[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.
Cognitive Content Marketing: The Path to a More (Artificially) Intelligent Future
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.
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
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
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
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
19. Marketing automation platforms
generally do NOT provide deep
insights into data, recommend
actions, predict outcomes
or create content.
@PaulRoetzer #intelcontent
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
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
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
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.
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
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
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
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
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
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.
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.