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Cognitive Customer Service
with IBM Watson
September 2017
2
About Perficient
Perficient is the leading digital
transformation consulting firm serving
Global 2000 and enterprise customers
throughout North America.
With unparalleled information technology, management
consulting, and creative capabilities, Perficient and its
Perficient Digital agency deliver vision, execution, and
value with outstanding digital experience, business
optimization, and industry solutions.
3
Perficient Profile• Founded in 1997
• Public, NASDAQ: PRFT
• 2016 revenue $487 million
• Major market locations:
Allentown, Atlanta, Ann Arbor, Boston, Charlotte,
Chicago, Cincinnati, Columbus, Dallas, Denver, Detroit,
Fairfax, Houston, Indianapolis, Lafayette, Milwaukee,
Minneapolis, New York City, Northern California, Oxford (UK),
Southern California, St. Louis, Toronto
• Global delivery centers in China and India
• Nearly 3,000 colleagues
• ~95% repeat business rate
• IBM Watson Talent Partner
• 2017 Beacon Award Winner for an Outstanding
Watson Cognitive Solution
• Vast portfolio of Watson-based accelerators, quick
starts and assessment offerings
4
Blueworx Profile• 100 years in combined experience in voice and
mobile applications
• Legacy of innovation since 1986 in IBM labs
• BVR is rock solid and massively scalable
• 100,000+ ports deployed
• Top telco’s in the world have run on BVR for 10+ years
• Cloud, on-premises or a combination of both
• Obsessed with delivering amazing customer
experiences
• Locations in Tulsa, LA, NY and the UK
5
Speaker Introduction
CHRISTINE LIVINGSTONDirector, IBM Watson
Perficient
DEAN UPTONDirector, Product Management
Blueworx
6
Deliver Cognitive
Customer Service
with IBM Watson
7
• Introduction
• What is Watson?
⎼ Cognitive Computing
⎼ Structured vs. Unstructured Data
⎼ Customer Service Usage Patterns
• Case Studies
• Getting Started with Watson
Agenda
8
Changing Consumer
Expectations
• Highly demanding of seamless and
frictionless experience
• Less loyal to singular brand
• Have omni-channel expectations
• Social media gives individual voices great
power
9
Self-Service Channels are Key to
Winning the Future of Customer Service
10
Customer Experience Gap
To drive
customer loyalty
you must invest in
customer experience.
What is Watson?
13
What is Watson?
A tablet you talk to? A giant server? A robot?
14
Understand
The ability to understand structured and unstructured
data, text-based or sensory in context and meaning, at astonishing speed and
volume.
Reason
The ability to formhypotheses, make considered
arguments and prioritize recommendations to help
humans make better decisions.
Learn
Ingest and accumulate data and insight from every interaction
continuously. Trained, not programmed, by experts to
enhance, scale and accelerate their expertise.
Watson: A Cognitive Platform
15
The volume, variety and
veracity of data –
80% of it
unstructured – is
growing at a rate impossible
to keep up with.
Customers have a wider
range of choices than ever
before and are expecting
innovative, relevant and
personalized
engagement.
Why is Cognitive Important?
Companies must engage customers
on their terms in a consistent,
natural, and intuitive way.
Cognitive is the new
competitive advantage for
enterprises focused on
enhancing the customer
experience.
16
Column Value
Patient Joe Brown
Date of Birth 02/13/1972
Date Admitted 02/05/2014
Structured DataHigh Degree of organization, such as a
relational database
“The patient came in complaining of chest pain,
shortness of breath, and lingering headaches
… smokes 2 packs a day … family history of
heart disease…has been experiencing similar
symptoms for the past 12 hours.”
Unstructured DataInformation that is difficult to organize using
traditional mechanisms
Structured vs. Unstructured Data
17
explorer
India
In May
1898
India
In May
celebrated
anniversary
in Portugal
In May, Gary arrived in India after
he celebrated his anniversary in
Portugal
Portugal
400th
anniversary
celebrated
Gary
In May 1898, Portugal celebrated the
400th anniversary of this explorer’s
arrival in India
This evidence suggests “Gary” is the
answer BUT the system must learn that
keyword matching may be weak relative
to other types of evidence
arrived in
arrival in
Legend
Keyword “Hit”
Reference Text
Answer
Weak evidenceRed Text
Answering complex natural language questions requires more than keyword evidence
Analyzing Unstructured Content
18
27th May
1498
Vasco da
Gama
landed in
arrival
in
explorer
India
Para-
phrases
Geo-
KB
Date
MatchStronger evidence can
be much harder to find
and score …
… and the evidence is still
not 100% certain
Search far and wide
Explore many hypotheses
Find judge evidence
Many inference algorithms
On the 27th of May 1498, Vasco da
Gama landed in Kappad Beach
400th anniversary
Portugal
May 1898
celebrated
In May 1898 Portugal celebrated the
400th anniversary of this explorer’s
arrival in India.
