Jason Brenier's Presentation "Principles of Conversational Business" - Activate 2017 by mPulse Mobile

Principles of
Conversational
Business

georgianpartners.com
Conversational Business
Jason M. Brenier
• Director of Strategy @Georgian Partners
• Ph.D. Linguistics
• Research @Stanford
– Spoken dialogue systems, natural language processing, text-to-speech
synthesis, discourse processing, deception detection, acoustic
phonetics
• Previous affiliations:
– CTO @Idibon; Adaptive AI, human-in-the-loop NLP
– Forensic Technology @Ernst & Young; fraud, risk & compliance,
forensic investigations, active machine learning and NLP for e-
discovery, electronic communications surveillance, insider threat
detection, AML
– Speech Design @Nuance; expressive text-to-speech, data-driven
voices
– Linguistics @Cataphora; email/IM behavior analytics, emotive tone,
sentiment, linguistic style

• More than 100 years’ collective experience
applying analytics, machine learning, and
artificial intelligence to industry-specific
business problems
• Work directly with portfolio companies
through workshops, applied research,
product development, engineering
• Facilitate resource acquisition and sharing
– Georgian Data Union
• Practitioners of AI for our own business –
Spring sourcing engine
Georgian Impact
Madalin Mihailescu
VP, Impact Team
Hershel Harris
Engineering
Justin LaFayette
Managing Partner
Jason Brenier
Yevgeniy Vahlis
Security First
Ji Chao Zhang
Software Development
Parinaz Sobhani
Machine Learning

Conversationa
l Business
Applications that enable long-
running, real-time, bi-directional
transmissions of text or voice
messages.
• Just the right amount of UX for the task
• Conversational
• Immediate and long-running transactions
• Seamlessly weaves robust services together
• Natural language vs. menu-driven interfaces
• Multiple signals (text, emoji, images)
• Dynamic views and flows
• Known participants

Business
Correspondence
Content
Publishing
Social
Communication
Print
Web
Email
Social Media
Messaging
As remote communication evolves, conversation becomes
ubiquitous.
Written correspondence
Telephone
Fax
Email
Messaging
Written correspondence
Telephone
Email
Messaging
Social Media

Messaging defines a new customer interaction paradigm.
• Mobile app usage is declining by 20% YoY
• Most users spend 50% of their time in only one app
— usually messaging.
• 75% of smartphone users use at least one
messaging app.
• Number of messaging users have surpassed social
network users.
• 5 of the all-time top 10 apps are messaging apps.
• 55% of messaging push notifications are read.
• 63% of Facebook users have increased messaging
with businesses over the last year
Source: https://insights.fb.com/2016/12/01/messaging-means-business/

The journey from apps to chat requires a new approach.
WEB TO APPS
Humans learn apps
From “and mobile” to “mobile first”
Platform = OS & app store
Discoverability
Visual navigation / menu-driven UX
Move to cloud
Similar design process
Designing around the device
APPS TO CHAT
Apps learn to be human
From “and bots” to Conversational Business
Platform = messaging, voice, bot stores
Discoverability
Language-based UX
Start in the cloud
New design process
Designing around the language and dialogue

Chat is becoming ambient.
MESSAGING VOICE ASSISTANTS CONVERSATIONAL DEVICES

Chatbots: unique customer interactions at scale.
• No two conversations are the same
• Scale engagement across a large user population
• Live in messaging platforms, on SMS
or in conversational devices
• Automate complex tasks
• Act as direct participants or assistants
• Use rules, machine learning or AI
11k
bots in 3 months
23k
bot developers
900M
active users

Trends: Users desire effortless, natural, engaging interactions.
Cultivate rapport
Users desire engaging, personalized, private interactions
with friends, colleagues, businesses and brands
Humanize the interface
Trend toward intuitive, physiologically grounded UX
and conversational intelligence
Summon function when it is needed
Desire to access rich insights and services through
a simple interface with minimal effort

What are the challenges?
• User expectations are high
• Conversational intelligence is low
• New interfaces must be better than apps
• Discoverability, management, and
switching
• Finding users and keeping them engaged
• Graceful failure, iterative improvement
• Security, privacy & trust

Principles of

Maturity Levels
Capability and Ingredients
– Intrinsic company assets or strategic intent that give an advantage
– Basic understanding of priorities and opportunities, few specialist skills in
org
Readiness & Process Advantage
– Formalized company standards, practices, skills that give an advantage
– Partially documented approach and priorities
Execution Advantage
– Exploiting advantages with mature processes that capture outcomes
– Applying data and insights to drive continuous improvement
– Complete documentation of approach and skills to execute
Level
1
Level
2
Level
3

Principles of Conversational Business
4. Content enables conversations.
5. Capture user context.
6. Design for conversation.
7. Personify your business.
8. Bot or not?
1. Identify where you’ll have the greatest conversational impact.
2. Understand your audience.
3. Build complete experiences.
9. Keep private conversations private.
Purpose
Data
Design
Integrity

Identify where you’ll have the greatest
conversational impact.
Customer expectations are changing. Anticipate opportunities to meet their
unstated needs.
1
Purpose
Level 1 Level 2 Level 3
Opportunities identified in an ad-
hoc manner.
Business processes partially
documented and prioritized.
All business processes prioritized,
roadmap developed.

