Additional preparatory configuration
Configure the settings required to ensure that Messaging AI functions properly.
Pega Customer Service
Implementation Guide
- Ensure that an open ruleset is available in your highest application.
Note: The Digital Messaging interface which holds the Messaging AI configuration is created in this ruleset. - Add any case types that you want Messaging AI to suggest to the Content section on Configuration tab in your Digital Messaging interface.
- Ensure that the implementation application uses the
CSEndUser skin or a skin that inherits from the
CSEndUser skin.
Note: If the implementation application uses a wrong skin, the UI that is associated with the features of Messaging AI might not render properly. - Add the following roles to the appropriate access groups to ensure that agents
and supervisors have access to Messaging AI features
that are relevant to their role:
- To enable CSRs to receive Messaging AI suggestions during the chat conversations, add the MessagingAI:CSR role to the access group of the CSRs.
- To enable supervisors to view the Messaging AI suggestions in chat transcripts as part of the post-chat analysis, add the MessagingAI:Manager role to the access group of the supervisors.
- In the suggested actions settings in App Studio, enable the
intelligent guidance feature, and set the Maximum number of actions
displayed to a value greater than
1.For more information, see Configuring the suggested actions settings.
- In the knowledge management settings in App Studio, enable the
display of Pega Knowledge articles, and set the limit for the
number of suggested articles to a value greater than 1.For more information, see Configuring knowledge management settings.
- Define the entities that are specific to your organization in Pega Platform natural language processing (NLP) to expand the
scope of the NLP engine beyond common system entities such as country codes,
which it recognizes by default.
For example: If you manufacture cars, enter your car models into Pega NLP so that it recognizes and populates the names of the models in case fields during a chat interaction with customers.
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