eMarketer Webinar: Artificial Intelligence—The Future Is Already Here

© 2016 eMarketer Inc.
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Artificial Intelligence for Marketers:
The Future is Already Here
Victoria Petrock
Principal Analyst, Industries
October 27, 2016

What Exactly is AI?

Hollywood has done some dramatic portrayals
Image credits: Cryteria/Wikimedia Commons, Stephen Bowler/Wikimedia Commons, Helloclaire/Wikia.com
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HAL 9000 Terminator Robots Samaritan

AI means
different
things to
different
people
The most common
definition involves the
simulation of human
intelligence and
decision-making
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There is a lot
of confusing
terminology!
Some terms represent
specific technologies,
others are used
interchangeably
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AI comprises several core technologies, but is
often known by different names
 Machine learning
 Neural networks
 Deep learning
 Expert systems
 Computer vision
 Machine translation
 Natural language processing
 Natural language generation
 Chatbots
 Virtual digital assistants
 Computational linguistics
 Recommender systems
 Predictive analytics
 Cognitive computing
 Augmented intelligence
 Man-machine learning
 Algorithmic assistance
 Cognitive augmentation
 Intelligence amplification
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Core
Technologies
Major
Applications
Other
Names

AI has had a long and difficult history
“Artificial intelligence
as a name was
reserved for
mysterious stuff
that was beyond the
state of the art.”
—Mark Torrance,
Chief Technology
Officer, Rocket Fuel
 A lot of early researchers
overpromised on AI, giving
it a bad rap
 As new technologies based
on AI became mainstream,
they were renamed other
things
 Computing power has
recently advanced to support
more of AI’s full potential
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Some AI isn’t always called AI
“We prefer to think of
machine learning as
‘algorithmic
assistance.’”
—Mike Paquette, Head of
Security Strategy, Elastic
“We call it machine
learning, because I
think [artificial
intelligence]
sometimes can spook
some folks.”
—Mahesh Tyagarajan,
Chief Product Officer,
RichRelevance
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And many businesspeople are using AI without
even knowing it
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Source: Narrative Science, 2016
37%Businesspeople who say they
are using AI technologies in the
workplace
88%Businesspeople who are
actually using technologies that
rely on AI

There is more awareness of newer technologies,
though many are AI-based
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Image Credit: Narrative Science

So … what are we really talking about?
Neural Networks: Machine learning algorithms trained with specific sets of data
points, which they use to guess at an answer to a query. The network’s guess is then
compared with the correct answer for each data point. If errors occur, the “neurons” are
tweaked and the process repeats itself until the error levels decrease.
Deep Learning: A branch of machine learning concerned with building and training
neural networks with multiple layers. Each layer of a network can find patterns in the
output of the layer above it. Deep networks excel at sorting and classifying data and
identifying anomalies in data patterns.
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Machine Learning: The branch of AI computing that involves training algorithms to
perform tasks by learning from previous data and examples rather than explicit
commands programmed by humans.

AI is already a part of everyday life
Self-Driving Cars Fraud Detection Digital Assistants
Image credits: Michael Shick/Wikimedia Commons, Pixabay, Tej3478/Wikimedia Commons
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Global estimates for the AI market are disparate,
reflecting the market’s relative immaturity
$5B by 2020
Source: MarketsandMarkets, February 2016
$15B by 2021
Source: BCC Research, March 2016
$37B by 2025
Source: Tractica, August 2016
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Why now? Several factors are driving adoption
Image credits: Pixabay
Successful use
cases
Collaborative
academic
community
The internet of
things (IoT) and
data overload
More powerful,
yet smaller and
less expensive
computing power
Tech giants with
deep pockets
Innovative
startups
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Tech giants are among the biggest AI investors
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Since 2011, nearly $2.4 billion has been invested
globally in AI startups, over 397 deals
Source: CB Insights, June 2016
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Businesses
across
industries are
taking different
routes to
developing their
AI capabilities

