The velocity of change in the marketing industry is accelerating, but what we see today is elementary when we consider the potential of what comes next. This session provides a glimpse into the future of marketing, and the opportunities that exist for those who can harness the power of artificial intelligence and cognitive technology like IBM's Watson. They will be able to do more with less, run personalized campaigns of unprecedented complexity, and analyze massive data sets to predict outcomes. The opportunities are endless for those with the will and vision to transform the industry. Attendees will: - Learn what the disruption of other industries can teach us about the inevitable impact artificial intelligence will have on the marketing industry. - Discover existing marketing technologies using artificial intelligence to make marketing more efficient and effective. - Get inspired to explore what’s possible for the future of marketing, as well as their businesses and careers.

1. #INBOUND16
ORIGINS OF THE
MARKETING
INTELLIGENCE ENGINE
Paul Roetzer, Founder & CEO, PR 20/20
Copyright 2016 PR 20/20. All rights reserved.
@PaulRoetzer

2. #INBOUND16
Consider
how
much
!me
your
marke2ng
team
spends
.
.
.
crea2ng
ad
copy
managing
digital
ad
campaigns
tes2ng
headlines,
landing
pages,
ads
scheduling/publishing
social
shares
predic2ng
opens,
clicks,
conversions
reviewing
analy!cs
wri2ng
performance
reports
recommending
strategies
alloca2ng
resources
dra;ing
social
media
updates
discovering
keywords
planning
blog
post
topics
wri!ng
content
op!mizing
content
cura!ng
content
personalizing
content
automa!ng
content
building
email
workflows
Copyright 2016 PR 20/20. All rights reserved.

3. Now imagine if machines performed the majority
of those activities,
and a marketer’s primary role
was to enhance rather than create.

4. There is a relatively untapped technology that possesses the
power to change everything…

5. artificial intelligence

6. #INBOUND16
“The
science
of
making
machines
smart.”
—
Demis
Hassabis,
Co-­‐Founder
&
CEO
of
DeepMind
what
is
ar!ficial
intelligence?
(which
in
turn
augments
human
knowledge
and
capabili5es)
Source: Rolling Stone

7. #INBOUND16
a
set
of
instruc!ons
that
tells
the
machine
what
to
do.
what
is
an
algorithm?
(except
with
AI
the
machine
can
create
its
own
algorithms,
determine
new
paths,
and
unlock
unlimited
poten5al
to
advance
marke5ng,
and
mankind.)

8. #INBOUND16
THE DISRUPTION OF
INDUSTRIES

9. @paulroetzer www.pr2020.com
60%
of
all
trades
are
executed
by
computers
with
liKle
or
no
real-­‐2me
oversight
from
humans.
Source:
Christopher
Steiner,
Automate
This

10. @paulroetzer
avg
120
stops/day

11. what
is
the
possible
number
of
alterna!ves
for
ordering
those
stops?

12. 6,689,502,913,449,135,000,000,000,
000,000,000,000,000,000,000,000,
000,000,000,000,000,000,000,000,
000,000,000,000,000,000,000,000,
000,000,000,000,000,000,000,000,
000,000,000,000,000,000,000,000,
000,000,000,000,000,000,000,000,
000,000,000,000,000,000,000,000,
000,000
Source: Wall Street Journal

13. “Can
a
human
really
think
of
the
best
way
to
deliver
120
stops?
This
is
where
the
algorithm
will
come
in.
It
will
explore
paths
of
doing
things
you
would
not,
because
there
are
just
too
many
combina2ons.”
Jack
Levis
Senior
director
of
process
management,
UPS
Source: Wall Street Journal

14. NETFLIX
uses
algorithms
to
suggest
content
and
manufacture
shows
based
on
subscriber
viewing
habits
and
preferences.
Source:
NeUlix
Tech
Blog

15. 75%
of
what
people
watch
on
NeSlix
is
from
some
sort
of
algorithm-­‐generated
recommenda!on
Source:
NeUlix
Tech
Blog

16. Epagogix
algorithms
analyze
movie
scripts
to
predict
how
much
money
they
will
make
at
the
box
office
and
offer
recommenda!ons
on
how
to
make
them
more
marketable
and
profitable,
including
through
changes
to
plot
lines,
seVngs,
character
roles
and
actors.

