Table of Contents

Configuring email analysis

Improve automatic actions that the system performs on emails, by configuring Pega Email Bot that analyzes email content for topics, sentiment, language, and entities. You can also configure additional analysis for the email subject field and file attachments.

Define suggested responses for your email bot. For more information, see Defining suggested responses for an Email channel.

To provide better responses, you can configure more than one text analyzer in your email bot. In that scenario, the text analyzers scan the email content one by one, starting with the first analyzer in the list, until they find a response. You can also configure one text analyzer to analyze only the content in the email body, while configuring another to perform only the text analysis of email attachments.

  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.

    For more information, see Defining topics for text analysis for an email bot.

  3. Optional:

    To enable the automatic detection of a language for text analysis, configure a dedicated text analyzer.

    For more information, see Enabling automatic language detection for text analysis.

  • Exploring text analyzers

    Text analyzers for Pega Intelligent Virtual Assistant (IVA) and Pega Email Bot process user input and help the system find the best matching response by using natural language processing (NLP) and adaptive analytics. You can configure text analyzers to detect topics, entities, sentiment, and language in an email, chat text message, or a voice command.

  • Understanding text analysis

    Text analysis is an important aspect of conversational channels that enables a Pega Platform application to intelligently and seamlessly interact with a user in a natural conversational manner. Text analyzers examine user input one by one using natural language processing (NLP), adaptive analytics, and artificial intelligence.

  • Defining Email channel behavior

    Configure how the Email channel automatically responds to email requests, so that you can route email content and create top-level cases in your application. To ensure that the responses are meaningful and contextual, you can define such parameters as suggested cases and responses, and configure email analysis of the subject field and file attachments.

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