how A.I. is transforming the marketing Mix - Innovation assesment - Gartner Curve - ChatGPT - Open AI Lecture Deck at Solvay Brussels School of Economics & Management - ULB - Commpass

1. (Open) A.I. & Marketing
- Out of the Hype -
Empowering
the Marketing Mix & the Consumer Decision Journey
Hugues L. Rey
18th of April 2024

2. Topics of the Day
Technology Hype &
Marketing
Moving the Marketing
Mix
Empowering the
Consumer Decision
Journey
Effects on Marketing
Jobs

3. How Marketing could exploit A.I. ?
G A R T N E R H Y P E C U R V E V S M A R K E T E E R N E E D S

4. Do you remember
Second Life ?

6. At its peak in 2006, Second Life had
a story on the cover of Business
Week, a 12-page spread in Wired,
and numerous blog posts about
brands like Coca-Cola, Scion and
even the NBA establishing in-
world presences.
Reuters, CNET, CNN and Wired also
set up virtual news bureaus, though
all …
but CNN killed off their in-
world coverage about a year
later.

9. Useful
Usable
Used

10. Do you Zwift ?

11. Worldwide
Phygital
Integration

15. Get Out the
Hype
Mapping
Innovation
Through the
Gartner Curve
Gartner Hype Cycles are a graphic
representation of "the maturity and
adoption of technologies and
applications, and how they are
potentially relevant to solving real
business problems and exploiting new
opportunities"

16. Timing is everything

17. 2022 - Marketing & Advertising
Hype Curve

18. 2023 - Marketing & Advertising
Hype Curve

19. 2023 - Marketing & Advertising
Hype Curve

20. Influence,
Content
Creator,
and Advocacy
(Plateau < 2y)
SLOPE OF
ENLIGHTENMENT

21. 2023 - Marketing & Advertising
Hype Curve

22. Shoppable
Media
(Plateau 2-5 y.)
TROUGH OF
DISILLUSIONMENT

23. 2023 - Marketing & Advertising
Hype Curve

24. PEAK OF
INFLATED
EXPECTATIONS
Generative AI
(Plateau 2-5 y.)

25. 2023 - Marketing & Advertising
Hype Curve

26. Digital twin
of a
customer
(DToC)
(Plateau 5-
10 y.)
A digital twin of a
customer (DToC) is a
dynamic virtual
representation of a
customer that
simulates and learns
to emulate and
anticipate behavior.
Customers can be
individuals, personas,
groups of people or
machines.
DToC gives marketers a
flexible approach to
anticipating a customer’s
state of mind
INNOVATION
TRIGGER

27. For a marketeer …

31. Interacting With
Human
Acting as Human
Speech
Vision and Hearing
Natural Language
Processing
“Machine” Learning
- Recommendation

35. OpenAI is an AI
research and
deployment
company.
Our mission is to
ensure that
artificial general
intelligence
benefits all
of humanity

38. A.I. Omniscience in Marketing
A.I.
is moving
the 4P’s
(Marketing Mix)
to S.A.V.E
A.I.
optimize every
stage of the
Consumer
Decision Journey

39. A.I. Omniscience in Marketing
A.I.
is moving
the 4P’s
(Marketing Mix)
to S.A.V.E
A.I.
optimize every
stage of the
Consumer
Decision Journey

40. A.I. Is moving 4P’s to S.A.V.EEE.
in a Hyper Personalized Relation
Product Place
Price Promotion
Service x Product
= Bespoke Offer
Value Based
Pricing
Access x
(Learn + Apply)
= Experience
Engage, Entertain,
Educate = Unique
Relationship

42. A.I. Is moving Product to Service
in a Bespoke Offer
Product
Service x Product
= Bespoke Offer
1. Recommendation
2. New Features
3. Churn Prediction

44. Pivot 1

45. Pivot 2

47. A recommendation
system generates a
compiled list of items in
which a user might be
interested, in the
reciprocity of their
current selection of
item(s).
It expands users’
suggestions without any
disturbance or
monotony, and it does
not recommend items
that the user already
knows.
USE CASE 1