Leveraging AI for
Marketing and Advertising

The many faces of AI for marketing
Image Credits: Pixabay, The Weather Company
Marketing
Intelligence
Lead
Generation
Call-Center
Technology
Bots and
Virtual Assistants
Smarter
Search
Interfaces
Recommender
Systems Content
Creation
Brand
Building
AI-Driven
Advertising
Campaign
Optimization

Marketing Intelligence

Marketing intelligence is a top use for AI

Turner Broadcasting uses IBM Watson
technology to uncover insights for advertisers
 Watson ingests first- and
third-party, structured
and unstructured data
 Makes automated
recommendations to help
optimize TV campaigns
 Combined with predictive
analytics from Neustar’s
MarketShare product
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BBC uses Thoughtly’s Ellipse to identify themes
in its worldwide content
 Analyzes unstructured
program descriptions and
viewing data
 Identifies overrepresented
and underrepresented
themes in programming
 Helps match programs
with most appropriate
audiences
Image Credits: BBC Worldwide, Thoughtly
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Lead Generation and
Customer Acquisition

Some AI companies specialize in lead and
demand generation
Conversica uses AI to contact, qualify and
nurture sales leads
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Mariana uses AI-based social targeting
to identify and convert sales prospects
Image credit: Mariana Image credit: Conversica

The Weather Company is rolling out interactive
“cognitive” ads
 First advertising
application for IBM Watson
 Will enable consumers to
have voice- or text-based
conversations with brands
 The Campbell Soup Co.,
GSK Consumer Healthcare
and Unilever will be among
the first to try them out
Image Credits: IBM, The Weather Company
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Marketing Optimization

AI is particularly adept at optimizing and
measuring marketing campaigns
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Rocket Fuel uses “moment scoring” to buy and
optimize programmatic advertising
• Platform learns from
customer interaction to
optimize media spend
• Assigns scores to each
“moment” based on the
goal
• Moments are determined
by demographics,
behaviors and/or contexts
Image Credits: Rocket Fuel
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Harley-Davidson NYC is using Adgorithms’
“Albert” to build lookalike models
“Currently, we attribute 40% of
Harley-Davidson New York
motorcycle sales to Albert.
… Albert not only determines
when and where we should
display content, but also
provides feedback on how that
content is performing.”
—Asaf Jacobi, President,
Harley-Davidson of New York City
Image Credits: Harley Davidson of NYC, Adgorithms
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Smarter Search Interfaces

Google uses RankBrain to help with every search
 Machine learning assists
with vague and ambiguous
queries
 AI is the third-highest
signal (out of more than
200) contributing to a
search query result
 Will affect how content is
created going forward
Source: Google; Image Credit: Pixabay
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LHW works with WayBlazer to improve the hotel
research and booking process
 First Watson application
in travel industry
 Can highlight unique
features of hotels for
specific customers
 Trip Discovery tool enables
searches by concepts
(beaches, family, etc.) and
pulls up personalized
images
Image Credit: WayBlazer
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Recommender Systems

Recommender systems are getting better
Pandora uses content-based
filtering based on user preferences
to suggest songs similar to ones
liked
Amazon uses collaborative filtering
to customize users’ searching and
browsing experiences based on
what similar others have liked
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Stitch Fix has used recommendation algorithms
since 2012
 Augments human stylists
with machine learning
 Uses hundreds of
algorithms to match
clothing and accessories
to tastes and budgets
 AI “most salient aspect of
company”
Image Credit: Stitch Fix
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Bots and Virtual Assistants

Swedbank uses “Nina” to communicate with
customers and free up reps to sell
 Uses natural language
processing technology
from Nuance
Communications
 Answers routine
questions from customers
and frees up service reps
to do more selling
 Handles almost 40,000
conversations a month
Image Credit: Swedbank
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1-800-Flowers and HealthTap use Facebook’s
Messenger bot
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Finds answers to previously posted
questions or connects users with
doctors
Takes orders or connects
customers with human reps

And of course there are physical robots!
Image credits: (c) 2016 Hilton Worldwide, SoftBank
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Hilton’s “Connie” robot concierge answers
guests questions about local attractions and
services
SoftBank’s “Pepper” robot
can read human emotions
and change its behavior
accordingly

