Web marketers have never faced a more dangerous time to have their visitors hit that "back" button. Facebook, Google, and even Twitter are measuring engagement and punishing the sites and brands that lose too much of their audience to an "I'm outta here" click. We've moved from a world where conversion rate optimization happens only in the purchase funnel to one where converting from a 5-second visitor to a 45-second, more engaged visitor who leaves with an answer is hugely important. In this presentation, Rand will show how Google's Rankbrain, Facebook's engagement algorithms, and other platforms' metrics are transforming this landscape and what web marketers can do to fight back.

1. Rand Fishkin, Wizard of Moz | @randfish | rand@moz.com
Fight Back Against Back
Why the back button has become web marketing’s
greatest enemy (and how to defeat it)

2. Slides online at
bit.ly/backenemy

3. Let’s Go Back to 2012…

4. Keywords,content,links,anda
crawlable sitecouldgetyouhere…
Andkeepyou there.

5. Eveniftheexperienceusershadwasn’tsuperb,solongas you
couldoutearnyourcompetitors’links,youwerelikelytostayontop

6. OnFacebook,thelikes andshares
determinedhowoftenyou’dbein
thenewsfeedofyourfans.

7. OnTwitter,visibilitywasentirely
determinedby publicationtime.

8. In2012,weonlyhadtoworry
aboutthepathtoconversion
andCRO onourownsites.

9. Wecouldletaudiencesself-
selectoutofthesephases
afteraninitial visitwithout
fear ofrepercussions

10. If puttingaprice heremeant80%
ofvisitorsleft,noproblem.So
longasthemorequalifiedones
(thosewereally wanted)stayed,
weweredoingourjobs.

11. What Happened that
Made 2016 so Different?

12. Google Moved to
Learning Algorithms

13. Early On, Google Rejected Machine Learning in
the Organic Ranking Algo
Via Datawocky,
2008

14. Amit Singhal Shared Norvig’s Concerns About ML
Via Quora

15. In 2012, Google Published a Paper About
How they Use ML to Predict Ad CTRs:
Via Google

16. 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.”

17. By 2013, It Was
Something
Google’s Search
Folks Talked
About Publicly
Via SELand

18. In October of2015,
they finally revealed
RankBrain, an AI-
system input to the
search rankings
Via Bloomberg Business

19. As ML Takes Over More ofGoogle’s Algo, the
Underpinnings of the Rankings Change
Via Colossal

20. Google is Public About How They Use MLin
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

21. Google is Public About How They Use MLin
Image Recognition & Classification
ViaJeff Dean’s Slides onDeep Learning; aMustReadforSEOs

22. Machine Learning in Search Could Work Like This:
Potential
Ranking Factors
(e.g. PageRank, TF*IDF,
TopicModeling, QDF,Clicks,
Entity Association, etc.)
Training Data
(i.e. good&badsearch results)
Learning
Process
Best Fit
Algo

23. Training Data
(e.g. goodsearch results)
This is a good SERP – searchers
rarely bounce, rarely short-
click, and rarely need to enter
other queries or go to page 2.

24. 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.

25. The Machines Learn to Emulate the Good Results &
Try to Fix or Tweak the Bad Results
Potential
Ranking Factors
(e.g. PageRank, TF*IDF,
TopicModeling, QDF,Clicks,
Entity Association, etc.)
Training Data
(i.e. good&badsearch results)
Learning
Process
Best Fit
Algo

26. Deep Learning is Even More Advanced:
Deansaysbyusingdeep
learning,they don’thave totell
thesystemwhata catis,the
machineslearn, unsupervised,
forthemselves…

27. We’re Talking
About Algorithms
that Build
Algorithms
(without human
intervention)

28. Googlers Don’t Feed in Ranking Factors… The
Machines Determine Those Themselves.
Potential
Ranking Factors
(e.g. PageRank, TF*IDF,
TopicModeling, QDF,Clicks,
Entity Association, etc.)
Training Data
(i.e. goodsearch results)
Learning
Process
Best Fit
Algo

29. Last October, Google Finally Went Public
with Their Use of ML-Based RankBrain
Via Bloomberg Business

30. And RankBrain is Clearly Important:
Via Bloomberg Business

31. Google Leverages theOutputs from RankBrain
Despite NotKnowing for Sure What ItUses:
Via SERoundtable

32. Google’s AI Just Keeps Growing in Power…
Via The Verge

33. No wonder these guys are stressed about
Google unleashing the Terminators J
Via CNET & Washington Post

34. But Google Isn’t Alone

35. Facebook’s Visibility
Algorithms

36. Via Slate
Machinelearningbasedon
engagementdetermines
whatappearsinour
FacebookNewsFeeds

37. Twitter’s Emerging
Visibility Plan

38. Twitter’snewhome
screenwillworkthe
sameway–
highlightingthe“most
important”(aka“most
engaged-with”)tweets
fromaccountsyou
follow
Via Mashable

39. Instagram’s New
Algorithmic Feed

40. Instagram
announcedthe
changeMarch 15th
sayingtheywill
“taketheirtime to
getthisright.”
Via Mashable

41. Engagement is Becoming
the Web’s Universal
Quality Metric

42. Google Suggest
The orderof suggestionsis
basedonengagementw/
thosequeries

43. Chrome Autocomplete
Orderedby whatI (and
others)have engaged
withmostthatcontain
theseletters

44. Google Maps &
Local Results
Search volume,driving
directions,andSERP
engagementare all
elementsoflocal rankings

45. Social Networks’ “Trending” Content

46. Suggested Accounts to Follow

47. What’s “Important” inGmail
If lotsoffolksignore,
delete, orreportspamon
youremails,you won’tget
thislabel anymore

48. Sites & Brands Earn an
Engagement Reputation
that Determines Visibility

49. Quantity of
Posts/Emails/
Pieces of Content/
Rankings/etc
Quantity of
clicks/likes/shares
/reactions/etc
Engagement
Reputation=

50. Every Time a Visitor Clicks
that Back Button, It Saps
Away at our Reputation

51. How Do We Fight Back
Against Back?

52. Understand & Serve All
of Your Visitors’ Intents#1

53. Don’t Just Ask “Who is My Customer?”
Via Moz

54. Ask “What Are All theNeeds ofThese Searchers?”
Then Serve As Many as Possible
Youmightbetryingtoselldesks,butsearchers
are seekinganswerstoallof theseandmore.

