MG5705 AI in Marketing to share.pptx

MG5705 AI Leadership & Business Models
1
© Ana Isabel Canhoto
AI in Marketing
Image by @halacious via Unsplash

About me
• Dr. Ana Isabel Canhoto
– https://www.brunel.ac.uk/people/ana-canhoto
• Managerial and Academic work in:
• Media and entertainment
• Management consulting
• Telecommunications
• Financial services
• Hospitality
• Role of technology in service delivery
2

This session
1. Applications of AI in Marketing
2. Potential vs. limitations of AI in
marketing
3. Anthropomorphism in
customer facing AI
4. Managing customer
expectations and attribution of
blame
[Break]
5. Class activity: In-store AI system 3
Image source:
https://sloanreview.mit.edu/article/five-ai-
solutions-transforming-b2b-marketing/

But, first…
What is marketing?
4

5
“If you were the marketing manager for a brand of
deodorant, what would your job entail?”

Marketing - definition
6
American Marketing Association: "Marketing is the
activity, set of institutions, and processes for
creating, communicating, delivering, and
exchanging offerings that have value for
customers, clients, partners, and society at large.”
Source: https://www.ama.org/the-definition-of-marketing-what-is-marketing/

Marketing - process
7
Source: https://marketing-insider.eu/marketing-process/

Applications of AI in Marketing
8

9

10

11

12
e.g., sentiment
analysis

- Also known as opinion mining
- Use of natural language processing, text analysis
and other techniques to identify, extract,
quantify, and study affective states
- Used to analyse customer voice materials such
as reviews, survey responses, social media
comments, etc…
- E.g.,
Application: Sentiment Analysis
13

14
- Identify sentiment
- And, most importantly, changes in sentiment
- Understand drivers of sentiment

15
Advantages of AI for sentiment analysis?

Potential of AI in marketing
16
- Connectivity
- Between AI components – e.g., Collect and analyse
data, and post autonomously
- With external elements – e.g., external databases
- Cognitive ability
- Detect patterns in the input data, learn from
mistakes, and self-correct.
- Imperceptibility
- Applications may go unnoticed by users (improves
tech acceptance).
Source: Canhoto and Clear (2020)

17
- But, often, makes mistakes in classification:

18
- But, often, makes mistakes in classification:
Source: Canhoto & Padmanabhan (2015)

19
“The early shift sucks. Oh well at least my latte is
yummy :) “

20
yummy :) “
Multiple
objects

21
yummy :) “
Multiple
objects
Multiple
emotions

22
“100 copies of Ghosts sold overnight means a
definite Starbucks run this morning. Possibly
coffee out twice this week! Maybe even sushi!!”

23
“100 copies of Ghosts sold overnight means a
definite Starbucks run this morning. Possibly
coffee out twice this week! Maybe even sushi!!”
Lack of emotionally charged words

24
“How the heck am I supposed to be able to sleep
well without coffee in my system? fucking snow”

25
“How the heck am I supposed to be able to sleep
well without coffee in my system? fucking snow”
Subtlety - Negative sentiment due to absence of
product

26
“Having coffee with my grandma before work
right now. QT”

27
“Having coffee with my grandma before work
right now. QT”
Syntax and style, specially abbreviations and
slang

28
“This coffee shop needs to change there music
up every once and a while. Or maybe I should go
home”

29
“This coffee shop needs to change there music
up every once and a while. Or maybe I should go
home”
Target of emotion is not coffee!

