AI and machine learning can enhance marketing efforts in several ways: - They allow marketers to analyze large amounts of customer data to better understand customers and segment them into precise groups. - Tools like sentiment analysis and web scraping can provide insights into customers' opinions and behaviors. - AI can optimize marketing campaigns and personalize content for each customer segment. - Chatbots and natural language generation can automate content creation at scale. While AI brings benefits like increased efficiency and customer insights, marketers also face challenges of ensuring ethical data use, demonstrating AI's value, and adapting to the changing landscape.

2. ➢ Introduction
✓ AI, ML
✓ AI IN Marketing.
➢ AI implementation in Marketing.
✓ Why is AI Marketing Important?
✓ How to use AI and ML to enhance your
marketing strategies, campaigns, and
performance.
✓ Discover some of the best tools and
platforms that can help you leverage the
power of AI and ML in your marketing
efforts.
➢ How to set up Artificial intelligence.
➢ Other applications of artificial intelligence in
marketing
➢ Benefits & and challenges for Ai marketing

5. AI
learning from data
ML
Definition
DL

6. AI
AI stands for artificial intelligence, which is the ability of
machines or software to perform tasks that normally require
human intelligence, such as understanding natural
language, recognizing images, making decisions, and
learning from data
ML
DL

7. AI
learning from data
ML
ML stands for machine learning,which is a subset of AI
that focuses on creating systems that can learn from
data and improve their performance without explicit
programming
DL

8. AI
learning from data
ML
DL
Dl stands for Deep learning which is a subset of
machine learning, which is essentially a neural
network with three or more layers. These neural
networks attempt to simulate the behavior of
the human brain—albeit far from matching its
ability—allowing it to “learn” from large amounts
of data. While a neural network with a single
layer can still make approximate predictions,
additional hidden layers can help to optimize
and refine for accuracy.

9. AI IN MARKETING
understand your
customers better
analyzing their
behavior
Segment your
customers
Collect huge amounts
of data
highly personalized
Content
Right message
Right person.
at the right time.

10. • AI in marketing is the use of customer
data, machine learning, and other
computational concepts to predict a
person's action or inaction.
• It can take on huge amounts of data and
help marketers easily segment them as
such marketers can further break down
Data to create customized content for
their audience.
• AI solutions provide marketers with
deeper knowledge of consumers and
prospective Clients enabling them to
deliver the right message to the right
person at the right time.

11. Marketeers can use AI
solutions to take these
profiles as step further,
refine marketing
campaign and create
highly personalized
Content.
AI in marketing is the
process of utilizing
data, models,
mathematics and
algorithms to generate
insights that can be
used by marketers

12. 01
02
03
04
Understand your customers
they can help you understand
your customers better by
analyzing their behavior,
preferences, needs and
feedback.
Optimize your marketing
Optimize your marketing
channels and campaigns by
testing different variations,
predicting outcomes and
allocating resources
efficiently.
Personalize your marketing
Personalize your marketing
messages and offers to each
customer based on their
profile, context, and stage in
the customer journey.
Segment your customers
Segment your customers into
more specific and relevant
groups based on their,
characteristics interests and
actions.
WHY IS AI
MARKETING
IMPORTANT
AI implementation in Marketing.

13. AI in Marketing
Uses
AI And ML
Customer
Segmentation
Web
Scraping
Survey
Content
Creation
Market
Research
Social
Media
Marketing
Clustering
Natural
language
generation
Sentiment
analysis

14. How to use AI and ML to enhance
your marketing strategies,
campaigns, and performance.
• How to use AI and ML for market research and
analysis.
✓Market research and analysis are essential for any
marketing department as they help you understand
your market size, trends, opportunities, threats,
competitors, and customers.
✓By using AI and ML, you can automate and enhance
your market research and analysis process and gain
more insights and intelligence from your data.

15. AI implemnting in Marketing.
1.1 Why is AI Marketing Important
▪ How to use AI and ML for market research and
analysis.
The ways to use AI and ML for market research and
analysis are:
➢ web scraping
➢ Survey
Web scraping is the process of extracting data from
websites and online sources such as social media,
blogs, forums, reviews or news
Web scraping can help you collect large amounts of data
about your market and customers such as their
demographics, preferences, opinions, sentiments and
behaviors.
You can then use AI and ML to analyze and visualize this
data and discover patterns, trends, correlations,
and insights that can help you make better marketing
decisions.

16. use web scraping
to track your own
online reputation
and see how your
customers are
reacting to your
marketing
campaigns.
3
see what they're
offering, how
they're pricing
their products,
what their
customers are
saying about
them.
2
you can use
web scraping
to monitor
your
competitor's
websites and
social media
accounts
1
use AI and ML to
compare your
data with your
competitors and
identify your
strengths,
weaknesses,
opportunities and
threats.
4
How to use AI and ML for market research and analysis.

17. ▪ How to use AI and ML for market research and analysis.
• Surveys are a traditional method of collecting data
from your customers or potential customers by asking
them questions about their needs, wants,
expectations, and satisfaction.
• Surveys can help you understand your customers
better and tailor your marketing strategies accordingly.
• However, surveys can also be time-consuming, costly
and prone to errors and bias.
• By using AI and ML, you can improve your survey
design, distribution, analysis, and interpretation.

