Creating unique digital experiences

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Bala Iyer is Dean of Faculty and professor of
technology, operations, and information
management at Babson College.
Bruce Posner is a senior editor at MIT Sloan
Management Review.

4. Digital Experiences using Conversational
Interface
Prof. Bala Iyer
3/28/18
@BalaIyer
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5. Digital experience
• Effect of using technology to create, manage, deliver and
optimize stakeholder experience anytime, anywhere. It
helps build a trusted relationship between a customer and a
brand by being consistent across every touchpoint.
• This requires paying attention to all the phases of a product
life cycle and learning with each interaction.
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Core
Stakeholder Engagement
Innovative Business Models
Dynamic Ecosystems
Automation & Learning

6. Mega trends
• Smart connected products everywhere
• Atomizing services and offering it in different
contexts
• Collecting data and offering it in different business
models
• Building a moat using customer data, digital
experience and product-in-use data
• Ambient user interface
• Strategy  Owning the digital experience
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7. Arrival of Digital Titans
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8. Who are the Digital Titans?
• Multi-billion dollar companies
operating as platform-based business
models
• Have mastered the art and science of
creating digital experiences
• Mastered the data asset and taken it
into different domains
• Multi-purpose platforms with wide
applicability

9. Digital Customer
• A digital customer is one who consumes smart
products, or products that have in-built sensors,
information processing and connectivity
capabilities. In doing so, the digital customer
generates information upon product use, and
enables third party access to that information [HBR,
2014].
• When effectively served, these digital customers
add to novel informational assets with regard to
how products are consumed or used.
• Data can be used to make better products
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10. Digital Replica
• Digital representation of physical assets owned by a
company along with its current state. The current
state and environmental information is provided by
sensors that are embedded on the physical assets.
• Digital replicas allow companies to provide real-
time monitoring, predictive maintenance and other
outcome based services.
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11. What constitutes the digital
replica?
• Digital model of the product
• Enterprise Events data
• Customer data
• Product-in-use
• Contextual data
• Location
• Time
• physiological
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12. Users are interacting with brands
• “I don’t know anyone who likes calling a business.
And no one wants to have to install a new app for
every business or service that they interact with.
We think you should be able to message a business,
in the same way you would message a friend.” —
Mark Zuckerberg at F8 in 2016.
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Chatbot Interface
AI and NLP
Trusted
data
sources

14. What is a chatbot?
• Chatbots are software and computer programs that
mimic human conversation using artificial
intelligence to perform tasks for humans.
• They help answer questions from know data
sources
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15. New Stack
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Command Driven (DOS, Unix)
Apps Layer (AppStore, GooglePlay)
Web Browser (IE, Netscape, Mozilla)
Graphical User Interface (Windows, Xwindows)
Conversational Layer (bots, machine learning & messaging)
Understand machines
Understand humans

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Channels
Chatbot Interface
General
Knowledge
Domain
Knowledge
Third-party
services
AI
Engines
Natural
Language
Processing
Apps
Third-party Data
API
Customer
Data
Contextual
Data

17. Lessons
• Stack has many layers
• Firms can dominate within a layer
• Layers closer to the customer are more highly
valued
• Firms in higher layers can act to commoditize lower
layers
• Getting closer to the customer means bringing
more “humanity” to the exchange
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19. What is conversational
commerce?
• Conversational interfaces allow people to
command devices and programs using natural
language.
• Conversational commerce involves users interacting
with businesses through media and chat apps like
Facebook Messenger, WeChat and Talk. It is a term
coined by Chris Messina.
• Uses AI to make interactions meaningful and
productive.
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21. Types of bots
• Customer Service
• Personal assistants (find restaurants, find flights,
relationships, meetings)
• News
• Help desk
• Order processing
• Product selection
• Personal branding
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22. Bot preferences from Humanity in
the Machine study
• 63% would consider an online channel to connect
to a brand
• 48% agree that it is creepy if the chatbot is
pretending to be human
• 61% agree that it would be frustrating if a chatbot
couldn’t solve their problem
• 75% agree that they would like to know if they are
interacting with a chatbot or human
• 79% would like to know that a human could step in
if they asked to speak to someone
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23. Concerns
• Bots could only fulfill 30% of requests without a
human stepping in
• Of those who have used chatbots on a variety of
platforms, 55% say accuracy in understanding the
request is the biggest challenge.
• Some 28% said they want chatbots to hold a more
human-like natural conversation.
• Users expect personalized, human-like assistance from
bots
• Works well for structured, simple situations like
Tacobot and Domino DOM.
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24. What to look for?
• Clear purpose and narrow domain
• Ease of development
• What are the sources for data?
• Cross messaging platform deployment
• Humans for exception handling
• Platform measures (monitor)
• Users
• Developers
• Data
• Community
• Integrate with existing information systems and data
• Humanize interface
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25. Ecosystem of Bot Companies
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Nodes: 429
Edges: 482

26. It begins with the smartphone
• As more and more people adopt smartphones and tablets as their primary gateway to the online world,
these lightweight, data-friendly chat apps have become portals to news, services and of course, commerce.
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2.87 billion smartphones in 2020

27. Adoption
• 2.5 billion people have signed up for at least one
mobile messaging app and, according to a study by
the advisory firm Activate, that number could reach
3.6 billion by 2018. That’s 90 percent of the
internet-connected
• Apps like Facebook Messenger, WeChat, Tango and
Kik
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28. Generation next
• ...this rising generation of consumers value
experiences that are quick, easy and suit an on-the-
go lifestyle. By building commerce opportunities
into the platform where people are already holding
conversations, you eliminate a significant barrier
between the consumer and the brand.
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30. Facebook and Uber
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31. Alexa, order me a pizza!
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32. Growthbot
• Helps users access
tons of marketing and
sales data using an
app they probably
already have open all
day — Slack
• Data sources:
Hubspot, Google
Analytics, MailChimp
and social networking
sites
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36. Core idea
• Good data + Algorithms (AI)  Sense making 
Decisions
• Machine learning, expert systems, user experience
• Data sources: IoT, transaction data, public data,
third-party data
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37. Underlying engines
• Artificial Narrow Intelligence
• Artificial General Intelligence
• Artificial Super Intelligence
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39. What should companies do?
• Choose a business process to automate
• Chose a development platform
• Choose a metaphor for the digital experience
• Build the Chatbot
• Pilot bots with your customers
• Keep the domain knowledge
• Understand the learning algorithms
• Run strategic experiments
• Look for innovative users in other settings
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40. Risks
• Unintended consequences
• Regulations
• Security and privacy
• Loss of ethics, policy and humanity
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41. Era of Data
Power of personalization and digital experience
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44. Liberating Value
Internal
Services
Decision
A
P
I
Known Partner
Services
Decision
Data
StructuredData
THIRD PARTY DATA
ENTERPRISE EVENT DATA
• D&B
• Thomson Reuters
• Nielsen
• SAP & ERP
• Salesforce &
Eloqua
• Engineering
• Mfg./ * Production
• Distribution
• Legacy / Others
CONSUMER GENERATED
DATA
• Weblogs
• Omniture
• Product-in-use
• Social Media
Contextual
OPEN DATA
EXPERIMENTS
Open
Services
Decision

45. Major considerations
• Data Privacy
• Ethics of data use
• Security
• Bias in algorithms
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46. Are Chatbots here to stay?
• Yes
• No
• Maybe
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47. Takeaway
• Should be called niche bots
• Set scope expectations
• Scan logs for market insights
• Own the digital experience
• Collect the contextual data
• Collect the in-use data
• Look for data-driven business opportunities
• Apply platform thinking
• Be part of an ecosystem
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