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Defining Email channel behavior

Suggest edit Updated on September 7, 2021

Ensure that Pega Email Bot™ responds to emails in an automated and intelligent way by precisely defining how the system behaves. As a result, you make the job of customer service representatives (CSRs) easier and increase the efficiency and responsiveness of your email bot for your application.

For example, CSRs can save time responding to customer email requests when the email bot correctly detects the email subject, entities and language, and as a result provides meaningful replies and suggests relevant business cases to spin-off.
Before you begin: Create an Email channel to use as an email bot. For more information, see Creating an Email channel.
  1. Provide the ability to start a top-level case based on emails that are received from users.
  2. Provide meaningful automatic responses to emails.
  3. Define how Pega Email Bot analyzes emails from users so that the email bot takes advantage of natural language processing (NLP) and adaptive analytics:
    1. Configure text analyzers for the email bot so that the system users natural language processing (NLP) and adaptive analytics text analysis of the email.
      For more information, see Adding a text analyzer for an email bot.
    2. Define topics, the general subject, the intent of email that is detected by the email bot using text analysis.
    3. Optional: To let the email bot analyze text contained in image-based email attachments, configure and use the optical character recognition (OCR) component.
      For more information, see Pega OCR on Pega Marketplace.
    4. Optional: To enable the automatic detection of a language for text analysis, configure a dedicated text analyzer.
    When the email bot correctly detects the subject matter, sentiment, entities and the language of an email, you improve the automatic actions that the system can then perform on emails. The system sets up the iNLP text analyzer by default, which uses natural language processing (NLP) and adaptive analytics text analysis to detect topics and entities in emails.
    Design Patterns: For more information about NLP and machine learning in email bots, see Using email bots for natural language processing and machine learning.
What to do next: Configure intelligent email routing for the email bot. For more information, see Configuring intelligent email routing.
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