Objectives

• 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

Objectives

• 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.

Objectives

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

Objectives

• 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

Objectives

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

Objectives

• 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.

Objectives

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

Objectives

• 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.

Objectives

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

Objectives

• 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.

Objectives

• 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.

Objectives

• 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.

Objectives

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

Objectives

• 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.

Objectives

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

Objectives

• 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.

Objectives

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

Objectives

• 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

Objectives

• 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

Objectives

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