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.