Kappad Beach
Legend
Temporal Reasoning
Reference Text
Answer
Statistical Paraphrasing
GeoSpatial Reasoning
Leverage Multiple Algorithms
The Watson Difference
19
Customer Service and Engagement
Agent Assist
• Provide 360° views
• Deliver consistent and accurate answers
• Efficiently scale expertise to novice agent
• Personalize the customer experience
Virtual Agents
• Provide self-service options
• Guide customers through transactions
• Engage customers through several mediums
Integrated Voice Solutions
• IVR Replacement/Enhancement
• “Active Listening”
Customer Service Interaction Analysis
• Support Multiple Channels (social media,
call center, email exchanges)
• Understand customer tone and sentiment
• Uncover hidden trends and relationships
Agent Assist
21
• Improve self-service options through natural language interfaces,
reducing the number of calls received
• Provide 360° insight into customer, product, tickets, etc.
• Personalize the client experience with deep insights into preferences
and interaction history
• Deliver consistent and accurate answers
• Efficiently scale expertise to novice agents
• Additional insights identified through analysis of all existing knowledge
and problem history
– Which problems / issue areas take long to solve?
– Trends and deviations? Peaks?
– Has the same or a similar problem already occurred?
– Any issues known with this entity / product / …?
– Who do I need to contact (Who solved it before?)
– Related cases / workarounds
Contact Center Agents
Watson Explorer
Applications and Data Sources
Watson Developer Cloud
Empower agents to better respond to requests and improve conversion rates
Watson Agent Assist
22
Active Listening
Watson listens and
transcribes the
conversation between a
customer and an agent
Watson understands the
intent of the customers
questions and surfaces
relevant information to
the agent
Virtual Agents
24
Schedules recurring
payment plan to ensure
that he’s always covered
Consistent, effective
relationship management is
essential in industries where
infrequent interactions have
substantial impact on customer
satisfaction.
Currently customers have limited
self-service options available to
them for servicing their accounts
but choose to navigate through
phone-based systems answered
by local agents or call centers
Watson Offers customers an
elevated, intuitive self service
experience that allows them to
easily achieve what they set out
to do.
The Cognitive Customer Experience
25
From:
To:
SELF-SERVICE LEVEL 1 LIVE AGENTS
LEVEL 2 LIVE
AGENTSSELF-SERVICE LEVEL 1 LIVE AGENTS
LEVEL 2 LIVE
AGENTS
FIRST CALL RESOLUTION
- Self-service solutions unable to resolve calls
- Customers want to be passed to Live Agents quickly
FIRST CONTACT RESOLUTION
- Watson offers better user experience
- Able to resolve calls through integrated actions
From First Call to First Contact Resolution
26
Scripted vs. Cognitive Conversations
• Driven by a pre-defined conversation flow
• Expects key phrases or words
• Functions best on structured data
• Best for short and simple tasks
• Relatively quick to implement
Scripted Conversations
• Driven by conversational intents rather than expected flow
• Trained to understand natural language
• Operates on both structured and unstructured data
• Learns over time
• Capable of a wide range of tasks
• Training time varies by complexity
Cognitive Conversations
27
Virtual Agent Knowledge Base Expansion
Cognitive Contact
Center
29
Blueworx Delivers Watson’s
Capabilities to Your Contact Center
• Blend Watson’s fluid conversation
with traditional directed dialog
• Build a cognitive contact center at a
pace that suits your business
• Continuously improve the quality of
every customer interaction
• Transform calls into a more relevant
and relational experience
• …with the proven reliability of
Blueworx
Blueworx is the only IVR to certify IBM’s
MRCP connector for Watson.
Level 1
New speech engines
Example
Speech to text instead of grammars.
Level 2
FluidConversation
Example
Watson Conversation guides caller to an existing Directed Dialog application.
Level 3
Agent-assist
Example
Cognitive application attempts to provide resolution to a human agent.
Level 4Highly automated
Example
Cognitive application attempts to provide resolution directly to the caller. Agents are freed up for more challenging calls.
Level 5Fully autonomous
Example
Caller uses freeform speech to request information, continuously improved resolution derived from machine learning.
