Customer Experiences with Contact Center AI - Dialogflow ES

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Customer Experiences with Contact Center AI - Dialogflow ES Course Overview

Overview

Enrol for this 4-day Customer Experiences with Contact Center AI - Dialogflow ES training from Koenig Solutions. In this course, you will learn how to design, develop, and deploy customer conversational solutions using Contact Center

Target Audience:

  • 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.

Learning Objectives:

  • Define what Contact Center AI (CCAI) is and what it can do for contact centers.
  • Explain how Dialogflow can be used in contact center applications.
  • Describe how natural language understanding (NLU) is used to enable Dialogflow conversations.
  • Implement a chat virtual agent using Dialogflow ES.
  • Describe how natural language understanding (NLU) is used to enable Dialogflow conversations.
  • Describe options for storing parameters and fulfilling user requests.
  • Describe how to deploy virtual agents to production.
  • Identify best practices for development of virtual agents in Dialogflow ES.
  • Identify key aspects, such as security and compliance, in the context of contact centers

This is a Rare Course and it can be take up to 3 weeks to arrange the training.

You will learn:

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.
  • 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.
  • Identify user roles and their journeys.
  • Write personas for virtual agents and users.
  • Model user-agent interactions.
  • 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.
  • Review what was covered in the course as relates to the objectives.
  • 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.
  • 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.
  • 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.
  • aware of the telephony integration for voice in a production environment.
  • Review what was covered in the course as relates to the 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.
  • 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.
  • 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.
  • Review what was covered in the course as relates to the 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.
  • Analyze audio recordings using the Speech Analytics Framework (SAF).
  • Describe two ways security can be implemented on a CCAI integration.
  • Identify current compliance measures and scenarios where compliance is needed.
  • 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.
  • 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.
  • Review what was covered in the course as relates to the objectives
Live Online Training (Duration : 32 Hours) Fee On Request
Group Training
Online
15 - 18 Aug GTR 09:00 AM - 05:00 PM CST
(8 Hours/Day)
05 - 08 Sep GTR 09:00 AM - 05:00 PM CST
(8 Hours/Day)
03 - 06 Oct GTR 09:00 AM - 05:00 PM CST
(8 Hours/Day)
We Offer :
  • 1-on-1 Public - Select your own start date. Other students can be merged.
  • 1-on-1 Private - Select your own start date. You will be the only student in the class.
4 Hours
8 Hours
Week Days
Weekend

Start Time : At any time

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12 PM

1-On-1 Training is Guaranteed to Run (GTR)
Physical Classroom Training with 4 hours /8 hours option is available. Enquire Now!
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Course Prerequisites

Completed GCP Fundamentals or have equivalent experience.

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