Defining conversational channel behavior
Improve user experience in Pega Intelligent Virtual Assistant™ (IVA) by configuring the conversational channel behavior that fit the needs of your organization. You can add a conversation to a case type, add suggested cases, and define suggested responses for the IVA so that you speed up business processes for a Pega Platform application.
You can also configure text analyzer settings and system responses to improve the artificial intelligence of the IVA.- Prepare the IVA to collect case information and create a case with the
information:
- Configure the IVA to automatically collect case information through
standard questions to users, by adding a conversation to a case
type.For more information, see Adding a conversation to a case type.
- Configure the system to create a case in a Pega Platform application based on user input, by adding
case commands in the IVA.For more information, see Adding case commands for a conversational channel.
- Configure the IVA to automatically collect case information through
standard questions to users, by adding a conversation to a case
type.
- Configure the system to provide automatic responses to user actions by defining
response commands for the IVA.For more information, see Defining response commands for a conversational channel.
- Define how the IVA analyzes user interactions so that the chatbot takes
advantage of natural language processing (NLP) and adaptive analytics:
- Configure text analyzers for the chatbot so that the system users
natural language processing (NLP) and adaptive analytics text analysis
of chat interactions.For more information, see Adding a text analyzer for an IVA.
- Define topics, which are the general subject and intent of user input
that is detected by the IVA using text analysis.For more information, see Defining topics for text analysis for an IVA.
Design Patterns: To learn about authentication in the IVA for Unified Messaging, see Digital Messaging Channels and Authentication. - Configure text analyzers for the chatbot so that the system users
natural language processing (NLP) and adaptive analytics text analysis
of chat interactions.
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