55. If the Competition Delivers Value to Searchers
Who Aren’t Buyers, But You Don’t…

56. They’re Likely to Win the Engagement Battle
Via JustStand.org

57. Outearn Your Ranking’s
Avg. Clickthrough Rate#2

58. Optimize the Title, Meta Description, & URL
a Little for Keywords, but aLot for Clicks
If yourank#3,buthave a higher-
than-averageCTRforthatposition,
youmightgetmoved up.
Via Philip Petrescu on Moz

59. Every Element Counts
Doesthetitlematch
whatsearcherswant?
DoestheURLseem
compelling?
Dosearchers
recognize&wantto
clickyourdomain?
Is yourresultfresh?
Dosearcherswanta
newerresult?
Doesthedescription
createcuriosity&
enticeaclick?
Doyougetthe
branddropdown?

60. Given Google Often Tests New Results Briefly on Page One…
ItMayBeWorth Repeated Publication onaTopic toEarn that High CTR
Shoot!My postonlymade itto#15…
PerhapsI’lltryagain ina fewmonths.

61. Driving Up CTR Through Branding Or
Branded Searches May Give An Extra Boost

62. #1Ad Spender
#2 Ad Spender
#4 Ad Spender
#3Ad Spender
#5Ad Spender

63. With Google
Trends’ new, more
accurate, more
customizable
ranges, youcan
actually watchthe
effects ofevents
and adsonsearch
query volume
Fitbitwasrunningads onSunday
NFLgamesthatclearlyshowinthe
searchtrends data.

64. Optimize Signal:Noise
Ratio on Every Channel#3

65. Better Content > More Content
A lotofSEOusedtobeaboutestablishing
authoritythroughbrutequantity,butPanda,
andnowRankbrain,are changingthat.

66. Better Social Shares > More Social Shares
Via Rand’s Facebook Page
WhenI have a successful
postonFacebook,itboosts
Facebook’slikelihoodto
showmy postsinthe future…

67. Better Social Shares > More Social Shares
High engagementgrows
my reach potential.
Lowengagementshrinks
my reach potential.

68. Better Emails > More Emails
Via Pinpointe.com

69. Better Emails > More Emails
Via CrazyEgg.com

70. Better Rankings >
More Rankings
A brandthatconsistentlygetsonpage 1
butisn’tholdingsearchers’interestor
developsa negativebrandreputationin
SERPsmay findthosepage 1rankingsare
hurtingtheirabilityto get#1rankings!

71. Put User Experience
First in Your Marketing#4

72. 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

73. Uniquely Valuable Content
Via R2D3
Lotsofarticlestrytoexplainmachine learning,butthis
oneSHOWShowitworksina wayanyonecangrasp.

74. Speed, Speed, and More Speed
Via Moz

75. Easy, Enjoyable Experience on Every Device
Via CNN

76. Via CNN
Easy, Enjoyable Experience on Every Device

77. Engagement, Sharing, & Repeat Visits
Via Meshable.io

78. Nothing That
Dissuades Or
Annoys Visitors
Ads,more ads,distractions,
andnosalarynumbers?It’sa
miracle theyrankatall.

79. Thismightconvertmorevisitorstoemail subscribers,butit
mightalsoconvertmanymorevisitorstoback-button-clickersJ

80. Cyrus May Have
Gone a Little
Overboard…
Via Cyrus on Twitter

81. Craft Compelling CTAs
at the Top of the Funnel#5

82. Top-of-Funnel Content Can’t Be Used Solely
to Filter Out the Non-Customers
Tryingtorank w/content
thatonlyservesoneniche
ofyour searchaudience
may bea recipe for failure

83. Fighting Against Back Means Serving a
Broader Audience
AngelList’stoolmakes
salarycomparison
easy,fast,andservesa
huge rangeofroles,
locations,andmarkets
Via AngelList

84. Or, Getting More Precise with Your Search
Query -> Content Targeting
By targetinga less
competitive,lowervolume
query,Compasscanreach
theaudience they’reseeking

85. Either Way, Engagement Metrics on Content
Must Become KPIs
ImprovingPages/Sessionand
loweringBounceRateshould
probablyplay a “link-building-
like”role inyourSEOarsenal

86. Our Content CTAs Deserve to Be
Customized, Tested, & Refined
(just like conversion-focused landing pages)
e.g. IbetI couldmake a
betterCTA forthe
comparisontoolthan
this(whichlooksfar too
muchlike anad IMO)
Via Talkpay (Comparably’s Blog)

87. Welcome to 2016: A
World of Engagement-
Based Reputation

88. The Machines Are
Judging Us…

89. Let’s Show ‘Em
What We Got.

90. Fight Back Against Back.

91. Rand Fishkin, Wizard of Moz | @randfish | rand@moz.com
Bit.ly/backenemy