17. Source: Tesla

20. #INBOUND16
THE MARKETING MACHINE
AGE

21. POTENTIAL to disrupt + the REWARD for disruption

22. ExactTarget
IPO
(Mar
'12)
Oracle
buys
Eloqua
(Dec
'12)
SF
buys
ExactTarget
(Jun
'13)
IBM
buys
Silverpop
(Apr
'14)
Marketo
market
cap
(8-­‐30-­‐16)
HubSpot
market
cap
(8-­‐30-­‐16)
0 5 10 15 20 25
$161.5M
$871
M
$2.5
B
venture
funding,
mergers,
acquisi2ons
and
IPOs
have
fueled
the
marke!ng
automa!on
space
@paulroetzer www.pr2020.com
$270
M
$1.6
B
$1.9
B

23. 90% of all data in the world
has been created in the last 2 years
Source:
IBM

24. marketers have access to data from dozens of sources:
social monitoring, media monitoring, web analytics,
email, call tracking, sales, advertising, remarketing,
ecommerce, mobile apps. . .

25. We
have
a
finite
ability
to
process
informa2on,
build
strategies,
create
content
at
scale,
and
achieve
performance
poten!al.

26. Algorithms, in contrast, have an almost
infinite ability to process data, and deliver
predictions, recommendations and content
better, faster and cheaper.
Image:
Wikimedia
Commons

27. @paulroetzer www.pr2020.com
And
yet
marke2ng
remains
largely
human
powered,
with
a
bit
of
automa2on
mixed
in.

28. The future may be
closer than you think.

29. #INBOUND16
NATURAL LANGUAGE GENERATION
(AKA MACHINE-ASSISTED CONTENT)

30. Image:
Franck
Calzada/YouTube
The AP “writes” 10x more earnings reports using AI,
specifically natural language generation

32. @paulroetzer

33. Define
Founda2on
Projects
Subjective analysis
Internal stakeholders
10 sections
27 profile fields
132 factors
Sample
Marke5ng
Score
Factor
Slider
Scale

34. A
strong
marke!ng
technology
founda2on
is
cri2cal
to
driving
performance.
Core
technologies,
when
integrated,
improve
efficiencies,
maximize
produc2vity
and
ROI,
and
create
compe22ve
advantages.
The
company
should
priori2ze
CMS
(5),
CRM
(4),
email
marke2ng
(3),
marke2ng
analy2cs
(2)
and
marke2ng
automa2on
(2).
sample key finding

35. A
strong
marke!ng
technology
founda2on
is
cri2cal
to
driving
performance.
Core
technologies,
when
integrated,
improve
efficiencies,
maximize
produc2vity
and
ROI,
and
create
compe22ve
advantages.
The
company
should
priori2ze
CMS
(5),
CRM
(4),
email
marke2ng
(3),
marke2ng
analy2cs
(2)
and
marke2ng
automa2on
(2).

36. * Requires human writers to develop and enhance templates.
Using
Natural
Language
Genera!on
(aka
Machine
Assisted)*:
50
briefs
x
15
minutes
per
brief
=
12.5
hours/month
The
Diff:
37.5
hours
(at
a
cost
of
$250/month
for
the
license.)
Tradi!onal
Way:
50
briefs
x
1
hour
per
brief
=
50
hours/month

37. The
Benefits
More
accurate
(eliminates
human
error)
More
briefs
published
(enables
content
at
scale)
More
cost
efficient
(shi;s
2me
to
edi2ng
only)
More
engagement
More
value
crea!on
for
members
More
new
business
opportuni!es

38. #INBOUND16
THE NEXT FRONTIER

39. Private investment in the AI sector has grown from
$1.7B in 2010 to $14.9B in 2014
The market for AI based analytics could grow from
$8.2B to $70B by 2020.
— Source: BofA Merrill Lynch: Robot Revolution — Global Robot & AI Primer

40. There are dozens of AI-powered marketing tools that you
can use to predict, plan, create, optimize, personalize,
promote, measure and analyze.
Source: Timothy Neesom

41. $29.4 M
$36.0 M
$9.5 M
Source:
Crunchbase
Artificial Intelligence + Marketing
$279+ M $80.0 M*
$66.0 M
$14.5 M
$13.9 M
$11.0 M
$5.4 M
$14.2 M

42. “We’re in an AI spring. For our
company, and I think for every
company, the revolution in data
science will fundamentally
change how we run our
business because we’re going to
have computers aiding us in
how we’re interacting with our
customers.”
— Marc Benioff
Source:
FortuneImage:
Wikipedia

43. Source: Social Media Frontiers
Facebook
uses
“deep
learning,”
an
AI
subfield,
to
filter
your
Newsfeed
and
recognize
faces
in
photos
you
upload,
but
that’s
only
the
beginning
.
.
.

44. Source: Social Media Frontiers
hKps://research.facebook.com/ai
“We’re
commiKed
to
advancing
the
field
of
machine
intelligence
and
developing
technologies
that
give
people
beger
ways
to
communicate.
In
the
long
term,
we
seek
to
understand
intelligence
and
make
intelligent
machines.”

