Get started with Dialogflow & Contact Center AI on Google Cloud

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Sep 14, 2021: “Get started with Dialogflow & Contact
Center AI on Google Cloud” with Lee Boonstra.
Introduce yourself if you “arrive” before we
start at 12:05pm ☺

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Fill the Survey help us serve you better,
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https://forms.gle/oH2ZTnSgMTH41xsg7

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Lee Boonstra | @ladysign
Get started with Dialogflow &
Contact Center AI on Google Cloud
Lee Boonstra
Developer Relations Engineer, Google

Lee Boonstra
Developer Relations Engineer, Conversational AI
@Google
Author of the book: The Definitive Guide to
Conversational AI with Dialogflow & Google Cloud
(Apress)
https://www.leeboonstra.dev
@ladysign

Proprietary + Confidential
Agenda
1
2
3
4
Intro Conversational AI Google
Dialogflow Different Versions
Contact Center AI
My Omnichannel Project
Code Repos
Q&A
5
6

Chatbots exists since the 90’s…
So why are they popular now?

SHIFT FROM A MOBILE FIRST
TO AN AI FIRST STRATEGY

Chatbots.
It's all about Machine Learning.
● Natural Language Understanding
● Intent Matching
● Speech to Text
● Text to Speech (Wavenet)

Main Categories of Conversational AI
IoT
Search Customer
Care
Assistance

Conversational AI as part of Google Cloud
Dialogﬂow ES
Dialogﬂow CX
Speech to Text Text to Speech
Insights
CCAI Agent Assist
Developer APIs
SAAS
Partner GTM
offering

Dialogflow usage
● 2016 - 2020 - people started to
experience with conversational
AI
● Our conversational UI
development suite: Dialogflow,
has a user base of more than
1.7M.
Development Suit for
building Conversational UIs

What we see at Google
In the beginning (2016), most conversational AIs
● Simple chatbots / voice bots - 1 or 2 turn taking turns
● "Example Google Assistant bot;
○ 'hey Google, what's my balance?'
Building conversational AIs is an ongoing process, and thus the
conversational AIs become more complicated over the years.

Chatbots are expected to cut
business costs by more than
$8 billion per year by 2022
Juniper Research

What we see at Google
● The big $$$ savers are typically
complex use-cases
● Replacement or add-ons for Customer
Care / contact centers
○ Which is very expensive for
businesses
○ With conversational AI we can:
■ Reducing Calltime,
■ Reducing hold time
■ Offer 24/7 availability

The next generation of conversational
UI's are more complex.
● Large complex flows / giant implementations
○ hundreds or thousands of intents
● More than 3 turn taking turns (branching of conversations)
● Parts of a dialogue are repeatable
● Understanding the intent & context from long utterances (in
contact centers)
● Working with teams on large implementations
● Maintaining an always growing conversation

Introducing
Development suite for building large &
complex Conversational UIs.
BETA
An additional conversational
product which co-exist next to
the other Dialogﬂow tooling…
● Build complex enterprise
conversations
● Easier to maintain

60%
want easier access to
self-service solutions
prefer personal interactions, not
necessarily with humans
Note: US statistics millennials; Source: Zendesk, Statista, Strategy Analytics, HBR, Ovum, USA market, CISCO VNI
expect to receive
real-time assistance
64% 75%
Customers expect great, flexible, & personal experiences

Often the reality looks like this
● Long waiting / hold times
● Unlimited Call transfers
● IVR difficult to navigate
● Availability
● Inadequate information
● Agents have to answer
same types of questions
over and over again.
https://www.youtube.com/watch?
v=72tF7ggdQyU

Introducing Google Cloud Contact Center AI
Out of the box solution for telephony
contact centers to use AI. No machine
learning expertise required.
It's using popular Google Cloud components...

Use machine intelligence, to make the
experience of calling a service number
better; better for the customer,
and better for the agent

Bots in a telephone contact center are actually
much more complicated...
Turn on the lights
Short utterance. -> Match to 1 intent. Long utterance. Many possible
intent matches.

...and speech quality is critical
● Phone Quality: 8kz mono
● Background noises
● Speaker Diarization (multiple speakers / interrupting each other)
● Requires special IVR features

Conversational
core
Insights
V
i
rt
u
a
l
A
g
e
n
t
A
g
e
n
t
A
s
s
i
s
t
We enable rich
interactions with
virtual agents.
Allows customers to have multi-topic and
multi-channel conversations. Bot
interactions provide more natural
experiences. Multi-lingual support.
We make agents
superheroes in
the eyes of
customers.
Agents can quickly respond to customers with the suggested
responses rather than needing to determine the right
response themselves. Agents are suggested knowledge base
content to solve a customer’s issue so they don’t have to ask a
customer to wait while they search.
We offer the
visibility and
actionable ways to
improve contact
center performance.
Analysts no longer need to manually review and categorize
conversations. Accurate and scaled coverage of call driver
assignment allows easy data segmentation and helps drive
deeper analysis of conversations. Data from Virtual Agents
and Agent Assist feed Insights, providing continuous
evaluation and cyclical feedback.

Proprietary + Confidential
Cloud
STT
Session Manager
State Management
Agent Assist
Articles
Cloud TTS
(Wavenet)
Cloud STT
Full Session Transcripts
Dialogﬂow
Virtual Agent
Agent Assist
NLU + Model
Knowledge
service/KB
Agent Assist
Feedback
Partner Virtual Agent Path Human Agent Path
Agent
Desktop
Telephony
Partner
Customer
Call
General Reference Architecture
(Voice)

What's possible with
Contact Center AI
in combination with Genesys IVR
system
https://www.youtube.com/watch?v=
hWmPLOJPYSc

A preview of
CCAI Insights

Conversational AI Summary
● Developer APIs, such as Speech-to-Text, Text-to-Speech, Natural Language Understanding.
● Conversational AI suites / SAAS:
○ Dialogflow Essentials
○ Dialogflow CX (advanced conversational AIs)
○ Insights AI (suite for detecting the call drivers of a conversation)
● Contact Center AI & Agent Assist
○ GTM offering, where Google delivers the above components + specific Contact Center
APIs so telephony partners can integrate this in their existing architectures.

Future of Customer Care
● Proactive
● Ubiquitous
● Omnichannel
"Make your call center not a cost center but a revenue center."

An example of
a conversational
omnichannel
experience

The technology is already there
RCE 360 Architecture
Twilio
Telephony
Backend Container
Dialogflow
ES
Stackdriver
Cloud
Pubsub
Twilio
SMS
Mobile
App
Google
Assistant
Dialogflow
CX
Nginx Container
Website
Container
Server
Actions on Google
Middleware
Flutter
Middleware
Twilio
Middleware
Website
Middleware
NLU
Cloud
Functions
AdLingo
Dialogflow
ES
External
Load
Balancer

Code Repos
● https://github.com/savelee/kube-django-ng
○ http://www.futurebank.nl
● https://github.com/dialogflow/selfservicekiosk-audio-streaming
○ https://selfservicedesk.appspot.com/

Thank you!
Twitter: ladysign
Amazon: Lee Boonstra
https://www.leeboonstra.dev/chatbots/dialogﬂow-the-book/

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Get started with Dialogflow & Contact Center AI on Google Cloud

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