Presentation at AMSWMC, Kent, July 12th 2023

1. Leveraging the Metaverse for
Marketing Strategy Insight
Ana Isabel Canhoto1; Jan Kietzmann2; Brendan Keegan3
1. University of Sussex Business School, UK
2. University of Victoria, Canada
3. Maynooth University, Republic of Ireland
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2. Waning public interest in the MV
2

3. Potential vs Actual experience
3
Fortnite MV - Marshmallo’s live concert =>
<= Oasis MV (Ready Player One)

4. And… Product customisation (Nike)
4
https://www.facebook.com/ladinabattle/videos/315192
1765121685/

5. In summary:
• MV as cost-effective environment for experimentation and
innovation, offering ability to observe actual consumer
response to new product concepts or ideas
• RQ: How can we assess the value of MV as source of customer
insight, to develop marketing strategy?
5

6. MV, the MV, MVs…???
6
• The term “MV” refers to a shared, persistent and decentralized
virtual environment, where users, represented by avatars,
engage in social activities (Hwang and Chien, 2022).
• Users can be individual persons, organisations such as universities or
business, and even nations (e.g., such as South Korea)

7. MV, the MV, MVs…???
7
Type of MV Closed Open
Example
Meta’s Horizon Worlds,
Roblox
Decentraland, The Sandbox,
Somnium, Cryptovoxels
Governance
Centralised; by platform
owner
Decentralised; maintained by
communities or decentralized
autonomous organisation
Control of digital
assets
Assets are held by platform
owner
Assets are owned by users and
may be sold to others
Capabilities (e.g.,
integration w/ VR
headsets)
Advanced and quickly
developing, due to large
capital investments made by
platform owner
Limited and slow to develop,
due to lack of capital
investment

8. MV, the MV, MVs…???
8
Type of MV Closed Open
Business
model – users
Platform provider harvests and
monetizes users’ data in exchange
for free or low-cost services
Users have more control and
autonomy over identity,
behavioural data and digital
assets
Business
model –
developers
Platform provider controls type of
apps offered in ecosystem, and
retains large percentage of app
revenues (e.g., Meta keeps 47.5%
of developer revenues for Horizon
Worlds; Steam and Google Play
keep 30%; Roblox keeps nearly
75%)
Users have more autonomy
over apps developed, and
retain higher share of
revenues

9. MV, the MV, MVs…???
9
• The term “MV” refers to a shared, persistent and decentralized
virtual environment, where users, represented by avatars,
engage in social activities (Hwang and Chien, 2022).
• Users can be individual persons, organisations such as universities or
business, and even nations (e.g., South Korea)
• Use of terms:
• MV – To refer to the overall socio-technical phenomenon (like “Social
media”)
• MV realms – To refer to specific MV manifestations (like “social
network”, “microblogging”, …)

10. The approach
• Activity in a platform is conditioned by the characteristics of the
medium (Yoo et al, 2010)
• Digital medium (e.g., open vs closed MV realm)
• Digital content (e.g., virtual shoe)
• Technology and its use are not independent of each other (Giddens,
1986)
• Users of the MV realm (e.g., Child designing the shoe)
• Users of the data generated in the MV realm (e.g., Nike)
10

11. The medium (Briel et al., 2018)
11
• Specificity: Technology’s features constrain what users
can do
• Relationality: Extent to which technology is connected
and responsive
Digital Medium
Specificity
Relationality

12. The medium (Briel et al., 2018)
12
• Specificity: Technology’s features constrain what users
can do
• Proposition 1: MV realms high in sophistication (e.g., VR,
haptics…) and low in realism (e.g., fly, turn into animal, be in
two places at once…) => wide range of activities take place =>
expands the dataset => better for insight
• Relationality: Extent to which technology is connected
and responsive
Digital Medium
Specificity
Relationality

13. The medium (Briel et al., 2018)
13
• Specificity: Technology’s features constrain what users
can do
• Proposition 1: MV realms high in sophistication (e.g., VR,
haptics…) and low in realism (e.g., fly, turn into animal, be in
two places at once…) => wide range of activities take place =>
expands the dataset => better for insight
• Relationality: Extent to which technology is connected
and responsive
Digital Medium
Specificity
Relationality

