We are happy to advise you!
+43 1 6000 880-0     Contact

Customer Experiences with Contact Center AI (GCP-CCAI)

Detailed 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.
  • Describe the role each component plays in a CCAI solution.
  • Quiz - Contact Center AI fundamentals

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 in conversation experiences.
  • Explain the different elements of a conversation (intents, entities, etc.).
  • Use sentiment analysis to help with the achievement of a higher-quality conversation experience.
  • Improve conversation experiences by choosing different TTS voices (Wavenet vs. Standard).
  • Modify the speed and pitch of a synthesized voice.
  • Describe how to leverage SSML to modify the tone and emphasis of a synthesized passage.
  • Quiz - Conversational Experiences

Module 3 - Fundamentals of Building Conversations with Dialogflow

  • Identify user roles and their journeys.
  • Write personas for virtual agents and users.
  • Model user-agent interactions.
  • List the basic elements of the Dialogflow 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
  • Quiz - DF Fundamentals: Intents and Entities
  • Lab - DF Fundamentals: Build a Basic Virtual Chat Agent That Uses Intents and Entities
  • Lab - Creating a Knowledge Base Connector

Module 4 - 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.
  • Quiz - Context
  • Lab - Context: Add to your virtual chat agent using input and output contexts to map more intricate conversational scenarios

Module 5 - Moving from Chat agent to Voice 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
  • Quiz - Chat versus Voice agent.
  • Lab - Voice Agent: Add voice to your virtual agent.

Module 6 - Taking Actions with Fulfillment

  • Define the role of fulfillment with respect to Contact Center AI.
  • Characterize what needs to be collected in order to fulfill a request.
  • Identify existing backend systems on the customer infrastructure.
  • Use Firestore to store mappings returned from functions.
  • Appreciate that the interaction with customers’ data storage will vary based on their data warehouses.
  • Implement fulfillment using Cloud Functions.
  • Implement fulfillment using Python on AppEngine.
  • Describe the use of Apigee for application deployment.
  • Quiz - Fulfillment
  • Lab - Fulfillment: Using cloud functions to persist and query data from a database.

Module 7 - Testing and Logging

  • Debug a virtual agent by testing intent accuracy.
  • Debug fulfillment by testing the different functions and integrations with backend systems through API calls.
  • Implement version control to achieve more scalable collaboration.
  • Log conversations using Cloud Logging.
  • Recognize ways that audits can be performed.
  • Quiz - Testing and Logging
  • Lab - Logging: Use Cloud Logging to debug your virtual agent code

Module 8 - Intelligent Assistance for Live Agents

  • Recognize use cases where Agent Assist adds value.
  • Identify, collect, and curate documents for knowledge base construction.
  • 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.
  • Quiz - Helping agents enhance the customer experience with knowledge bases, smart replies, and document assistance

Module 9 - Drawing Insights from Recordings

  • Analyze audio recordings using the Speech Analytics Framework (SAF).
  • Lab: Use the Speech Analytics Framework to draw insights from contact center logs

Module 10 - Integrating a Virtual Agent with Third Parties

  • Use the Dialogflow API to programmatically create and modify the virtual agent.
  • Describe connectivity protocols: gRPC, REST, SIP endpoints, and phone numbers over PSTN.
  • 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.
  • Incorporate IVR features in the virtual agent.
  • Quiz - IVR Features
  • Quiz - Common platforms of integration
  • Quiz - Contact Center AI integration points

Module 11 - 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.
  • Quiz - Environment Management
  • Lab - Use the Dialogflow Environment Management feature to deploy a draft version of your virtual agent to a new environment

Module 12 - Methods of Compliance with Federal Regulations

  • Describe two ways that security can be implemented on a Contact Center AI integration.
  • Identify current compliance measures and scenarios where compliance is needed.
  • Quiz - Audit

Module 13 - Best Practices for Virtual Agents

  • 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.
  • Quiz - Best practices

Module 14 - Google Implementation Methodology (Partners only)

  • Identify the stages of the Google Implementation Methodology.
  • Enumerate the key activities of each implementation stage.
  • Acknowledge how to use Google's support assets for Partners.

Module 15 - Course Summary

  • Recapitulate what was covered during this course.