UseCases/Current/GenesysCloud/EE31 - Revision history

Shlandy93: UCC: Use Case will now cover native Genesys Agent Assist product

2023-03-14T09:55:45Z

UCC: Use Case will now cover native Genesys Agent Assist product

Shlandy93 at 13:37, June 1, 2022

2022-06-01T13:37:57Z

Shlandy93: UCC: Published Use Case

2022-06-01T13:35:12Z

UCC: Published Use Case

New page

{{SMART UseCase
|ID=EE31
|Title=Genesys Agent Assist with Google Contact Center AI
|Offering=GenesysEngage-onpremises
|SMART_Benefits={{SMART Benefits
|UCBenefitID=Improved Employee Utilization
|UCBenefit=A constantly-evolving knowledge base trains agents in real time.
}}{{SMART Benefits
|UCBenefitID=Improved Employee Satisfaction
|UCBenefit=Agents tackle more complex business inquiries with AI assistance.
}}{{SMART Benefits
|UCBenefitID=Improved First Contact Resolution
|UCBenefit=Present relevant suggestions in real-time to help the agent resolve the caller's inquiry.
}}{{SMART Benefits
|UCBenefitID=Reduced Handle Time
|UCBenefit=By empowering agents to more effectively provide answers, callers enjoy a quicker, more positive experience.
}}
|UCOverview=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 agents properly and effectively handle these interactions. Agents must navigate knowledge and FAQs to find answers and resolve customer inquiries - which takes 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 (AI) to display a real-time transcription of the voice call and to 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. To improve the knowledge base for future use, an agent may verify whether the suggestions that Google Contact Center AI (CCAI) returns are relevant.
|UCSummary=“During a call between a customer and an agent, to assist the agent, Genesys Cloud Agent Assist presents relevant, real-time suggestions to the agent in their desktop. Agent assist provides contextually relevant knowledge suggestions, such as answers to frequently asked questions 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 end-customer.
|PainPoints=* Agents without the right information will give the wrong answer or take precious time finding the correct answer.

* Agents spend an average of 12.5% of their work-week looking for information.

* Agents want to help customers. If they don’t know how, they get frustrated.

* Training material becomes quickly outdated.
|DesiredState=* Agent Assist empowers agents to be CX Heroes by giving them contextually relevant knowledge suggestions in real-time as they talk.

* Commonly asked questions related to the live conversation are automatically served up as needed without agents having to look them up manually.
|BuyerPersonas=Head of Customer Experience, Head of Contact Center(s), Chief Information Officer
|MaturityLevel=Differentiated
|CloudAssumptionsAdditional_Sales=Must be an Engage Cloud customer with English (US-En) speaking agents deployed in North American region.

Must be willing to provide a reference.

Must be using Engage Cloud IVR, Designer 9 and WWE 9.
|PremiseAssumptionsAdditional_Sales=Not available for premise at this time.
|BusinessImageFlow={{SMART BusinessImageFlow
|BusinessFlow='''Proactive Knowledge Surfacing'''
|BusinessImage=https://www.lucidchart.com/documents/edit/b9642209-6872-48ef-9455-6b7a91fcc312/0
|BusinessFlowDescription=#Genesys connects the user to the live agent.
#The agent sees the context (for example bot intents and slots) of the users 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.
#*Agent Assist displays the real-time transcription of the voice call.
#*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 base 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*.
#The 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''.
}}
|BusinessLogic='''BL1: Review knowledge:''' The agent performs a high-level assessment to ensure the information returned from Agent Assist is appropriate and relevant to the current conversation.

'''BL2: Leverage knowledge:''' The agent communicates relevant information to the end-customer, or they use the information to perform the required "back-end" actions to resolve the customer issue.

'''BL3: Rate knowledge:''' Agent assist may provide an agent with multiple pieces of information during the interaction. Agents should rate the information using the thumbs up / thumbs down buttons to verify as r''elevant'' or i''rrelevant''. Any information not rated will be checked as ''Unspecified.''

'''BL4: Resolve issue or continue conversation:''' If the end-customer issue is not adequately resolved, the agent continues the conversation with the end-customer to trigger Agent Assist to surface additional information. If Agent Assist is unable to provide appropriate information to resolve the end-customers issue, Agents should follow their corporate escalation policy to ensure that expectations are fulfilled.
|DistributionLogic=Since the end-customer is already speaking with an agent in real time, any subsequent call steering is likely to be manually directed by the agent.
|CustomerInterfaceRequirements=The following are the user interface requirements for this use case:

*Google dialogflow's knowledge interface (for uploading or pointing to knowledge base).

