Genesys Agent Assist (EE31) for Genesys Engage cloud

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This topic is part of the manual Genesys Engage cloud Use Cases for version Current of Genesys Use Cases.
Read this topic for other versions:
Important
PS material for this use case has not been finalized. The capabilities illustrated in this case are part of the Early Adopter Program (EAP), reference the EAP announcement for details.
Monitor customer and agent conversations to provide the agent with contextually relevant suggestions.
    GenesysEngage-onpremises

Use Case Overview

Story and Business Context

A positive customer experience relies on the ability of the company or provider to answer a customer's request, provide excellent service and deliver on the requested outcome. Contact centers are often the single point of contact for customers and it is critical that these interactions are properly and effectively handled. Agents need to navigate a plethora of systems and resources to find answers and resolve customer inquiries - time that could be better spent on activities that improve customer service or sales outcome.

With Agent Assist, companies can rely on the power of Artificial Intelligence to display a real-time transcription of the voice call and present relevant and timely suggestions to the agent. The agent spends time assisting the customer based on the suggested results, rather than digging for information across the various systems. An agent may provide feedback (in the form of marking the suggestion as Relevant or Irrelevant) on the suggestions returned by Google CCAI to improve the knowledge base for future use.

Use Case Benefits*

Use Case Benefits Explanation
Improved Employee Occupancy Agents are trained in real-time thru a constantly evolving knowledge base
Improved Employee Satisfaction Agents tackle more complex business inquiries with AI assistance
Improved First Contact Resolution Present relevant suggestions in real-time to help the agent resolve the customer's inquiry
Reduced Handle Time By empowering agents to more effectively provide answers, customers will enjoy a quicker, more positive experience
*You can sort all use cases according to their stated benefits here: Sort by benefits

Summary

During a call between a customer and an agent, relevant, real-time suggestions are presented to the agent in their agent desktop, to assist them on the job. Contextually relevant knowledge suggestions, such as answers to frequently asked questions are presented to the agent in real time. The knowledge empowers the agent, provides the right information at the right time, and enables the agent to provide better support to a customer.


Use Case Definition

Business Flow

Proactive Knowledge Surfacing

Business Flow Description

  1. Genesys connects the customer to the live agent
  2. Agent sees the context (e.g. bot intents and slots) of the customer's journey in the agent desktop
  3. Genesys Agent Assist monitors the voice conversation
  4. During the voice conversation, the following happens:
    • Real-time audio of the voice interaction is streamed to Google Agent Assist service
    • Real-time transcription of the voice call is displayed in agent desktop
    • Google Agent Assist service returns real-time knowledge suggestions
    • The suggested content is displayed to the agent automatically in a live stream of suggestions during the conversation
  5. The agent can do the following with the live stream of suggestions:
    • Click to expand the suggested content, or click the URL to open the full knowledge article (BL1)
    • Read the suggested content directly to the customer, or use it to assist with the interaction (BL2)
    • Share the recommended content, via email, SMS, WhatsApp, or other channels*
  6. Agent can rate (upvote/downvote) to improve the AI suggestions model over time. The more that Agent Assist is used and content rated by agents, the better the suggestions will be in the future. (BL3, BL4)

* Sharing content - future.

Business and Distribution Logic

Business Logic

BL1: Review knowledge: Agent will need to perform a high-level assessment to ensure the information returned from Agent Assist is appropriate and relevant to the current conversation.

BL2: Leverage knowledge: Agent will communicate relevant information to the customer, or, they will use the information to perform the required "back-end" actions to resolve the customer issue.

BL3: Rate knowledge: An agent may be presented with multiple pieces of information during the interaction. Agents should rate all of the information using the thumbs up / thumbs down buttons to mark as Relevant or Irrelevant. Any information not rated will be marked as Unspecified.

BL4: Resolve issue or continue conversation: If the customer issue is not adequately resolved, the agent will continue the conversation with the customer to trigger Agent Assist to surface additional information. If Agent Assist is unable to provide appropriate information to resolve the customer issue, Agents should follow their corporate escalation policy to ensure customer expectations are fulfilled.


Distribution Logic

Since the customer is already speaking with an agent in real-time, any subsequent call steering is likely to be manually directed by the agent.


Use Case Requirements

Customer Interface Requirements

The following are the user interface required for this use case:

  • Workspace Web Edition 9 with Agent Assist plugin enabled
  • Google Dialogflow's Knowledge interface (for uploading or pointing to knowledge base)

Agent Desktop Requirements

Workspace Web Edition 9, with Agent Assist plugin enabled

Reporting

Real-time Reporting

Interaction-related reporting is based on standard Pulse templates.

Historical Reporting

Engage Cloud customers can use Genesys CX Insights to view call reporting.

Assumptions

General Assumptions

Customers and/or Genesys Professional Services are responsible for managing and uploading their own knowledge base content into Google Cloud to be used by Agent Assist, using Google Dialogflow's Knowledge interface

Customer Assumptions

Interdependencies

All required, alternate, and optional use cases are listed here, as well as any exceptions.

All of the following required: At least one of the following required: Optional Exceptions

    Inbound

      Workforce Engagement

        None

          Self-Service and Automation

            None

            Premise Assumptions

            • This use case is not currently available for Premise.


            Cloud Assumptions

            • Must be an Engage Cloud customer with English (US-En) speaking agents deployed in North American region
            • Must be using Engage Cloud IVR, Designer 9 and WWE 9


            Related Documentation

            Document Version

            • v 1.0.1