Content Creation

About 5% of US businesses using AI are doing
automated reporting or communications
Data Source: Narrative Science, May 2015
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Wordsmith generates more than 1.5 billion
pieces of content per year for 42 industries
“[We] generated more
content than any
company in the
world last year …
everything from AdWords
reporting to ecommerce
product descriptions,
real estate listings and
everything in between.”
—Robbie Allen, Founder and
CEO, Automated Insights
Image Credits: Automated Insights, Yahoo
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Brand Building

Kia worked with Influential and Watson to
amplify its campaign for Super Bowl 50
Image Credit: Kia Motors America
 Analyzed Facebook,
Twitter and Instagram
posts to pick top 100
“social media
influencers” based on
personality traits
 Sent colorful socks to
influencers and asked
them to post with
hashtag #AddPizzazz
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TD Ameritrade worked with Havas Cognitive and
IBM Watson on “Most Confident Fans” Campaign
“It allowed us to test AI with
minimal risk and delivered
learnings that are being
applied to benefit other
areas of the business.”
—Dedra DeLilli, Director,
Social Media and Corporate
Sponsorships, TD Ameritrade
Image Credit: TD Ameritrade

AI for marketing continues to evolve
Image Credit: Fonytas/Wikimedia Commons

Experimentation and patience are key to success
“The most important thing is to
allow freedom to
experiment, because
nobody within organizations
really understands very well
how an AI should work or what
to expect. And there’s no clear
format that will fit all the
different situations.”
—Alberto Rey Villaverde,
Head of Data Science, easyJet
“Be patient and
understand that AI
takes time to learn the
marketplace. … AI is an
opportunity for growth, and
if you have at least the
content or something right,
data will get you there.”
—Asaf Jacobi, President,
Harley-Davidson of
New York City

And experts have other advice, too
 Have a plan: Define an end goal for what you want to
accomplish or a business problem you want to solve.
 Be flexible and open to discovering new things along the way;
be as nimble and agile as possible.
 Don’t jump into anything too overwhelming all at once.
 Do small pilots to test the solution with limited risk.
 Test and learn in stages; work the kinks out before launching
at full scale.
 Be honest about success and failure, and learn from both.
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Where Does This Leave
Marketers?

A sizable
number of
workers are
suspicious
about AI and
worry about
losing their
jobs because
of the
technology
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Their fears are not without merit
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Image Credit: Pixabay
Forrester Research predicts robots and other AI technologies will replace
16% of the US jobs currently done by humans by 2025
?

But it may not be as dire as they think
#eMwebinar
Image Credit: Pixabay
The same study found that AI-related technologies would create 8.9 million
new US jobs in the same timeframe

AI has potential to benefit human workers in
important ways
“[AI lets] the machine do things
it can do very well, but then
allows the human to
bridge that gap. It’s the
human understanding what the
machine is trying to do and
then saying ‘I’m going to help
nudge you so you can do a
better job.’”
—Mahesh Tyagarajan, Chief
Product Officer, RichRelevance
“We’re liberating the marketers
back to the place where they
can drive the marketing
with creativity, with
ideas, and not just by
changing bids and Google
AdWords or scheduling email
campaigns. These are not jobs
for humans. There’s too much
work to be done.”
—Or Shani, Founder and
CEO, Adgorithms

Key takeaways
 After years of false starts, conditions are finally right for
mainstream AI adoption. Forecasts vary widely, but all agree
that the market is growing.
 AI’s use in marketing is still in early stages, but nearly all
industries are experimenting.
 Marketing intelligence, campaign optimization, content
creation, customer experience and brand building are just a few
applications of AI in marketing.
 The jury is still out on the long-term effects AI will have on
marketing jobs, but many experts believe it will free up humans
to do more high-value work.

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Victoria Petrock
Artificial Intelligence for
Marketers: The Future is
Already Here
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Potential of Immersive Digital Marketing Experiences
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