Directed DialogDirected Dialog
Directed Dialog
Directed Dialog
Levels of contact center autonomy
Cognitive
Conversation
Natural
Speech
Cognitive
Information
30
Blueworx Gives Watson its Own Voice
Applications &
Data Sources
Watson
Developer Cloud
Contact Center
Agents
Watson Explorer
31
Level 1 – New Speech Engines
Benefits:
• Better quality speech
• Cloud based; no hardware or software maintenance
• Pay-per-use pricing
32
Level 2 – Fluid Conversation
Benefits:
• Fluid speech interaction
• Omnichannel
• Easy application development
33
Watson + Blueworx
Step-1 Call arrives to SIP gateway. (SIP or TDM initiated calls)Step-2 Call is routed to the IVR.Step-3 Access VXML Application layer transformation to interface with Watson Cognitive. Step-4 (Optional) Access client systems (Web Services, Database, Legacy Systems)
Step-5+ Access Watson Services (i.e. WVA, Conversation, Natural Language Classifier, etc) and more. Establish and manage ongoing dialog with either Watson Virtual Agent, and / or Watson Conversation.
Step-6 Interact with the MRCP server to access Watson Speech-To-Text & Text-To-Speech.Step-7 MRCP server manages session, and transformation between MRCP-v2 Protocol and Watson
speech services <-> Speech-To-Text & Text-To-Speech. Step-8 User interfacing with WVA using Chat Bot Widget.
34
Cognitive Contact Center
• A center that unlocks the customer
experience potential by leveraging
data from external, internal,
structured, unstructured, voice and
visual sources…making them work
together.
• Provides an interaction that delivers
on customer expectations based on
the cognitive ability to understand,
reason and learn from every
interaction.
• Communicates with fluid, natural
language through speech or text.
Case Studies
36
360° Customer Perspective
Unification of structured and unstructured data
in a 360° dashboard
Consolidated data platform enhances search
and eliminates multiple system logins
Automated call notes summary and closure
process
Improved consistency and customer service
transcript analysis
43%reduced AHT
training period
and attrition
customer
satisfaction
Life Insurer
37
A Watson Digital Concierge
Reshaped the user experience
Autonomously handles tier-1 requests
(60% Upon Initial Release)
Supports software activation and
maintenance tasks
300% increase in web traffic
90% 99%lower support
costs
shorter
resolution times
North American Software Company
38
63%reduced AHT
Interactive Agent for Healthcare Providers
Cognitive agent converses with providers to
verify benefits
Seamlessly manages member information
inquiries
Transformed a tedious IVR system
Drastic reduction in live agent requests
Call time reduced from 8 to 3 minutes
live agent
requests
Healthcare Insurer
Getting Started
40
Available Workshops
Rapidly iterate through Watson’s
application in your organization, define
measurable goals for your cognitive
analytics implementation, and begin your
cognitive journey.
Ideate on and discover the
possibilities of cognitive analytics
and industry applications for your
organization. Rapidly prototype and
illustrate the art of the possible.
IBM Watson
Workshop
IBM Watson
Innovation Lab
3-4 WeeksHalf-to-Full Day
41
Workshop Format
OBJECTIVES,
GOALS & KPIS
APPLICATIONS
OF WATSON
EDUCATION
USE CASES
USER EXPERIENCE
& IDEATION
RAPID
PROTOTYPING
Watson Workshop
Watson Innovation Lab
42
Questions?
Appendix
44
Channel proliferation has consumers expecting
instantaneous personalized, high-quality
interactions regardless of the contact channel
the consumer chooses.
Watson Virtual Agent offers customers a
cognitive, conversational self-service engine
that can provide answers and take action
through a variety of channels at scale.
What is Watson Virtual Agent, and what can it do for you and your customers?
Watson Virtual Agent on IBM Marketplace
Watson Virtual Agent
Business Problem:
Solution:
Learn More:
• Personalized, contextual digital assistant that can take action on customer’s request
• Pre-trained natural language understanding conversations for customer service domain
• Customer service-focused dialog flows across a range of complexities
• Conversation tooling and dashboard for managing customer experiences
• Software-as-a-Service solution with continuous delivery of enhancements and new content
Quantitative Benefits
• Absorb deflected contacts from higher cost channels
• Increased first-contact resolution
• Increased revenue through re-tasking human reps
• Decreased agent-to-agent transfers
Qualitative Benefits
• Satisfy customer demand through the channel they choose
• Consistent omni-channel customer experience
• Increases in lifetime value, net promoter score
45
Watson Virtual Agent Knowledge Base
Fre
quency
Question Intent Complexity
20% Of User Volume, much larger
number of singleton (unique) intents. High complexity, answer depends on a number of
variables (knowing the intent is not enough to
answer), requires deep QA search.
Body Long Tail
Pilo
t
Phase 1
Ph
ase
2
Phase 3
80% of User Question Volume
20% of unique intents. Low complexity, easy to answer derived
using context of the question itself