Customer Experiences with Contact Center AI - Dialogflow ES Course Overview

Target Audience for Customer Experiences with Contact Center AI - Dialogflow ES

Koenig Solutions' Customer Experiences with Contact Center AI - Dialogflow ES course is designed for IT professionals aiming to enhance contact center operations with AI.

• Contact Center Managers and Operations Directors
• IT and Support Engineers specializing in contact center technologies
• AI and Machine Learning Specialists focusing on conversational AI
• Customer Experience (CX) Designers and Strategists
• Software Developers and System Integrators implementing Dialogflow solutions
• Product Managers overseeing customer service or contact center products
• Business Analysts looking to optimize customer interaction workflows
• Data Scientists interested in speech analytics and NLP
• Technical Sales Professionals and Consultants offering AI solutions
• DevOps Engineers responsible for deployment and maintenance of AI systems
• Compliance and Security Officers in the telecommunications industry
• Professionals in charge of digital transformation initiatives within customer service departments
• CRM and ERP Specialists integrating AI with existing platforms (e.g., Salesforce, Zendesk)
• Voice User Interface Designers creating voice applications
• Innovation Managers exploring new technologies to improve customer service
• Corporate Trainers and Educators in customer service technology
• R&D Personnel in telecommunications and AI fields

Learning Objectives - What you will Learn in this Customer Experiences with Contact Center AI - Dialogflow ES?

Introduction to Course Learning Outcomes and Concepts:

This course equips participants with the knowledge to create exceptional customer experiences using Contact Center AI, focusing on Dialogflow ES's capabilities and integration.

Learning Objectives and Outcomes:

• Understand the components and capabilities of Contact Center AI (CCAI) and its impact on modern contact centers.
• Identify and describe the roles of CCAI components: Speech Recognition, Dialogflow, Speech Synthesis, Agent Assist, and Insights AI.
• Develop conversational experiences by applying basic principles and integrating NLU/NLP techniques to enhance interaction quality.
• Design and implement Dialogflow ES conversational agents, leveraging intents, entities, and context to maintain a coherent dialogue flow.
• Differentiate between Dialogflow ES and Dialogflow CX, recognizing their design principles and implementation variations.
• Build, train, and refine virtual agents in Dialogflow ES to manage both expected and unexpected user interactions.
• Integrate virtual agents with various platforms, including telephony, CRM, and enterprise communication systems.
• Manage virtual agent environments, ensuring proper version control and environment-specific configurations.
• Utilize Dialogflow tools and Google Cloud resources to troubleshoot, debug, and analyze virtual agent performance.
• Implement best practices for smart conversational design, agent escalation, multi-platform support, and DevOps strategies for continuous improvement.