Duration

4 days.

Prerequisites

Completed GCP Fundamentals or have equivalent experience

    Skills Gained

    • Define Google CCAI.
    • Explain how Dialogflow can be used in Contact Center applications.
    • Implement a virtual agent using Dialogflow ES.
    • Read and write data from Firestore using Cloud Functions.
    • Use Dialogflow tools and cloud logging for troubleshooting.
    • Describe how to manage virtual agent environments.
    • Identify general best practices for virtual agents.
    • Identify key aspects such as security and compliance in the context of contact centers.
    • Analyze audio recordings using the Speech Analytics
    • Framework (SAF).
    • Recognize use cases where Agent Assist adds value.

    Who Can Benefit?

    This is a beginner to intermediate course, intended for learners with the following types of roles:

    • Conversational designers: Designs the user experience of a virtual assistant. Translates the brand's business requirements into natural dialog flows.
    • Citizen developers: Creates new business applications for consumption by others using high level development and runtime environments.
    • Software developers: Codes computer software in a programming language (e.g., C++, Python, Javascript) and often using an SDK/API.
    • Operations specialists: Monitors system operations and troubleshoots problems. Installs, supports, and maintains network and system tools.

    Outline for Customer Experiences with Contact Center AI - Dialogflow ES Training

    Course Outline

    Module 1: Overview of Contact Center AI

    • Define what Contact Center AI (CCAI) is and what it can do for contact centers.
    • Identify each component of the CCAI Architecture: Speech Recognition, Dialogflow, Speech Synthesis, Agent Assist, and Insights AI.
    • Describe the role each component plays in a CCAI solution.

    Module 2: Conversational Experiences

    • List the basic principles of a conversational experience.
    • Explain the role of Conversation virtual agents in a conversation experience.
    • Articulate how STT (Speech to Text) can determine the quality of a conversation experience.
    • Demonstrate and test how Speech adaptation can improve the speech recognition accuracy of the agent.
    • Recognize the different NLU (Natural Language Understanding) and NLP (Natural Language Processing) techniques and the role they play on conversation experiences.

    Module 3: Fundamentals of Designing Conversations

    • Identify user roles and their journeys.
    • Write personas for virtual agents and users.
    • Model user-agent interactions.

    Module 4: Dialogflow Product Options

    • Describe two primary differences between Dialogflow Essentials (ES) and Dialogflow Customer Experience (CX).
    • Identify two design principles for your virtual agent which apply regardless of whether you implement in Dialogflow ES or CX.
    • Identify two ways your virtual agent implementation changes based on whether you implement in Dialogflow ES or CX.
    • List the basic elements of the Dialogflow user interface.

    Module 5: Course Review

    • Review what was covered in the course as relates to the objectives.

    Module 6: Fundamentals of building conversations with Dialogflow ES

    • List the basic elements of the Dialogflow CX User Interface.
    • Build a virtual agent to handle identified user journeys.
    • Train the NLU model through the Dialogflow console.
    • Define and test intents for a basic agent.
    • Train the agent to handle expected and unexpected user scenarios.
    • Recognize the different types of entities and when to use them.
    • Create entities.
    • Define and test entities on a basic agent.
    • Implement slot filling using the Dialogflow UI.
    • Describe when Mega Agent might be used.
    • Demonstrate how to add access to a knowledge base for your virtual agent to answer customer questions straight from a company FAQ.

    Module 7: Maintaining Context in a Conversation

    • Create follow-up intents.
    • Recognize the scenarios in which context should be used.
    • Identify the possible statuses of a context (active versus inactive context).
    • Implement dialogs using input and output contexts.

    Module 8: Moving From Chat to Voice Virtual Agent

    • Describe two ways that the media type changes the conversation.
    • Configure the telephony gateway for testing.
    • Test a basic voice agent.
    • Modify the voice of the agent.
    • Show how the different media types can have different responses.
    • Consider the modifications needed when moving to production.
    • Be aware of the telephony integration for voice in a production environment.

    Module 9: Course Review

    • Review what was covered in the course as relates to the objectives.

    Module 10: Testing and Logging

    • Use Dialogflow tools for troubleshooting.
    • Use Google Cloud tools for debugging your virtual agent.
    • Review logs generated by virtual agent activity.
    • Recognize ways an audit can be performed.

    Module 11: Taking Actions with Fulfillment

    • Characterize the role of fulfillment with respect to Contact Center AI.
    • Implement a virtual agent using Dialogflow ES.
    • Use Cloud Firestore to store customer data.
    • Implement fulfillment using Cloud Functions to read and write Firestore data.
    • Describe the use of Apigee for application deployment.

    Module 12: Integrating Virtual Agents

    • Describe how to use the Dialogflow API to programmatically create and modify the virtual agent.
    • Describe connectivity protocols: gRPC, REST, SIP endpoints, and phone numbers over PSTN.
    • Describe how to replace existing head intent detection on IVRs with Dialogflow intents.
    • Describe virtual agent integration with Google Assistant.
    • Describe virtual agent integration with messaging platforms.
    • Describe virtual agent integration with CRM platforms (such as Salesforce and Zendesk).
    • Describe virtual agent integration with enterprise communication platforms (such as Genesys, Avaya, Cisco, and Twilio).
    • Explain the ability that telephony providers have of identifying the caller and how that can modify the agent design.
    • Describe how to incorporate IVR features in the virtual agent.

    Module 13: Course Review

    • Review what was covered in the course as relates to the objectives.

    Module 14: Environment Management

    • Create Draft and Published versions of your virtual agent.
    • Create environments where your virtual agent will be published.
    • Load a saved version of your virtual agent to Draft.
    • Change which version is loaded to an environment.

    Module 15: Drawing Insights from Recordings with SAF

    • Analyze audio recordings using the Speech Analytics Framework (SAF).

    Module 16: Intelligence Assistance for Live Agents

    • Recognize use cases where Agent Assist adds value.
    • Identify, collect and curate documents for knowledge base construction.
    • Describe how to set up knowledge bases.
    • Describe how FAQ Assist works.
    • Describe how Document Assist works.
    • Describe how the Agent Assist UI works.
    • Describe how Dialogflow Assist works.
    • Describe how Smart Reply works.
    • Describe how Real-time entity extraction works.

    Module 17: Compliance and Security

    • Describe two ways security can be implemented on a CCAI integration.
    • Identify current compliance measures and scenarios where compliance is needed.

    Module 18: Best Practices

    • Convert pattern matching and decision trees to smart conversational design.
    • Recognize situations that require escalation to a human agent.
    • Support multiple platforms, devices, languages, and dialects.
    • Use Diagflow’s built-in analytics to assess the health of the virtual agent.
    • Perform agent validation through the Dialogflow UI.
    • Monitor conversations and Agent Assist.
    • Institute a DevOps and version control framework for agent development and maintenance.
    • Consider enabling spell correction to increase the virtual agent's accuracy.

    Module 19: Implementation Methodology

    • Identify the stages of the Google Enterprise Sales Process.
    • Describe the Partner role in the Enterprise Sales Process.
    • Detail the steps in a Contact Center AI project using Google’s ESP.
    • Describe the key activities of the Implementation Phase in ESP.
    • Locate and understand how to use Google's support assets for Partners.

    Module 20: Course Review

    • Review what was covered in the course as relates to the objectives.
    04/09/2024 - 04/12/2024
    09:00 AM - 05:00 PM
    Eastern Standard Time
    Online Virtual Class
    USD $3,600.00
    Enroll