Customer Experiences with Contact Center AI - Dialogflow CX (CCAIDCX)

Программа курса

The course includes presentations, demonstrations, and hands-on labs.

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.
  • 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.

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 CX

  • List the basic elements of the Dialogflow CX User Interface.
  • Create entities.
  • Create intents and form fill entities in training phrases.
  • Train the NLU model through the Dialogflow console.
  • Build a basic virtual agent to handle identified user journeys.

Module 7: Scaling with Standalone Flows

  • Recognize the scenarios in which standalone flows can help scale your virtual agent.
  • Implement a flow that uses other flows.

Module 8: Using Route Groups for Reusable Routes

  • Define the concept of route groups with respect to Dialogflow CX.
  • Create a route group.
  • Recognize the scenarios in which route groups should be used.
  • Identify the possible scope of a route group.
  • Implement a flow that uses a route group.

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.