[Presented at Intelligent Content Conference 2017] Consider how much time your team spends discovering keywords; planning blog post topics; writing, optimizing, personalizing and automating content; testing landing pages; scheduling social shares; reviewing analytics and defining content strategies. Now imagine if a machine performed the majority of those activities and a marketer's primary role was to enhance rather than create. Machines are not going to replace content marketers in the near term, but artificial intelligence is accelerating us toward a more intelligently automated future. Come explore the present and future potential of artificial intelligence, and discover AI-powered technologies that can drive marketing performance and transform your career. * Understand what the disruption of other industries can teach us about the inevitable impact artificial intelligence will have on the marketing industry. * Learn about the marketing technology companies that are leading the way in advanced automation, predictive analytics and machine-generated content. * Apply new technologies and processes to make your content marketing more efficient and effective.

1. @TwitterHandle • #intelcontent
Cognitive Content Marketing
The Path to a More (Artificially) Intelligent Future
Paul Roetzer
Founder & CEO | PR 20/20
Creator | Marketing AI Institute
@PaulRoetzer
@PaulRoetzer • #intelcontentCopyright 2017 PR 20/20. All rights reserved.

2. Can we automate
content creation
through artificial
intelligence (AI)?
@PaulRoetzer

3. Can we use machines
to write blog posts
at scale?
Image: Franck Calzada/YouTube #intelcontent

4. The Associated Press “writes”
10x more earnings reports using
Automated Insights NLG* technology.10x
*NLG = natural language generation@PaulRoetzer #intelcontent

5. We implemented NLG with Google Analytics reports,
cutting analysis and production time by more than 80%.
@PaulRoetzer Image: Automated Insights

6. What we’ve learned has dramatically
altered my view of what’s possible
today, and in the near future.
Image: Timothy Neesam

7. Consider how much !me your marke?ng team spends . . .
crea?ng ad copy
managing digital ad campaigns
tes?ng headlines, landing pages, ads
scheduling/publishing social shares
predic?ng opens, clicks, conversions
reviewing analy!cs
wri?ng performance reports
recommending content strategies
draCing 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 2017 PR 20/20. All rights reserved.
@PaulRoetzer #intelcontent

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

9. Artificial intelligence is
accelerating us toward a more
intelligently automated future . . .

10. “The science of making machines smart.”
— Demis Hassabis, Co-Founder & CEO of DeepMind
(which in turn augments human knowledge and capabilities)
Source: Rolling Stone
#intelcontent

11. Source: John Koetsier
#intelcontent

12. an algorithm is a
set of instructions that
tells the machine what to do.
@PaulRoetzer #intelcontent

13. Except with AI the machine
can create its own algorithms,
determine new paths, and
unlock unlimited potential
to advance marketing,
and mankind.

14. @PaulRoetzer

15. THEN send three-part email campaign.
IF visitor downloads ebook,
@PaulRoetzer #intelcontent

16. What if there are 10,000 downloads,
across five personas, originating
from multiple channels (social,
organic, paid, direct) that require
personalized emails and website
experiences based on user history?
@PaulRoetzer #intelcontent

17. the marketing automation we see
today is, ironically, largely manual.
@PaulRoetzer #intelcontent

18. Marketing automation platforms
save time, increase efficiency and
productivity, and drive performance.
BUT . . .
@PaulRoetzer #intelcontent

19. Marketing automation platforms
generally do NOT provide deep
insights into data, recommend
actions, predict outcomes
or create content.
@PaulRoetzer #intelcontent

20. Source: BBC: Is A.I. the Problem or the Solution?

21. AI takes very specific (narrow)
and complex data-driven
problems, and then devises
and executes solutions.

22. 90% of all data in the world
has been created in the last 2 years
Source: IBM

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

24. We have a finite ability to process
information, build strategies,
create content at scale, and
achieve performance potential.
@PaulRoetzer #intelcontent

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

26. @paulroetzer www.pr2020.com
And yet content marketing
remains largely human powered,
with a bit of automation mixed in.
#intelcontent

27. The future may be
closer than you think.

28. @TwitterHandle • #intelcontent
AGENDA
@TwitterHandle • #intelcontent
The Disruption of Industries
@PaulRoetzer • #intelcontent

29. @paulroetzer www.pr2020.com
60% of all trades are executed by computers
with little or no real-time oversight from humans.
Source: Christopher Steiner, Automate This