48. This seems totally logical!
But it is much more subtle and complex …

52. USE CASE 2

53. $6 billion on content this year
◦ If it just presented the most popular selections to everyone, many titles would remain unseen.
◦ Wasted content spend, Less time watching Netflix instead of other networks.
Take-rate on top personalized video recommendations was 3 to 4 times higher than the most popular
videos.
◦ Viewers were exposed to 4 times as many videos using personalized recommendations compared to a list of
the most popular titles.
Recommendations = surface niche titles that wouldn't find an audience on a traditional cable
network, but that its viewers love
◦ Save money on its content & maximize the value of inexpensive titles.
Recommendations lead to meaningful increases in overall engagement with the product (e.g.,
streaming hours) and lower subscription cancellations rates.
◦ Higher lifetime customer values and lower revenue volatility.
◦ Retention rates are already high enough that it takes a very meaningful improvement to make a retention
difference of even 0.1%.

54. By analyzing viewer
data – think 30
million “plays”, 4
million ratings, 3
million searches -
the company was
able to determine
that fans of the
original House of
Cards, which aired in
the UK, were also
watching movies
that starred Kevin
Spacey and were
directed by David
Fincher, who’s one
of the show’s
executive
producers.

55. CHAT GPT – Test

57. Episode 2: "The Betrayal”
Senator Owens discovers Robert's plan and sets out to stop him. However, Karen Thompson
convinces one of Senator Owen's closest allies to betray him, causing a rift in the
Democratic party.
Meanwhile, Robert makes a risky move that puts his career and marriage on the line. The
Thompsons' marriage begins to crumble as Karen realizes the true extent of her husband's
ambitions.
Episode 3: "The Showdown”
As Robert's power grows, he becomes increasingly paranoid, leading to a confrontation with
his wife. Karen Thompson decides to take matters into her own hands, putting herself in
danger to stop her husband's dangerous plan.
Senator Owens and President Santiago team up to stop Robert's plan, leading to a dramatic
showdown in the House of Representatives. In the end, the Thompsons' ambition and lust for
power prove to be their downfall as they are exposed for their corruption and illegal activities.
Episode 1: "The Deal"
Robert Thompson is determined to
pass a bill that will grant him and his
party more power. He strikes a deal
with a powerful corporate leader
who agrees to support the bill in
exchange for a seat at the table.
Karen Thompson pays an essential
role in the negotiation, convincing
the CEO to back her husband's plan.
Meanwhile, President Santiago tries
to stop the bill from passing, but his
efforts are thwarted by Robert's
cunning tactics. As the President's
popularity begins to wane, Robert
and Karen set their sights on the
White House.

59. Churn represents the percentage of lost customers in a given time range
Customer churn is a major threat to every streaming company.
Companies lose $1.6 trillion per year to churn1
USE CASE 3

61. Retention is King

63. Instead of reacting after the customer has
churned, Predict who will not convert
=
Reduce spending + Maximize impact

64. A.I. Is moving Price to Value
Price
Value Based
Pricing
1. Dynamic Pricing
2. Yield Segmentation
3. Predictive &
Prescriptive buying
Paterns

65. Uber: Till 2017 - Prices go up to encourage more drivers to go
online. The increase in price is proportionate to demand

66. Surge Pricing Acceptation Rate
“One of the strongest predictors of whether or not you are going to
be sensitive to surge is how much battery you have left on your cell
phone,” Keith Chen, Uber’s head of economic research said.
In other words, you’re more likely to accept a surge-priced fare, regardless of the price, if your phone’s
about to die because you need a ride home immediately, and if your battery’s death is imminent, you
can’t afford to wait 15 minutes to see if the price drops down again.
Uber knows when its users’ phone batteries are running low because the app switches into power-saving
mode.
“And we absolutely don’t use that to kind of like push you a higher surge price, but it’s an interesting kind
of a psychological fact of human behavior,” Chen said.

68. Fine-tuning price
segmentation
strategies with
insights gained from
AI is helping to
stabilize and
increase margins
and revenues today.

69. AI and machine learning are
helping pricing managers
capture more revenue and
profits by finding how what
a given customer is willing
to pay or optimizing price
across their customer and
product mix.

