Defining response commands for a conversational channel
To automate business processes and save the time that case workers spend answering simple questions typical for a case type, you can define response commands so that Pega Intelligent Virtual Assistant™ (IVA) reacts to user input correctly. The IVA detects the best response for a topic by using text analysis and automatically invokes a response type.
For example, when a user asks for help during an interaction with the IVA, the system can display a text message asking for more information and a menu of available options.You can also add case commands to the IVA, so that the system automatically starts a case in the application based on user input. All suggested cases and suggested responses that you define are topics.
- In the header of Dev Studio, click the name of the application, and then click Channels and interfaces.
- In the Current channel interfaces section, click the icon that represents your existing Unified Messaging or Web Chatbot channel.
- In the channel, click the Configuration tab.
- In the Content section, select a method for modifying a
response command:
- To add a new response command, click Add response.
- To edit an existing response command, click the Switch to edit mode icon for a response displayed in the list.
- In the Response type list in the Response
configuration window, select and configure a response type:
Choices Actions Authenticate the user in the system - Select Authenticate.
- In the Response text area, enter the text that you want to display.
Cancel the current work in the interaction session - Select Cancel.
- In the Response text area, enter the text that you want to display.
- Optional: To add a command to a menu you display after you cancel current work, click Add response.
- In the Menu item list, select the command that you want to invoke for the menu item.
- In the Label field, enter the menu item name that you want to display in the system.
- To add more commands that you want to display as menu items, repeat steps 5.c through 5.e.
Display a rich text menu by using a data transform in the IVA for Web Chatbot - Select Custom.
- In the Data transform field, select
a data transform rule.The rich text menu in the IVA for Web Chatbot looks similar to a Facebook generic template. The menu consists of a title, subtitle, link to an image, and up to three menu options. You can use the default pyPopulateOutboundData data transform as an example for the IVA.
Link to a specified Facebook account in the IVA for Facebook - Select Link.
- In the Response text area, enter the text that you want to display to the user.
- In the Title field, enter a title for the Facebook account to which you want to link.
- In the Authentication callback URL field, enter the authentication URL for the Facebook account to which you want to link.
Display a menu with a list of available commands - Select Menu.
- In the Response text area, enter the text that you want to display to the user.
- Optional: Add a command to a menu by clicking Add response.
- In the Menu item list, select the command that you want to invoke for the menu item.
- In the Label field, enter the menu item name that you want to display in the system.
- To add more commands to display as a menu item, repeat steps 5.c through 5.e.
Restart work on a case that is currently being processed in the session - Select Restart.
- In the Response text area, enter the text that you want to display to the user.
Display a text message to the user - Select Text.
- In the Response text area, enter the text that you want to display to the user.
- Optional: To save the text from the Response text area in a template, click Add existing.
- In the Response command field, enter or modify a user
command for the response type.Through text analysis, a user command provides the input that determines the best response command type that the system detects.
- If the response command requires authentication, select the Requires authentication check box.
- Click Submit.
- Optional: To add more suggested responses, repeat steps 4 through 9.
- Click Save.
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