The document discusses the role of artificial intelligence (AI) and machine-based intelligence in marketing, highlighting various applications such as customer insights, personalized advertising, and predictive analytics. It also provides market forecasts for AI technologies, including machine learning, deep learning, and augmented reality, indicating significant growth in these sectors. Additionally, it notes that AI has the potential to transform numerous industries, including healthcare, finance, and manufacturing.

1. ARTIFICIAL INTELLIGENCE
Disruption by machine based intelligence
1

2. Artificial Intelligence Helping Marketers
Unlocking deeper customer insights
2

3. Machine Based Intelligence
AI (Artificial
Intelligence)
ML (Machine
Language)

4. Vision-based Marketing
Compiled by author from source: hugeinc.com Image Source: Google Images
4
Visual retail
analytics and
targeting
UGC, image
and video
recognition
Smart digital
asset
management
Goal: Increase operational efficiency

5. Language-driven AI
Compiled by author from source: hugeinc.com Image Source: Google Images
5
Chatbots/UI’s
(User Interface)
Sentiment
analysis
Marketing
message
generation
Goal: Improve Customer Relationships

6. Insights & Discovery
Compiled by author from source: hugeinc.com Image Source: Google Images
6
Programmatic
Advertising
Real-time
personalization
Lookalike
audience
modeling
Goal: Optimize Marketing Spend

7. Anticipation & Decision Making
Compiled by author from source: hugeinc.com Image Source: Google Images
7
Recommendation
engines
Anticipatory
design
Predictive
analytics
Goal: Increase Sales

8. IBM’s Watson
Technology
AI travel companies apply cognitive
to social data to understand what a
destination is really like and who it will
appeal to
ML Watson will analyze sleep and food daily
activity, which they share with a health and
fitness app that shows insights that
the users with other similar members
Customers are demanding a
personalized experience
from brands, marketers will
have to rely more heavily on
machine based intelligence
Compiled by author from source: digitalagencynetwork.com Image Source: Google Images
8

9. Propensity Modeling
Propensity modeling is one goal of a
ML project
The ML algorithm is fed large
amounts of historical data, and it uses
this data to create a propensity model
which is able to make accurate
predictions about the real world
Compiled by author from source: smartinsights.com Image Source: Google Images
9

10. Lead Scoring
Very low
propensity to
buy
• Don’t waste
money on these
customers
Medium
propensity to
buy
• Make special
offers/provide
discounts
High
propensity to
buy
• Don’t offer
specials/they will
buy anyway
ML Propensity models can
score leads based on certain
criteria
A sales team can verify how
'hot' a lead is; if it’s worth
devoting time to
Compiled by author from source: smartinsights.com
10
Important in B2B businesses
with consultative sales processes

11. Subscriber Churn
AI lets mobile carriers understand the
behavior of a customer at risk for churn
early, allowing preventative action to
course correct the customer relationship
• New data or pricing incentives
• Encourage engagement
• Create enticing renewal offers
Sprint, Verizon, T-Mobile,
and AT&T — are heavily
investing in emerging AI
solutions to help predict
and prevent customers
leaving for another carrier
Compiled by author from source: marketingland.com Image Source: Google Images
11

12. AUGMENTED
REALITY
On the display network, ads
are generally shown in a two-
dimensional interface
Where viewers could once
only see ads directly ahead of
them, they will now be able to
see display ads in their
peripheral vision
AR also allows for more
detailed ads, due to the higher
pixel/display size ratio seen in
AR versus 2-D monitors
3 dimensional thinking
AR opens up a wide new
range of possibilities in
the third dimension
Compiled by author from source: forbes.com Image Source: Google Images
12

13. Market Forecast
A look at who’s investing in what technology & the economic
outlook
13

14. AI Global Market
Forecast To Rise
Target Audience:
AI Designers &
Manufacturers
Research
Organizations
AI Investors
Startup Companies
Raw Material
Suppliers
Government
Market Research
Consulting
The global AI market is
expected to be worth USD
16.6B and is forecast to rise
at a (CAGR) of 62.9% from
2016 to 2022
Compiled by author from source: marketsandmarkets.com
14

15. Machine Learning
Market Forecast
Target Audience:
System Integrators
AI Solution/Service
Providers
Enterprise Data
Center
Mobile Network
Operators
Cloud Service
Providers
Data Center
Software Vendors
Analytics Providers
Estimated to grow from USD
613.4M in 2016 to USD
3,755.0M by 2021, at a
(CAGR) of 43.7% from 2016
to 2021
Compiled by author from source: marketsandmarkets.com
15

16. Deep Learning
Market Forecast
Target Audience:
Universities
Government
Agencies
Aerospace
Defense
Automotive
Industrial
Medical
This market is expected to
be worth USD 1772.9M by
2022, growing at a (CAGR)
of 65.3% between 2016 and
2022
Compiled by author from source: marketsandmarkets.com
16

17. NLP Market
Forecast
Target Audience:
NLP Service
Providers
System Integrators
Consulting Firms
Research
Organizations
Resellers/Distributor
s
Government
Agencies
Media
Estimated to grow
from USD 7.63B in
2016 to USD 16.07B by
2021, at a (CAGR) of
16.1%
Compiled by author from source: marketsandmarkets.com
17

18. AR/VR Market
Forecast
Target Audience:
Mobile Manufacturers
Software Providers
Consulting Firms
Research Organizations
AR Forums/Alliances
Investors
The global AR market is
expected to reach USD 117.40B
by 2022 at a (CAGR) of 75.72%
The global VR market is
expected to reach USD 33.90B
by 2022 at a (CAGR) of 57.84%
Compiled by author from source: marketsandmarkets.com
18

19. Smart Machines
Research expects the autonomous robot
category to account for the largest share 22.8%
• Forecast Timeline: 2024
• Market Value Projected: $41.22B
This market is expected
to increase to nearly
$15.3B in 2019, a (CAGR)
of 19.7%
Compiled by author from source: techemergence.com Image Source: Google Images
19

20. AI In The Investment Community
The algorithmic trading use
case remains the top use case
among all of the 191 use
cases identified
60% of the use
cases are
related to big
data
40% are related
to image or
object
recognition
Compiled by author from source: techemergence.com Image Source: Google Images
20
Roughly 50% Of
The Hedge Fund
Assets Traded By
2025 Will Be AI-
driven

21. Percent By Resources
Top 3 highest
number of use cases
by percentage of
resources spent:
Cyber Intelligence
(22%)
Healthcare (10%)
Manufacturing
Automation (8%)
Compiled by author from source: techemergence.com
21

22. Potential Industries Transformed
Including:
AI has the potential to transform
entire industries
Manufacturing
Media
Advertising
Financial services
Health care
Retail
Transportation
Automotive
Compiled by author from source: blog.marketresearch.com Image Source: Google Images
22

23. CONTACT US FOR THE FULL
PRESENTATION:
Mediacontact USA Inc.
13575 58TH Street North #160
Clearwater, Fl. 33760
T: 727 538 4112
E: contact@mcusa.co
www.mediacontactusa.com

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