14. The medium (Briel et al., 2018)
14
• Specificity: Technology’s features constrain what users
can do
• Proposition 1: MV realms high in sophistication (e.g., VR,
haptics…) and low in realism (e.g., fly, turn into animal, be in
two places at once…) => wide range of activities take place =>
expands the dataset => better for insight
• Relationality: Extent to which technology is connected
and responsive
• Proposition 2: MV realms that operate at scale, are open and
support interaction with multiple user types => wide range of
connections => expands the dataset => better for insight
Digital Medium
Specificity
Relationality

15. The medium (Briel et al., 2018)
15
• Specificity: Technology’s features constrain what users
can do
• Proposition 1: MV realms high in sophistication (e.g., VR,
haptics…) and low in realism (e.g., fly, turn into animal, be in
two places at once…) => wide range of activities take place =>
expands the dataset => better for insight
• Relationality: Extent to which technology is connected
and responsive
• Proposition 2: MV realms that operate at scale, are open and
support interaction with multiple user types => wide range of
connections => expands the dataset => better for insight
Digital Medium
Specificity
Relationality

16. The content – produced (Tomczyk et al, 2016)
16
• Soundness: Ability to perform a desired action
• Dependability: Capacity to produce data as desired
Digital content
production
Soundness
Dependability

17. The content – produced (Tomczyk et al, 2016)
17
• Soundness: Ability to perform a desired action
• Proposition 3: MV realms that enable customisation of the
avatar and the environment => increased immersion in the
platform => expands the dataset => better for insight
• Dependability: Capacity to produce data as desired
Digital content
production
Soundness
Dependability

18. The content – produced (Tomczyk et al, 2016)
18
• Soundness: Ability to perform a desired action
• Proposition 3: MV realms that enable customisation of the
avatar and the environment => increased immersion in the
platform => expands the dataset => better for insight
• Dependability: Capacity to produce data as desired
Digital content
production
Soundness
Dependability

19. The content – produced (Tomczyk et al, 2016)
19
• Soundness: Ability to perform a desired action
• Proposition 3: MV realms that enable customisation of the
avatar and the environment => increased immersion in the
platform => expands the dataset => better for insight
• Dependability: Capacity to produce data as desired
• Proposition 4: MV realms with ubiquity of access and
interface, and interoperability => increased use of the
platform => expands the dataset => better for insight
Digital content
production
Soundness
Dependability

20. The content – produced (Tomczyk et al, 2016)
20
• Soundness: Ability to perform a desired action
• Proposition 3: MV realms that enable customisation of the
avatar and the environment => increased immersion in the
platform => expands the dataset => better for insight
• Dependability: Capacity to produce data as desired
• Proposition 4: MV realms with ubiquity of access and
interface, and interoperability => increased use of the
platform => expands the dataset => better for insight
Digital content
production
Soundness
Dependability

21. The content – used (Tomczyk et al, 2016)
21
• Completeness: Degree to which the dataset contains
breadth and depth of information about individual users
and their context
• Consistency: Dataset is available in a form and format
such that it can be used in a cost- effective way
Digital Content use
Completeness
Consistency

22. The content – used (Tomczyk et al, 2016)
22
• Completeness: Degree to which the dataset contains
breadth and depth of information about individual users
and their context
• Proposition 5: MV realms with ability to record behavioural
and physiological data about users, in real-time => richer
dataset => better for insight
• Consistency: Dataset is available in a form and format
such that it can be used in a cost- effective way
Digital Content use
Completeness
Consistency

23. The content – used (Tomczyk et al, 2016)
23
• Completeness: Degree to which the dataset contains
breadth and depth of information about individual users
and their context
• Proposition 5: MV realms with ability to record behavioural
and physiological data about users, in real-time => richer
dataset => better for insight
• Consistency: Dataset is available in a form and format
such that it can be used in a cost- effective way
Digital Content use
Completeness
Consistency

24. The content - used (Tomczyk et al, 2016)
24
• Completeness: Degree to which the dataset contains
breadth and depth of information about individual users
and their context
• Proposition 5: MV realms with ability to record behavioural
and physiological data about users, in real-time => richer
dataset => better for insight
• Consistency: Dataset is available in a form and format
such that it can be used in a cost- effective way
• Proposition 6: MV realms with ability to test and experiment
with users, in a cost-effective manner => usable dataset =>
better for insight
Digital Content use
Completeness
Consistency

