I could make a
better CTA for the comparison tool than
this (which looks far too much like an ad IMO)
Via Talkpay (Comparably’s Blog)
Welcome to 2016: A World of Engagement-Based Reputation
The Machines Are Judging Us…
Let’s Show ‘EmWhat We Got.
Fight Back Against Back.
GRACIASTHANK YOU
#theinbounder
@Randfish
RAND FISHKIN