30. @paulroetzer
avg 120 stops/day

31. what is the possible number of
alternatives for ordering those stops?
@PaulRoetzer #intelcontent

32. 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

33. “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
combinations.”
Jack Levis
Senior director of process management, UPS
Source: Wall Street Journal

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

35. 75% of what people watch on Netflix is from some
sort of algorithm-generated recommendation
Source: NeGlix Tech Blog #intelcontent@PaulRoetzer

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

37. Source: Tesla

39. #intelcontent@PaulRoetzer

40. @TwitterHandle • #intelcontent
AGENDA
@TwitterHandle • #intelcontent
The Marketing Machine Age
@PaulRoetzer • #intelcontent

41. “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

42. Source: Salesforce
#intelcontent@PaulRoetzer

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 . . .
#intelcontent@PaulRoetzer

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

45. search, voice recogni!on, language transla!on, robots, driverless cars . . .
#intelcontent@PaulRoetzer

46. “Alphabet Inc.’s Google named the head of its artificial-intelligence
research to run its search engine, demonstrating the importance of
the rapidly evolving technology to the company’s main profit engine.”
Source: The Wall Street Journal
#intelcontent@PaulRoetzer

47. Image: Wikimedia CommonsSource: IBM
The story of ar?ficial intelligence can’t be told without IBM ,
which possesses an es!mated 825 AI-related patents.

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

49. Source: Salesforce
#intelcontent@PaulRoetzer

50. Source: Campaign
In October, lingerie retailer Cosabella replaced its
digital agency with an AI platform named 'Albert'.
Since then it has more than tripled its ROI and
increased its customer base by 30 percent.
#intelcontent@PaulRoetzer

51. Source: Popular Science
“IBM used machine learning and experimental Watson
APIs, parsing out the trailers of 100 horror movies. It did
visual, audio, and composition 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.”
#intelcontent@PaulRoetzer

52. Source: The Drum
“Content creation is something that we have been doing
for a very long time . . . what I want to start
experimenting with is automated narratives.”
This experimentation will explore how AI can be applied
to everything from choosing music, updating social
media and even writing scripts . . .
(Mariano Bosaz, Coca-Cola’s global senior digital director, interview with AdWeek)
#intelcontent@PaulRoetzer

53. Source: The Guardian
“A machine will win a Pulitzer one day,”
predicts Kris Hammond from Narrative
Science, a company that specialises in
natural language generation. “We can tell
the stories hidden in data.”

54. "Cognitive technology is there to extend and amplify
human expertise, not replace it.”
— Rob High, Chief Technology Officer, IBM Watson
#intelcontent@PaulRoetzer

55. @TwitterHandle • #intelcontent
AGENDA
@TwitterHandle • #intelcontent
3 Things to Know
@PaulRoetzer • #intelcontent

56. #1
It is still very early. Many of the rising AI tech
companies have significant venture capital funding, but
limited market success to prove the products work and
that the models are scalable.

57. #2
Artificial intelligence requires massive amounts of data
(structured and unstructured) and customized
solutions, so large enterprises are more likely to see
short-term benefits from AI investments.

58. #3
There is a push to make AI technology more affordable
and accessible. The challenge will be finding technical
talent capable of building and executing AI solutions.

59. @TwitterHandle • #intelcontent
AGENDA
@TwitterHandle • #intelcontent
3 Steps to Get Started
@PaulRoetzer • #intelcontent

60. #1
Evaluate repetitive, manual marketing tasks that could
be intelligently automated.

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

62. $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

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

64. #intelcontent@PaulRoetzer

65. #intelcontent@PaulRoetzer

66. #3
Consider the AI capabilities of your existing marketing
technology, and explore the potential of emerging AI
solutions.

67. @TwitterHandle • #intelcontent
AGENDA
@TwitterHandle • #intelcontent
The Next Frontier
@PaulRoetzer • #intelcontent

68. draCing 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
crea?ng ad copy
managing digital ad campaigns
tes?ng headlines, ads
scheduling social shares
predic?ng conversions
reviewing analy!cs
wri?ng performance reports
recommending strategies

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

70. www.MarketingAIinstitute.com

71. Paul Roetzer
Founder & CEO | PR 20/20
Creator | Marketing AI Institute
paul@PR2020.com
www.PR2020.com
www.MarketingAIinstitute.com