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Defining conversational channel behavior

Updated on July 22, 2021

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.
Before you begin: Create a conversational channel. For more information, see Creating a Unified Messaging channel.
  1. Prepare the IVA to collect case information and create a case with the information:
    1. 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.
    2. Configure the system to create a case in a Pega Platform application based on user input, by adding case commands in the IVA.
  2. Configure the system to provide automatic responses to user actions by defining response commands for the IVA.For example: The system can authenticate, display text messages and a menu of options, or perform other actions as a response to user input.
  3. Define how the IVA analyzes user interactions so that the chatbot takes advantage of natural language processing (NLP) and adaptive analytics:
    1. 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.
    2. Define topics, which are the general subject and intent of user input that is detected by the IVA using text analysis.
    Design Patterns: To learn about authentication in the IVA for Unified Messaging, see Digital Messaging Channels and Authentication.
What to do next: Simulate a conversation and build an IVA. For more information, see Simulating a conversation and building a chatbot.

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