Ponencia de Rand Fishkin en The Inbounder.

1. @Randfish
Fight Back Against Back
RAND FISHKIN
#theinbounder
Ponencia en inglés - Ponte los

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

3. Slides online at
bit.ly/backenemy

4. Let’s Go Back to 2012…

5. Keywords, content, links, and a
crawlable site could get you here…
And keep you there.

6. 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

7. On Facebook, the likes and
shares determined how often
you’d be in the news feed of your
fans.

8. On Twitter, visibility was entirely
determined by publication time.

9. In 2012, we only had to
worry about the path to
conversion and CRO on our
own sites.

10. We could let audiences
self-select out of these
phases after an initial visit
without fear of
repercussions

11. 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.

12. What Happened that Made
2016 so Different?

13. Google Moved to Learning
Algorithms

14. Early On, Google Rejected Machine Learning in the
Organic RankingAlgo
Via Datawocky,
2008

15. Amit Singhal Shared Norvig’s ConcernsAbout ML
Via Quora

16. In 2012, Google Published a PaperAbout How
they Use ML to Predict Ad CTRs:
Via Google

17. 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.”

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

19. In October of 2015, they
finally revealed
RankBrain, anAI-
system input to the
search rankings
Via Bloomberg Business

20. As MLTakes Over More of Google’sAlgo, the
Underpinnings of the Rankings Change
Via Colossal

21. Google is PublicAbout 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

22. Google is PublicAbout How They Use MLin Image
Recognition & Classification
Via Jeff Dean’s Slides on Deep Learning; a Must Read for SEOs

23. 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

24. 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.

25. 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.

26. The Machines Learn to Emulate the Good Results & Try to Fix
orTweak 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

27. Deep Learning is Even MoreAdvanced:
Dean says by using deep
learning, they don’t have to
tell the system what a cat is,
the machines learn,
unsupervised, for
themselves…

28. We’re TalkingAbout
Algorithms that Build
Algorithms
(without human
intervention)

29. 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

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

31. And RankBrain is Clearly Important:
Via Bloomberg Business

32. Google Leverages the Outputs from RankBrain Despite
Not Knowing for Sure What It Uses:
Via SERoundtable

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

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

35. But Google Isn’t Alone

36. Facebook’s Visibility
Algorithms

37. Via Slate
Machine learning based on
engagement determines
what appears in our
Facebook News Feeds

38. Twitter’s Emerging Visibility
Plan

39. 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

40. Instagram’s New Algorithmic
Feed

41. Instagram
announced the
change March 15th
saying they will
“take their time to
get this right.”
Via Mashable

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

43. Google Suggest
The order of suggestions is
based on engagement w/
those queries

44. ChromeAutocomplete
Ordered by what I (and
others) have engaged
with most that contain
these letters

45. Google Maps & Local
Results
Search volume, driving
directions, and SERP
engagement are all
elements of local rankings

46. Social Networks’“Trending” Content

47. SuggestedAccounts to Follow

48. What’s “Important” in Gmail
If lots of folks ignore,
delete, or report spam on
your emails, you won’t
get this label anymore

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

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

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

52. How Do We Fight Back
Against Back?

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

54. Don’t JustAsk “Who is My Customer?”
Via Moz

55. Ask “WhatAreAll the Needs of These Searchers?” Then
ServeAs Many as Possible
You might be trying to sell desks, but
searchers are seeking answers to all of these

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

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

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

59. Optimize the Title, Meta Description, & URL
a 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

60. 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?

61. 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.

62. Driving Up CTR Through Branding Or Branded
Searches May GiveAn Extra Boost

63. #1 Ad Spender
#2 Ad Spender
#4 Ad Spender
#3 Ad Spender
#5 Ad Spender

64. 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.

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

66. 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.

67. 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…

68. Better Social Shares > More Social Shares
High engagement grows
my reach potential.
Low engagement shrinks
my reach potential.

69. Better Emails > More Emails
Via Pinpointe.com

70. Better Emails > More Emails
Via CrazyEgg.com

71. 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!

72. Put User Experience First in
Your Marketing#4

73. 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

74. 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.

75. Speed, Speed, and More Speed
Via Moz

76. Easy, Enjoyable Experience on Every Device
Via CNN

77. Via CNN
Easy, Enjoyable Experience on Every Device

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

79. Nothing That
Dissuades Or
Annoys Visitors
Ads, more ads, distractions,
and no salary numbers? It’s a
miracle they rank at all.

80. This might convert more visitors to email subscribers, but it
might also convert many more visitors to back-button-clickers

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

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

83. 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

84. FightingAgainst 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

85. 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

86. 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

87. 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)

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

89. The Machines Are Judging
Us…

90. Let’s Show ‘Em
What We Got.

91. Fight Back Against Back.

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

93. GRACIAS
THANK YOU
#theinbounder
@Randfish
RAND FISHKIN