Identify where you’ll have the greatest
conversational impact.
1
Purpose
1. Identify all possible business processes,
both informational and transactional.
2. Prioritize processes that help you meet
your strategic business needs.
3. Develop a roadmap for conversational
business that will drive high customer
satisfaction and company value.
- High friction
- Routine, boring workflows
- Multi-turn
- Already conversational
- Better experience than mobile

Understand your audience.
Your users are already having conversations through messaging and voice
interfaces. Understand your users’ preferred platforms, channels and
devices and engage with them there.
2
Purpose
Basic understanding of the
platforms the audience is using.
Research and testing used to
develop a complete understanding
of audience preferences.
Interaction data used to refine
understanding of audience’s
preferences.

Understand your audience.2
Purpose
a. Identify your current and potential audiences.
b. Use internal data, surveys, interviews, and third-
party research to learn about your users.
c. Segment users by demographics, engagement
level, platform, and business value.
d. Join conversations where they are already taking
place.
e. Take advantage of existing social communities.
f. Support text, voice and other engagement channels.
g. Be inclusive of all devices that users expect to use.

Build complete experiences.
Ensure that you have all of the right connections to the systems needed for
an end-to-end conversation.
3
Purpose
Some back-end service
integrations accessible.
All service integrations required
for end-to-end conversations
identified, most are accessible.
Optimized integrations for
complete end-to-end
conversational experiences.
“The bot is just a user interface.”
- Amir Shevat

Build complete experiences.3
Purpose
a. Map out the services needed to deliver the end-to-end business
process.
b. Ensure that you have access to the full range of required API services to
build complete experiences.

Content enables conversations.
Businesses should capture, curate and create content to deliver the
best possible set of conversational interactions.
4
Data
Examples of traditional customer
interactions captured over time.
Process in place to capture and
integrate all relevant customer
interactions.
Content is refined and expanded
based on measurements of
relevance, quality and
completeness.

Content enables conversations.4
Data
a. Capture conversational data
b. Curate and filter
c. Fill in the gaps
d. Keep improving over time

Natural Language Generation
• Retrieval-based methods – select pre-determined responses
• Generative models – create customized responses
• Short vs. long conversations – require dialogue manager
• Open vs. Closed Domain – world knowledge vs. task knowledge
• Diversity of response

Capture user context.
The best conversations are those in which the participants know
something about each other. Remember who your users are, what
they’ve said and what they’ve done to make conversations efficient,
engaging, and meaningful.
5
Data
Basic contextual data for customer
interactions captured from internal
sources.
Broad contextual data from both
internal and third-party sources
captured and integrated.
Contextual data expanded by
learning from every customer
interaction.

Capture user context.5
Data
a. Context improves experience by personalizing
interactions, reducing friction, and streamlining the
conversational flow.
b. Record rich contextual data about each interaction:
a. Demographics
b. Interests and preferences
c. Activities
d. Mood
e. Transactional
c. Monitor context and continuously improve your
understanding of the user to improve the quality and
effectiveness of future interactions.

Design for conversation.
Make it easy for users to complete the task at hand. Consider
participants, purpose, language, communication style, and channel
throughout your design process. Use interaction data to iteratively
improve the experience over time.
6
Design
Limited set of user intents and
responses, support scripted
conversations.
Wide range of user intents and
responses, use some
conversational conventions and
natural language.
Set of intents and responses
continuously expanded, extensive
use of natural language and
conversational conventions.

Design for conversation.6
Design
a. Understand intent.
b. Respond appropriately.
c. Be perceptive.
d. Learn from every conversation.
e. Simplify the interface and reduce cognitive load.
f. Minimize context switching.
g. Provide conversational and navigational grounding.
h. Make functionality discoverable.
i. Don’t be brittle: recover from errors gracefully and graciously.
j. Set realistic expectations with users from the outset.
k. Engage in compatible language.
l. Engage regularly to anticipate needs and eliminate obstacles.

