Secure email threading mechanism in email bots
Valid from Pega Version 8.6
Pega Email Bot™ now uses a secure built-in threading mechanism to ensure that all email communication between customer service representatives (CSRs), customers, and other stakeholders is secure and organized in separate threads for a triage case. For this purpose, the system embeds a unique encrypted security code in the body of outbound emails that identifies related triage cases, service requests, and forwarded emails.
For more information, see Understanding email triage process and Use a secure threading mechanism for emails.
Ability to handle responses to automatic email notifications in email bots
Valid from Pega Version 8.6
Pega Email Bot™ can now handle email responses to automatic email notifications that a Pega Platform™ application sends for a related case. As a result, customer service representatives (CSRs) can save time because all relevant emails from customers and other stakeholders are available from a single triage case in the system. To use this feature, ensure that you add the same email account to the email bot that you use to send case notifications in your application.
For more information, see Handle customer responses to automatic email notifications.
Update to Intelligent Virtual Assistant official names
Valid from Pega Version 8.6
To use better and more consistent names for conversational channels in Pega Platform™ and to help distinguish conversational channels from Pega Unified Messaging Edition™, Pega Intelligent Virtual Assistant™ (IVA) for Unified Messaging is now called IVA for Digital Messaging. Furthermore, the IVA for Web Chatbot is now officially called IVA for Legacy Webchat.
For more information, see Creating a Digital Messaging channel and Pega Intelligent Virtual Assistant features.
Ability to train the text analytics model based on email attachments
Valid from Pega Version 8.6
You can now train the text analytics model for Pega Email Bot™ based on training data from email attachments. As a result, you improve the natural language processing (NLP) analysis for your email bot so that your system detects the correct language, sentiment, topics, and entities from both the body of emails and their attachments. By default, you train the text analytics model based only on training data from the body of emails.
For more information, see Enabling training the model based on email attachments.