25. The content – used (Tomczyk et al, 2016)
25
• Completeness: Degree to which the dataset contains
breadth and depth of information about individual users
and their context
• Proposition 5: MV realms with ability to record behavioural
and physiological data about users, in real-time => richer
dataset => better for insight
• Consistency: Dataset is available in a form and format
such that it can be used in a cost- effective way
• Proposition 6: MV realms with ability to test and experiment
with users, in a cost-effective manner => usable dataset =>
better for insight
Digital Content use
Completeness
Consistency

26. The users
26
• Characteristics: Profile of MV realm users
• Motivations: Psycho-social needs driving use of MV
realm
Individual users
Characteristics
Motivations

27. The users
27
• Characteristics: Profile of MV realm users
• Proposition 7: Fit between users and the organisation’s target
customers => relevant dataset => better for insight
• Motivations: Psycho-social needs driving use of MV
realm
Individual users
Characteristics
Motivations

28. The users
28
• Characteristics: Profile of MV realm users
• Proposition 7: Fit between users and the organisation’s target
customers => relevant dataset => better for insight
• Current MV realms mostly attract young users from privileged
socio-economic backgrounds
• Motivations: Psycho-social needs driving use of MV
realm
Individual users
Characteristics
Motivations

29. The users
29
• Characteristics: Profile of MV realm users
• Proposition 7: Fit between users and the organisation’s target
customers => relevant dataset => better for insight
• Current MV realms mostly attract young users from privileged
socio-economic backgrounds
• Motivations: Psycho-social needs driving use of MV
realm
• Proposition 8: Fit between users’ motivations and the brand’s
positioning => relevant dataset => better for insight
Individual users
Characteristics
Motivations

30. The users
30
• Characteristics: Profile of MV realm users
• Proposition 7: Fit between MV realm’s users and the organisation’s
target customers => relevant dataset => better for insight
• Current MV realms mostly attract young users from privileged socio-
economic backgrounds
• Motivations: Psycho-social needs driving use of MV realm
• Proposition 8: Fit between MV realm’s users’ motivations and the
brand’s positioning => relevant dataset => better for insight
• Current MV realms mostly attract users interested in gaming and
socialization, with synchronous participation limited by geographical
proximity
Individual users
Characteristics
Motivations

31. The MV-IQ Framework
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Digital Medium Digital content
production
Digital Content use Value creation
Specificity
Relationality
Soundness
Dependability
Completeness
Consistency
Customer insight
Enable
Digital traces
Enable Enable
Characteristics Motivations
Individual users

32. Caveats
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• Trade-offs in insight potential
• Factors that increase MVs’ insight potential in one dimension may reduce its
potential in other.
• Need for dynamic assessment, due to embryonic stage of MV
development
• Technology development shaped by the interests of big tech, the actions of
regulators (e.g., in relation to crypto currency), and social phenomena (e.g.,
COVID-19)
• User base likely to become more diversified
• Materialisation of insight potential requires firms being able to:
• Identify and collect the data generated in MVs
• Analyse the dataset and produce actionable insight

33. References
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• Briel, F. v., Davidsson, P. & Recker, J. (2018). Digital Technologies as External Enablers of
New Venture Creation in the IT Hardware Sector. Entrepreneurship Theory and Practice,
42(1), 47-69.
• Giddens, A. (1986). The constitution of society: Outline of the theory of structuration (Vol.
349). University of California Press.
• Hwang, Q-J & Chien, S-Y (2022). Definition, roles, and potential research issues of the
metaverse in education: An artificial intelligence perspective. Computers and Education:
Artificial Intelligence, 3, 100082
• Tomczyk, P., Doligalski, T. & Zaborek, P. (2016), Does customer analysis affect firm
performance? Quantitative evidence from the Polish insurance market. Journal of
Business Research, 69(9), 3652-3658.
• Yoo, Y., Henfridsson, O & Lyytinen, K. (2010). The New Organizing Logic of Digital
Innovation: An Agenda for Information Systems Research. Information Systems Research,
21(4), 724-735.

34. Leveraging the Metaverse for
Marketing Strategy Insight
Ana Isabel Canhoto1; Jan Kietzmann2; Brendan Keegan3
1. University of Sussex Business School, UK
2. University of Victoria, Canada
3. Maynooth University, Republic of Ireland
34