[cxl live 16] fight back against back by rand fishkin

Rand Fishkin, Wizard of Moz | @randfish | rand@moz.com

Fight Back Against BackWhy 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 outearnyour 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

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 RankBrainDespite 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 J

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

Don’t Just Ask “Who is My Customer?”

Via Moz

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:NoiseRatio 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 Rankings

A 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

Engagement, Sharing, & Repeat Visits

Via Meshable.io

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 J

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’stool 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.

Rand Fishkin, Wizard of Moz | @randfish | rand@moz.com

Bit.ly/backenemy