71. A.I. Is moving Place to Access to generate
a unique experience.
Place
Access x
(Learn + Apply)
= Experience
1. Last Mile
2. Ux Optimisation
3. Usage Suggestion
4. Machine / Human Collab

72. Physical
placement
Merchandising optimization: You
can leverage machine learning and
big data to optimize your online or
offline merchandising.
Shelf audit/analytics: Your
business can use videos, images,
or robots in the retail area to audit
and analyze your use of shelf
space.

73. Digital
Placement
Product Information Management:
Businesses manage and improve all
product information centrally to
improve product discoverability and
appeal. As a result, they
automatically modify and update the
product description, box description,
and all other related information.
Image tagging to improve product
discovery: You can leverage
machine vision to tag your images,
taking into account your users’
preferences and relevant context for
your products.

74. Video Commerce
- with embedded
products
shoppable by
inserting relevant
links and auto-
identify products

75. Kia had more
than 800
websites
where a
customer can
ask about
buying a car

76. CONSUMER BEHAVIOR
ANALYSIS/SUPPORT
è ChatGPT data collection: everything from customer
interactions and demographics to preferences and purchase
history. The data will give you valuable insights into consumer
behavior and empower you to make data-driven decisions for
your brand and your marketing strategies.
è Enhanced Personalization: Recognize user interests and
preferences means that customers will have a more
personalized, more human experience
è Increase customer loyalty and satisfaction: support 24/7,
customers get the answers they need without having to wait
for regular business hours.
“In a way that feels like a more natural human
interaction, so it isn't as off-putting or frustrating
as speaking with other chatbots.”

78. A.I. Is moving Promotion to Engagement,
Entertainment, Education
Promotion
Engage, Entertain,
Educate = Unique
Relationship
1. Content Production
2. Dynamic Creation
3. Insights Automation
4. Micro-Targeting
5. Channel Selection

79. 20 % of all business-
oriented content is
generated by machines
(Gartner)
Client reports
Product descriptions
Campaign summaries
TV programming
Announcements Ratings
analysis,
Online content for clients
Social media updates
…
Wordsmith, a software platform lets you
create sophisticated templates that turn
raw data into unique pieces of writing
about that data. Wordsmith is a natural
language generation (NLG) platform.

81. Did a Human or
a Computer
Write This?

82. Did a Human or a
Computer Write
This?
MARCH 7, 2015

85. Contextual Advertising and Custom Algorithms
By supplying their first-party data, advertisers can train the algorithm to deliver more highly personalized ads and
improve campaign optimization.
2023

88. Cadbury (Mondelez): Amplifying Scale
and Personalization Through AI

90. Heinz: Asserting Brand Identity in the AI
Ecosystem

91. A.I. Omniscience in Marketing
A.I.
is moving
the 4P’s
(Marketing Mix)
to S.A.V.E
A.I.
optimize every
stage of the
Consumer
Decision Journey

92. A.I. empowers each stage of the consumer decision journey

93. Reach/ See
•Help marketeers create engaging and informative content
by suggesting topics and providing insights into audience
preferences.
•Assist with keyword research and optimisation, helping to
improve search engine visibility and attract more visitors to
your website.

94. Improve SEO/keywords analysis
Generative Artificial Intelligences are capable to propose improvements
based on a given input. Therefore, they are also able to:
è write Meta description
è Categorizing search intent on a range of keywords
è Analyse keyword difficulty
è search volume for picking best keyword
Source: https://seo.ai/blog/chatgpt-seo-examples-and-use-cases

96. ChatGPT does not
see the SERP but it
knows the search
intentions!
"Write and classify the keywords of the
theme "winter jumper" according to
whether the search is navigational,
commercial, informational and
transactional in a table"

97. Act - Think
Personalise content and recommendations based on customer behaviour and
preferences, helping to guide potential customers towards conversion.
Assist with lead generation and qualification, providing insights into which leads are most
likely to convert and how to engage them effectively.

99. Dog or Bagel ?

104. Convert - Do
•Provide recommendations and insights to help customers make informed
purchase decisions.
•Assist with lead scoring and qualification, helping to identify the most valuable
leads and guiding them towards conversion.

