Consider how much time your team spends reviewing marketing analytics, generating data-driven insights and recommendations, and devising intelligent 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 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.
Marketing in the Machine Age: The Path to a More (Artificially) Intelligent Future
marketing in the machine age
the path to a more (artificially) intelligent future
founder & CEO | PR 20/20
creator | Marketing Artificial Intelligence Institute@PaulRoetzer www.PR2020.com
Can we automate
Can we use machines
to write blog posts
Image: Franck Calzada/YouTube
The Associated Press “writes”
10x more earnings reports using
Automated Insights NLG* technology.10x
*NLG = natural language generation@PaulRoetzer
We implemented NLG with Google Analytics reports,
cutting analysis and production time by more than 80%.
@PaulRoetzer Image: Automated Insights
What we’ve learned has dramatically
altered my view of what’s possible
today, and in the near future.
Image: Timothy Neesam
Consider how much !me your marke2ng 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
wri%ng performance reports
recommending content strategies
dra7ing social media updates
planning blog post topics
building email workﬂows
Copyright 2017 PR 20/20. All rights reserved.
Now imagine if machines performed the
majority of those activities,
and a marketer’s primary role
was to enhance rather than create.
Artificial intelligence is
accelerating us toward a more
intelligently automated future . . .
“The science of making machines smart.”
— Demis Hassabis, Co-Founder & CEO of DeepMind
(which in turn augments human knowledge and capabilities)
Source: Rolling Stone
an algorithm is a
set of instructions that
tells the machine what to do.
Except with AI the machine
can create its own algorithms,
determine new paths, and
unlock unlimited potential
to advance marketing,
THEN send three-part email campaign.
IF visitor downloads ebook,
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?
the marketing automation we see
today is, ironically, largely manual.
Marketing automation platforms save time,
increase efficiency and productivity, and
BUT . . .
Marketing automation platforms generally
do NOT provide deep insights into data,
recommend actions, predict outcomes
or create content.
Source: BBC: Is A.I. the Problem or the Solution?
AI takes very specific (narrow)
and complex data-driven
problems, and then devises
and executes solutions.
90% of all data in the world
has been created in the last 2 years
Marketers have access to data from dozens of sources:
social monitoring, media monitoring, web analytics,
email, call tracking, sales, advertising, remarketing,
ecommerce, mobile apps. . .
We have a finite ability to process
information, build strategies,
create content at scale, and
achieve performance potential.
Image: Wikimedia Commons
Algorithms, in contrast, have an almost
infinite ability to process data, and deliver
predictions, recommendations and
content better, faster and cheaper.
And yet marketing remains
largely human powered, with a
bit of automation mixed in.
“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
Senior director of process management, UPS
Source: Wall Street Journal
NETFLIX uses algorithms to suggest content
and manufacture shows based on subscriber
viewing habits and preferences.
Source: Ne*lix Tech Blog
75% of what people watch on Netflix is from some
sort of algorithm-generated recommendation
Source: Ne*lix Tech Blog@PaulRoetzer
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.
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 . . .
Source: Social Media Frontiers
“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
“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
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.
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.”
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)
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.”
"Cognitive technology is there to extend and amplify
human expertise, not replace it.”
— Rob High, Chief Technology Officer, IBM Watson
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.
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.
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.