18. You can use
natural language
processing to
understand the
meaning and
sentiment of your
respondents
answers.
3
You can also
use AI and ML
to analyze your
survey results
more efficiently
and accurately.
2
you can use
AI and ML to
create more
engaging and
personalized
surveys that
can increase
your
response rate
and quality.
1
You can also use
ML algorithms to
segment your
respondents into
different groups
based on their
characteristics
or responses.
4
How to use AI and ML for market research and analysis.
You can then
use data
visualization
tools to present
your findings in
a clear and
compelling way.
5

19. Customer segmentation and
targeting are crucial for any
marketing department
1
they help you divide your customers
into smaller and more homogeneous
groups based on their characteristics,
interests, and behaviors.
2
By using AI and ML, you can create more
accurate and dynamic customer
segments and deliver more relevant and
personalized marketing messages and
offers to each segment.
3
How to use AI and ML for customer segmentation and targeting.

20. One of the ways to use AI and ML for customer
segmentation and targeting is to use clustering.
Clustering is a machine-learning technique that groups
data points based on their similarity or proximity.
1
Clustering can help you discover hidden
patterns and structures in your customer
data and create segments that are not
obvious or predefined.
2
You can then use these segments to tailor your
marketing strategies accordingly.
3
you can use clustering to segment your
customers based on their purchase history,
browsing behavior, and product preferences.
4
You can then use these segments to create
different marketing campaigns such as cross-
selling, upselling or loyalty programs.
5
How to use AI and ML for
customer segmentation
and targeting.

21. Content creation and curation are vital for any marketing
department as they help you produce and distribute engaging
and valuable content for your audience.
By using AI and ML, you can automate and enhance your
content creation and curation processes and generate more
original and relevant content for your marketing campaigns.

22. What are the potential
uses of NLG?
NLG can help you
create content that is
informative,
persuasive, creative,
or entertaining
depending
on your goal and
audience.
What is NLG, and how
does it relate to NLP
NLG is a machine
learning technique
that converts data
or information into
natural language.
Text, also known
as NLP.
How can AI and ML
be applied to
content creation
One of the ways to
use AI and ML for
content creation
and curation is to
use natural
language
generation or NLG.
Example 1
you can use NLG
to create content
such as headlines,
slogans, captions,
descriptions,
summaries,
reviews, or stories.
Example 2
You can also use NLG to
create content in
different styles,
languages, tones or
formats.
And to enhance your
marketing materials
such as websites, blogs,
emails, ads, social media
posts, and videos.
03 04 05
02
01

23. Social media marketing is one of the most popular
and powerful marketing channels
It allows you to reach and interact with your
audience on various platforms such as Facebook,
Twitter, Instagram, and YouTube.
By using AI and ML, you can enhance your social
media marketing strategies and increase your
reach, engagement, conversion, and loyalty.

24. How to use AI and ML for social media marketing
One of the ways to use AI and ML for social media
marketing is to use sentiment analysis.
Sentiment analysis is a machine learning technique
that detects and measures the emotions, opinions
and attitudes of your audience based on their text or
voice input.
Sentiment analysis can help you understand how your
audience feels about your brand, products, services,
or campaigns.

25. How to use AI and ML for social media marketing
For example,
you can use sentiment analysis to monitor your social
media mentions and comments and
see if they are positive, negative, or neutral.
You can also use sentiment analysis to measure your
social media performance and see how your audience
reacts to your posts, videos, or ads.
You can then use sentiment analysis to improve your
social media content and communication and respond to
your audience's feedback more effectively.

26. Other applications of artificial intelligence in marketing:
✓ Chat GPT is a new artificial intelligence
technology that enables computers to understand
and respond to natural language input.
• Chat GPT uses deep learning to interpret input
from humans and other software agents, and it
then provides real-time responses.
• Chat GPT can be used to build chatbots that can
understand and respond to human conversation.

28. 1
2
3
6
5
4
This to the AI on a test
bench to see how it will
respond to commands from
Consumers
Hire an AI professional.
hire a digital
marketing
professional. How to set up AI?

29. 01
02
03
04
You can achieve higher
customer satisfaction,
loyalty, retention, and
advocacy.
It will lower the cost of
digital marketing
And most importantly,
you can boost your
marketing ROI by
reducing costs and
increasing revenues
You can also increase
your brand awareness,
reputation, and
authority.
BENFITS
AND AI IN
MARKETING

30. CHALLANGES AI IN MARKETING
▪ CHALLENGES
➢Training time and data quality.
AI marketing tools don't automatically know which actions to take to
achieve marketing goals.
They require time and training just as humans do.
➢Privacy.
Digital marketing teams need to ensure they are using consumer data
ethically and in compliance with standards or risk heavy penalties and
repetition Damage.

31. CHALLANGES AI IN MARKETING
➢Getting buy-in
• it can be difficult for digital marketing teams to demonstrate the value of AI
marketing investments to business stakeholders.
➢Deployment Best Practices
Because AI Marketing is a newer tool in the digital marketer’s toolbox, definitive
best practices haven't yet been established to guide marketing teams’ initial
deployment.
Adapting to a changing marketing landscape.
• With the emergence of AI, marketing comes with a disruption in day-to-day
marketing operations.

32. Prepared by: Yara Hossam-Eldin, Mohamed Khater