Limitations of AI in marketing
30

Limitations of AI in marketing
31
It can result in value destruction:

Applications of AI in marketing
32
Context
Skills required

Huang and Rust (2018):
- Mechanical - Perform routine, repeated tasks
- Suitable for: simple, repetitive tasks – e.g., self-service
kiosks
- Analytical - Process information for problem-solving
and learn from it
- Suitable for: complex but rule based tasks – e.g., tax
reporting
- Intuitive – Think creatively and adjust to novel
situations
- Suitable for: complex, idiosyncratic tasks – e.g., news
reporting
- Empathetic – Recognise and understand emotions
- Suitable for: highly interactive tasks – e.g., customer
Types of intelligence
33

34
Empathetic
Intuitive
Analytical
Mechanical
Context
Skills required
Specific Generic

Huang and Rust (2018):
• A job typically consists of numerous tasks, each
requiring a specific type of intelligence
• Best performed by a combination of AI and human
35

36
Role of AI
Role of Human
Dominant Supportive
Dominant
Supportive

37
Empathetic
Intuitive
Analytical
Mechanical
Context
Role of AI
Role of Human
Specific Generic
Dominant Supportive
Dominant
Supportive
Skills required

38
Empathetic
Intuitive
Analytical
Mechanical
Context
Role of AI
Role of Human
Skills required
Specific Generic
Dominant Supportive
Dominant
Supportive
Source: https://anacanhoto.com/2019/10/11/the-potential-of-ai-for-customer-facing-applications/

39
Source: Davenport et al. (2020)

AI acceptance and use
40
Customers resist AI when the task is (Davenport et
al, 2020):
- Perceived as being subjective – When consumers
perceive that intuition, affect and empathy are needed
to perform the task well.

41
al, 2020):
- Perceived as being unique – If the task is perceived as
having unique, unrepeatable features.

42
al, 2020):
- Very consequential for customers – A task that is very
consequential for customers makes risks more salient
to them.

43
al, 2020):
- Related to autonomous goals – Enabling the AI to
decide how best to achieve a goal.

44
al, 2020):
- Salient to the customers’ identity - Customers resist
using AI in tasks that are seen as central to those
identities, because they perceive it as ‘cheating’.

Anthropomorphism in customer facing AI
45
• Appearance – e.g., Gendered
name
• Presentation – e.g., Female vs
male voice
• Behaviour – e.g., telling jokes
Making AI humanlike?
Conflicting evidence:
(Uncanny valley)

Anthropomorphism in customer facing AI
46
Source: Blut et al. (2021)
AI deemed as human-
like if it has a face or a
body, AND it displays
emotions
AI presented as female
Customers are
predisposed towards
the technology, and to
rate it as trustworthy.
Intention to use,
particularly for
information processing
services
e.g., financial services

Managing customer expectations
47
Ms Daniela Castillo
Guest Speaker
Castillo, D., Canhoto, A. I & Said, E., (2020). The Dark Side of AI-powered Service
Interactions: exploring the process of co-destruction from the customer perspective. The
Service Industries Journal DOI: https://doi.org/10.1080/02642069.2020.1787993

Activity
49
Major supermarket chains testing automated age-
verification system, when buying alcohol at self-
checkouts:
- Camera guesses age, using algorithms trained on database
of anonymous faces. If it deems customer is under 25,
they need to show ID to staff.
- Vs. compulsory ID check for all customers.

Activity
50
Major supermarket chains testing automated age-
verification system, when buying alcohol at self-
checkouts:
- Camera guesses age, using algorithms trained on database
of anonymous faces. If it deems customer is under 25,
they need to show ID to staff.
- Vs. compulsory ID check for all customers.
Based on what we discussed:
- How are customers likely to react to this
system?
- What would you recommend in terms of
the system’s functionality and
appearance, to improve customer

51
Key messages from this session

MG5705 AI Leadership & Business Models
52
AI in Marketing
Image by @halacious via Unsplash

MG5705 AI in Marketing to share.pptx

Recommended

Recommended

More Related Content

What's hot

What's hot (20)

Similar to MG5705 AI in Marketing to share.pptx

Similar to MG5705 AI in Marketing to share.pptx (20)

More from Ana Canhoto

More from Ana Canhoto (20)

Recently uploaded

Recently uploaded (20)

MG5705 AI in Marketing to share.pptx