Natural Language Understanding
Technique Question Example
Intent Detection What does your user want to do? “I want to travel from SFO to JFK on Tuesday.”
[Intent=book_flight]
Information Extraction What are the relevant people, places and things that
your user is mentioning?
“I want to travel from SFO to JFK on Tuesday.” [Origin=SFO;
Destination=JFK; Departure_date=Tuesday]
Sentiment Analysis How is your user feeling? “I have a question about my bill, and I’ve been trying to get
through to an agent for the last 45 minutes!!! 😩”
[Sentiment=frustrated]
Dialogue Act Classification What is the nature of your user’s response? Is it a
question, a statement, a confirmation, or something
else?
“Yes, that is the correct destination.”
[Dialogue_act=confirmation]
Discourse Processing / Discourse
Markers
What clues is your user leaving to indicate attitude
toward the discussion? What’s your user doing to
control the flow of the conversation and turn taking?
“...however that’s not what I was led to believe when I signed
up.” [Discourse_marker=contrast]
Language Identification Which language and dialect is your user speaking? Is
your user a native speaker?
“I’d like to order two in the same colour.” [Dialect=non-
US_english]
Linguistic Style Detection Is your user responding with formal or informal
language?
“In spite of the efforts that I made to update the password, it
remained unchanged.” [Formality=formal]
“I tried updating, but it didn’t work.” [Formality=informal]
Topic Classification What’s the general theme of the conversation? “Will you be serving ice cream sundaes?” [Topic=in-flight_meals]

Advances in speech technology make spoken interaction possible.
Speech Recognition (input)
- Reduced error rate to 5.1%
Speech Synthesis (output)
- Mean opinion score improved 50%

Personify your business.
Develop personas that engage users and represent your brand. Built trust
and loyalty as you deliver key business functions via customized, engaging
conversational experiences.
7
Design
Some brand values and
characteristics identified.
Persona designed to display key
traits to support brand strategy.
Brand impact of persona
measured and monitored to drive
improvements.

Develop trust and loyalty with users to
learn more about them and better serve
their needs.
Trustworthy
Reduce friction by engaging with users
in a consistent fashion. Don’t require
users to adapt to changing interfaces.
Consistent
Make the experience memorable
enough to share. Get users to return
and pick up where they left off.
Memorable
Make sure that your bot serves the
user’s desired purpose. Nobody wants a
Spambot.
Relevant
Get users excited about engaging with
your brand. Build rapport and an
ongoing relationship.
Engaging & Friendly
Your bot represents your brand and
company culture. Ensure that it is
recognizable and differentiated.
Recognizable
Design: Persona Design – Core Traits

Personify your business.7
Design
a. Develop the right persona.
b. Stay aligned.
c. Transform the business process into a conversation with a trusted agent.
d. Design personas to be consistent, recognizable, engaging, relevant and
memorable.
e. Develop deep, ongoing relationships with users.
f. Develop tailored personas for individual users and user segments.

Bot or not?
Make sure that the right person or technology is taking part in the
conversation. Utilize ‘humans in the loop’ as necessary to compensate for
current technology limitations and to help generate interaction data where
none exists.
8
Design
Strengths and limitations of
automated and human- in-the-loop
conversations understood.
Design process identifies
opportunities for automating
conversations.
Processes automated and
optimized through seamless
collaboration between humans
and machines.

Bot or not?8
Design
a. Understand the value, limitations and risks of bots and humans.
b. Deliver engaging and scalable conversations with bots.
c. Use human input as an onramp to future automation.
d. Determine the best role for each participant
(e.g. user, trainer, validator).
e. Identify appropriate handoff points in the conversation.
f. Make handoffs seamless.

Keep private conversations private.
Conversational interactions come with higher expectations of privacy from
users. Have a conversational privacy policy, and proactively make security
a part of the conversational design process. Set higher expectations on
conversational privacy than the market norm to create competitive barriers.
Integrity
You provide a blanket privacy
policy that covers the use of
conversational data.
You have a conversational privacy
policy and make security part of
your conversational design
process.
You proactively implement
security controls for all interactions
in support of an explicit and
differentiating privacy policy.
9

Keep private conversations private.
Integrity
a. Interactions with conversational interfaces come with greater
intimacy and trust than web- and app-based interactions.
b. Set expectations with users explicitly about how conversational
data will be used.
c. Explain how users benefit from analysis of their conversational
data to build trust.
d. Develop a conversational privacy policy and update it to reflect
changes in your product and the user experience.
e. Privacy is part of design.
“My daughter got this in the mail!” he said.
“She’s still in high school, and you’re
sending her coupons for baby clothes and
cribs? Are you trying to encourage her to
get pregnant?”
9

Questions?
jbrenier@georgianpartners.com

Jason Brenier's Presentation "Principles of Conversational Business" - Activate 2017 by mPulse Mobile

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