Topics are the general subject matter of a chat conversation that the system detects, for example, a request for a car insurance quote or an enquiry about a bank loan. After updating the text analytics model with samples of user input for the insurance topic, the chatbot correctly detects the subject matter and automatically starts the Insurance Quote case when the user requests information about a car insurance quote.

Associate topics with user input by performing the following steps:

1. In the navigation pane of App Studio, click Channels.
2. In the Current channel interfaces section, click the icon that represents your existing Legacy Webchat channel.
3. In the channel, click the Behavior tab.
4. In the preview console in the right panel, enter a request for a car insurance quote.
   For example: Enter: Give me a car quote please.

   

   

   Result: The IVA for Legacy Webchat does not recognize the request for a car insurance quote because no topic is associated with the entered text.
5. Click Define topic below the entered text.
6. In the Topic field, press the Down arrow key, and then select the correct topic.
   For example: Select insurance.
7. Optional: To associate the topic with additional similar user input, perform the following steps:
   1. In the field below the topic name, enter more sample user input for the insurance topic.
      For example: Enter: I need a car quote.
   2. Click Add example and add additional sample user input for the insurance topic.
      For example: Enter: How can I get a car quote?

      

      

   3. To define additional user input, repeat step 7.b.
8. Click Submit.

   

   

   Result: The insurance topic is now associated with the user input that appears above the topic name.
9. Rebuild the model by clicking Build model.
   Result: The chatbot learns how to respond to this user input and the additional two examples that you provided. To further enhance the text analytics model, ensure that the correct topic is associated with the user input samples, and to improve the chatbot responses, add more examples of the same user input and rebuild the model a few more times.

Entities are short phrases detected in the conversation, for example, an email address, car make, or car model. In the example below, create the Carmakeent and Carmodelent entities to associate them with the car make and model in the user input. Map these two entities to the .carMake and .carModel case properties that you define for the Insurance Quote case, respectively.

1. In the preview console, enter a request for an insurance quote.
   Tip: If the correct topic is already associated with your input, you can improve the chatbot's future responses in the model by clicking the Like icon next to the topic name, and then rebuilding the model.

   

   

   Result: Based on the insurance keyword, the chatbot correctly associates the text with the Insurance Quote case type, starts a case, and responds by asking the first question about the make of the car. The #insurance label below your request represents the topic, while the horizontal line indicates the start of case number I-60.
2. Display more information about the conversation and the case by turning on the Show analysis switch

   

   

   Result: The analysis shows that the system classified the sentiment of the text that you entered in the previous step as neutral, and that the insurance topic was guessed with 97 percent confidence. The chatbot did not detect any entities in your input, even though the text included the make of a car (Ford), and the model of a car (Mustang GT).
3. Associate new entities with "Ford" and "Mustang GT" from the text that you entered in step 1 by performing the following steps:
   1. Select and right-click Ford in the displayed text, and then click New entity.
   2. In the Entity name field, enter: Carmakeent
   3. Click Submit.
   4. Select and right-click Mustang GT in the displayed text, and then click New entity.
   5. In the Entity name field, enter: Carmodelent
   6. Click Submit.

   

   

   Result: The system maps the two entity types that you create to the make and model of the car in the text, Ford and Mustang GT, respectively.
4. Map the extraction of the two entity types that you created to case properties, by performing the following steps:
   1. In the Create case section, click the Open response configuration icon.
   2. In the Response configuration dialog for the Insurance Quote case type, click the Entities extraction tab.
   3. Click Add mapping.
   4. In the Entity list, select Carmakeent.
   5. In the Case property list, select carMake.
   6. Click Add mapping.
   7. In the Entity list, select Carmodelent.
   8. In the Case property list, select carModel.
   9. Click Submit.

      

      

5. Build the model and refresh the updated entity information in the chatbot by clicking Build model.

When you provide the car make and model in a request for information about car insurance, the chatbot automatically skips the first two questions for which it recognized the answer and assigns the details to the Insurance Quote case properties.

1. In the preview console, click Reset.
2. Enter the same text as in step 1 of the Configuring and mapping entities to case type properties section to request an insurance quote.

   

   

   Tip: If the correct topic is already associated with your input, you can improve the chatbot's future responses in the model in the future by clicking the Like icon next to the topic name, and then rebuilding the model.
   For example: Enter: I would like to obtain an insurance quote for my Ford Mustang GT.
   Result: The chatbot correctly associates the text with the Insurance Quote case type, and starts a case. However, this time the bot asks only the third question about the VIN number of the car.
3. Display more information about the conversation and the case by turning on the Show analysis switch.

   

   

   Result: The first and the second question about the make and model of the car are greyed out because they were skipped. The reason that they were skipped is that the Carmakent and Carmodelent entities were successfully extracted from your input, and automatically mapped to the .carMake and .CarModel case properties, respectively.