<br />
|AgentDeskRequirements=There is no applicable content for this section.
|RealTimeReporting=There is no applicable content for this section.
|HistoricalReporting=There is no applicable content for this section.
|DocVersion=v 1.0.0
|GeneralAssumptions=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.
|CustomerAssumptions=Establish and manage a Google Cloud Platform Account.
|RequiresAll=CE01, WE01
|Optional=CE31, CE41
|OperationalRequirements=.
}}

@@ Line 1: / Line 1: @@
 {{SMART UseCase
-|ID=EE31
+|ID=EE32
 |Title=Genesys Agent Assist with Google Contact Center AI
 |Offering=GenesysEngage-onpremises
@@ Line 18: / Line 18: @@
 |UCOverview=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 agents properly and effectively handle these interactions. Agents must navigate knowledge and FAQs to find answers and resolve customer inquiries - which takes 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 (AI) to display a real-time transcription of the voice call and to 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.  To improve the knowledge base for future use, an agent may verify whether the suggestions that Google Contact Center AI (CCAI) returns are relevant.
+With Agent Assist, companies can rely on the power of artificial intelligence (AI) to monitor and analyze the conversation and then deliver contextual, relevant information drawn from a knowledge base to provide relevant suggestions to the agent. The agent spends time assisting the customer based on the suggested results, rather than digging for information.  To improve the knowledge base for future use, an agent may verify whether the suggestions that Genesys Agent Assist AI returns are relevant.
-|UCSummary=“During a call between a customer and an agent, to assist the agent, Genesys Cloud Agent Assist presents relevant, real-time suggestions to the agent in their desktop. Agent assist provides contextually relevant knowledge suggestions, such as answers to frequently asked questions 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 end-customer.
 |PainPoints=* Agents without the right information will give the wrong answer or take precious time finding the correct answer.
@@ Line 40: / Line 42: @@
 |BusinessImageFlow={{SMART BusinessImageFlow
 |BusinessFlow='''Proactive Knowledge Surfacing'''
-|BusinessImage=https://www.lucidchart.com/documents/edit/b9642209-6872-48ef-9455-6b7a91fcc312/0
+|BusinessImage=e9e30f01-7227-4ac3-88d1-ae6346edac58
-|BusinessFlowDescription=#Genesys connects the user to the live agent.
+|BusinessFlowDescription='''1.'''Genesys connects the user to the live agent.
-''* Sharing content - future''.
+'''2'''.The agent sees the context (for example bot intents and slots) of the users journey in the agent desktop.
 }}
 |BusinessLogic='''BL1: Review knowledge:''' The agent performs a high-level assessment to ensure the information returned from Agent Assist is appropriate and relevant to the current conversation.
@@ Line 61: / Line 77: @@
 '''BL2: Leverage knowledge:''' The agent communicates relevant information to the end-customer, or they use the information to perform the required "back-end" actions to resolve the customer issue.
-'''BL3: Rate knowledge:''' Agent assist may provide an agent with multiple pieces of information during the interaction.  Agents should rate the information using the thumbs up / thumbs down buttons to verify as r''elevant'' or i''rrelevant''.  Any information not rated will be checked as ''Unspecified.''
+'''BL3: Rate knowledge:''' Agent assist may provide an agent with multiple pieces of information during the interaction.  Agents should rate the information using the thumbs up / thumbs down buttons to verify as r''elevant'' or i''rrelevant''.
 '''BL4: Resolve issue or continue conversation:''' If the end-customer issue is not adequately resolved, the agent continues the conversation with the end-customer to trigger Agent Assist to surface additional information.  If Agent Assist is unable to provide appropriate information to resolve the end-customers issue, Agents should follow their corporate escalation policy to ensure that expectations are fulfilled.
 |DistributionLogic=Since the end-customer is already speaking with an agent in real time, any subsequent call steering is likely to be manually directed by the agent.
-|CustomerInterfaceRequirements=The following are the user interface requirements for this use case:
+|CustomerInterfaceRequirements=<br />
 |AgentDeskRequirements=There is no applicable content for this section.
-|RealTimeReporting=There is no applicable content for this section.
+|RealTimeReporting=The knowledge dashboard for Genesys Agent Assist gives overview about knowledge base article activities. Genesys Agent Assist metrics and reporting provides insight about presented, opened and copied articles. For more information, see https://rcstaging.wpengine.com/?p=280180
-|HistoricalReporting=There is no applicable content for this section.
+|HistoricalReporting=In the knowledge optimizer dashboard, you can analyze the effectiveness of your knowledge base. In this view, you can see the following metrics:
-<br />
+*All queries in a specific time frame and the breakdown, in percentages, of answered and unanswered queries.
-|RequiresAll=CE01, WE01
+*All answered queries in a specific time frame and the breakdown, in percentages, of the application from which the conversation originated.
-|Optional=CE31, CE41
+*All unanswered queries in a specific time frame and the breakdown, in percentages, of the application from which the conversation originated.
 |OperationalRequirements=.
 }}

@@ Line 75: / Line 75: @@
 |DocVersion=v 1.0.0
 |GeneralAssumptions=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.
-|CustomerAssumptions=Establish and manage a Google Cloud Platform Account.
+|CustomerAssumptions=* Establish and manage a Google Cloud Platform Account.
 |RequiresAll=CE01, WE01
 |Optional=CE31, CE41
 |OperationalRequirements=.
 }}