Genesys Agent Assist (EE31) for Genesys Engage cloud
What's the challenge?
Many customers prefer to use self-service options. But when they need to speak to someone, they expect that person to know all about their journey and how best to help them in real time.
What's the solution?
Provide live transcripts of the conversation, and relevant real-time knowledge suggestions on the agent's omnichannel desktop.
- 1 What's the challenge?
- 2 What's the solution?
- 3 Use Case Overview
- 4 Use Case Definition
- 5 User Interface & Reporting
- 6 Customer-facing Considerations
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 checking the suggestion as Relevant or Irrelevant) on the suggestions returned by Google CCAI to improve the knowledge base for future use.
Use Case Benefits*
The following benefits are based on benchmark information captured from Genesys customers and may vary based on industry, lines of business or Genesys product line:
|Use Case Benefits||Explanation|
|Improved Employee Satisfaction||Agents tackle more complex business inquiries with AI assistance.|
|Improved Employee Utilization||Agents are trained in real-time through a constantly evolving knowledge base.|
|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 enjoy a quicker, more positive experience.|
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
Proactive Knowledge Surfacing
Business Flow Description
- Genesys connects the customer to the live agent
- Agent sees the context (for example bot intents and slots) of the customer's journey in the agent desktop
- Genesys Agent Assist monitors the voice conversation
- 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
- The agent can do the following with the live stream of suggestions:
- Click to expand the suggested content, or click the address 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, by email, SMS, WhatsApp, or other channels*
- 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
BL1: Review knowledge: Agent needs 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 communicates relevant information to the customer, or, they 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 the information using the thumbs up / thumbs down buttons to check as Relevant or Irrelevant. Any information not rated will be checked as Unspecified.
BL4: Resolve issue or continue conversation: If the customer issue is not adequately resolved, the agent continues 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 that customer expectations are fulfilled.
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.
User Interface & Reporting
Workspace Web Edition 9, with Agent Assist plugin enabled
Interaction-related reporting is based on standard Pulse templates.
Engage Cloud customers can use Genesys CX Insights to view call reporting.
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|
Self-Service and Automation
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
Must be using Engage Cloud IVR, Designer 9 and WWE 9
Must be an Engage Cloud customer with English (US-En) speaking agents deployed in North American region
- Version v 1.0.1 last updated January 29, 2021