105. Sephora Visual Artist product à
“try on” cosmetic products
Powered by Modiface AI
technology, the Visual Artist can
map and identify facial
features, then use augmented
reality to “apply” the user’s
selected product and shade.
Moreover, it can automatically
apply suggested shades based
on the consumer’s skin tone.

106. Engage - Care
Analyse customer data to identify opportunities for upselling and cross- selling,
by suggesting complementary products or upgrades.
Personalise post-purchase communication and follow-up based on customer
behaviour and feedback, helping to build long-term relationships and loyalty.

107. Salesforce Einstein:
Next Best Action
Deliver proven recommendations to
employees and customers, right in the
apps where they work. Define
recommendations, create action
strategies, build predictive models,
display recommendations, and activate
automation.

110. Curated shopping is
one of the firm’s
most important
projects for the next
12 to 18 months, says
Zalando CEO Rubin
Ritter.
Hyper
Personalized
Relation

111. https://algorithms-tour.stitchfix.com/

112. https://avpwork.com/home/stitch-fix-data-science-keep-rates-retention-nps

115. In the life of…
A Static Vinyl Poster in the
Meeting Room
FROM TO AND
In the voice of…
116
AI gives enables us to
bring audiences to life

116. © Havas 2023
117

117. © Havas 2023
118
Sophie, the Savvy Investor:
•Family: Sophie is married to Mark, a fellow finance enthusiast. They have a curious 8-year-old daughter named Lily who loves asking questions about stocks.
•Hobbies: Sophie enjoys reading financial thrillers during her downtime. She’s also an amateur photographer and captures cityscapes during her travels.
•Studies: Sophie holds a master’s degree in finance from the University of Brussels.
•Place of Residence: Sophie lives in a cozy apartment in the heart of Brussels, overlooking the historic Grand Place.
•Holidays: Sophie and her family explore European cities during holidays. Their favorite destination is Zurich, where they enjoy both the financial district and the serene Lake Zurich.
•Music: Sophie’s playlist includes instrumental jazz—perfect for analyzing stock charts
1.Sophie, the Savvy Investor:
1. Background: Sophie is a 35-year-old financial analyst who loves staying
informed about market trends. She follows financial news, reads
investment blogs, and watches stock market updates.
2. Media Consumption: Sophie spends her mornings reading financial
newspapers and evenings watching CNBC. She appreciates an app that
provides real-time market data, stock news, and expert opinions.
3. Trading Features: Sophie actively trades stocks and ETFs. She wants
advanced charting tools, customizable watchlists, and notifications for
price movements.
4. Preferred Features:
1. Market Insights: Daily market summaries, sector-wise
performance, and earnings reports.
2. Media Integration: In-app access to financial news, podcasts, and
video updates.
3. Advanced Trading: Limit orders, stop-loss, and after-hours
trading.

118. Please Transform – the profile in a text starting with “Hello, I’m Sophie … “
© Havas 2023
119
Hello, I’m Sophie, a 35-year-old financial analyst living in a cozy apartment
overlooking the historic Grand Place in Brussels. My mornings are filled with
reading financial newspapers, and evenings find me watching CNBC for real-
time market updates. When I’m not analyzing stocks, I’m an amateur
photographer capturing cityscapes during our European travels. My
daughter, Lily, keeps me on my toes with her curious questions about
investments. Jazz tunes accompany my stock chart analysis—perfect for
navigating the market’s rhythm

119. https://aicomicfactory.com/fr/playground
120
Eva, the Eco-Conscious
Entrepreneur
Background:
Eva is a 40-year-old entrepreneur who runs a
sustainable fashion brand in Belgium. Her
business focuses on creating stylish, ethically
produced clothing while minimizing
environmental impact. Eva is passionate
about conscious consumerism, eco-friendly
practices, and giving back to the planet.

120. Planning is A.I.
Compatible …
What about
Strategy ?

121. Final Conclusion
Wrap Up

123. hugues.rey@havasmg.com
Hugues.rey@ulb.be
@huguesrey
+ 32 496 26 06 88
www.huguesrey.com
THANK YOU
FOR
YOUR ATTENTION !