45. search,
voice
recogni!on,
language
transla!on,
robots,
driverless
cars
.
.
.

47. Image:
Wikimedia
CommonsSource:
Business
Insider
The
story
of
ar2ficial
intelligence
can’t
be
told
without
IBM
,
which
possesses
an
es!mated
500
AI-­‐related
patents.

48. IBM
Watson
is
a
technology
plaUorm
that
uses
natural
language
processing
and
machine
learning
to
reveal
insights
from
large
amounts
of
unstructured
data
Source: IBM

49. Source: Popular Science
“IBM
used
machine
learning
and
experimental
Watson
APIs,
parsing
out
the
trailers
of
100
horror
movies.
It
did
visual,
audio,
and
composi2on
analysis
of
individual
scenes.
.
.
.
Watson
was
then
fed
the
full
film,
and
it
chose
scenes
for
the
trailer.
.
.
.
A
process
that
would
normally
take
weeks
was
reduced
to
hours.”

51. "Cogni2ve
technology
is
there
to
extend
and
amplify
human
exper!se,
not
replace
it.”
—
Rob
High,
Chief
Technology
Officer,
IBM
Watson

52. Rather
than
simply
automa2ng
manual
tasks,
ar!ficial
intelligence
adds
a
cogni!ve
layer
that
infinitely
expands
marketers’
ability
to
process
data,
iden2fy
paKerns,
predict
outcomes,
and
build
intelligent
strategies
and
content
beger,
faster
and
cheaper.

53. dra;ing
social
media
updates
*
discovering
keywords
*
planning
blog
post
topics
*
wri!ng
content
*
op!mizing
content
*
cura!ng
content
*
personalizing
content
*
automa!ng
content
*
building
email
workflows
*
crea2ng
ad
copy
*
managing
digital
ad
campaigns
*
tes2ng
headlines,
landing
pages,
ads
*
scheduling/publishing
social
shares
*
predic2ng
opens,
clicks,
conversions
*
reviewing
analy!cs
*
wri2ng
performance
reports
*
recommending
strategies
*
alloca2ng
resources

54. and imagine if that was only the beginning . . .

55. The DeepMind team at Google has built a machine that taught itself
how to play and win over 49 Atari 2600 games from the 1980s
Image:
NML32/YouTube Source:
The
New
Yorker,
Ar2ficial
Intelligence
Goes
To
The
Arcade

56. “It is programmed to find a score rewarding, but is given
no instruction in how to obtain that reward.
“Its first moves are random, made in ignorance of the
game’s underlying logic. Some are rewarded with a treat
—a score—and some are not.
“Buried in the DeepMind code, however, is an algorithm
that allows the juvenile A.I. to analyze its previous
performance, decipher which actions led to better
scores, and change its future behavior accordingly.”
Source:
The
New
Yorker,
Ar2ficial
Intelligence
Goes
To
The
Arcade

57. “It is programmed to find a score rewarding, but is given
no instruction in how to obtain that reward.
“Its first moves are random, made in ignorance of the
game’s underlying logic. Some are rewarded with a treat
—a score—and some are not.
“Buried in the DeepMind code, however, is an algorithm
that allows the juvenile A.I. to analyze its previous
performance, decipher which actions led to better
scores, and change its future behavior accordingly.”
Source:
The
New
Yorker,
Ar2ficial
Intelligence
Goes
To
The
Arcade

58. What inevitably comes next are
marketing intelligence engines
that process data and recommend actions
to improve performance based on
probabilities of success.

59. inputs (time and money)
+
outputs (projects and campaigns)
+
outcomes (performance data)

60. “The ability to create
algorithms that imitate,
better, and eventually
replace humans is the
paramount skill of the next
one hundred years. As the
people who can do this
multiply, jobs will disappear,
lives will change, and
industries will be
reborn.”

61. 3 STEPS TO GET STARTED

62. #1
Evaluate repetitive, manual marketing tasks that could
be intelligently automated.

63. #2
Assess opportunities to get more out of your data—
discover insights, predict outcomes, devise strategies,
personalize content across channels, and tell stories at
scale.

64. #3
Consider the AI capabilities of your existing marketing
technology, and explore the potential of emerging AI
solutions.

65. Learn more at
www.MarketingAIinstitute.com

66. paul
roetzer
paul@pr2020.com
@paulroetzer
CEO
|
PR
20/20
creator
|
Marke2ng
Ar2ficial
Intelligence
Ins2tute
author
|
The
Marke5ng
Performance
Blueprint
(Wiley,
2014)
&
The
Marke5ng
Agency
Blueprint
(Wiley,
2012)
www.pr2020.com