Training the model for the Email channel
To use Pega Email Bot in your application to seamlessly respond to user problems,
train the system to recognize different user input in emails, such as help requests or
issues. When you train the text analytics model for the email bot, the system learns
from training records, improves the artificial intelligence algorithms, and provides
better responses to user input.
For example, when you train the model for
the email bot and apply changes to the model, a user might send an email requesting
information about car insurance. The system then performs the analysis of the email content
and detects the correct topic, entities, sentiment, and language. Based on this information
and intelligent email routing, the email bot then runs automated tasks, such as starting a
business case for a car insurance quote, and sends an automatic reply.
Before you begin: Build an email bot by configuring the Email channel. For more information, see Building an Email channel.
To ensure that the email bot learns from the training records and detects the correct information, such as topics and entities, apply the training changes to the text analytics model for the system. You apply changes to the model after you enable the training data recording, and then create and review the training records.