Harnessing conversational intelligence

Harnessing conversational intelligence

The Train functionality will streamline the current chatbot setup experience and has been introduced to make it easier for the users to set up a chatbot as quickly and effectively as possible. This will allow users to set up answers to probable queries by setting up FAQs, defining Entities, uploading questions, and responses in a Tabular Input format or uploading relevant documents in Document Lookup. Elitbuzz NLP engine has been set up and has the intelligence to search across the four types and match the most relevant response according to the query asked. Also, users have the control to change most of the settings and search preferences according to their requirements.

Customers can click on Train from the left navigation bar and setup responses from the following available input options:

1.FAQ

Adding and uploading FAQs are available to All Plans. The ability to configure Synonyms and Stopwords is available Business Plan onwards. 

To navigate to this functionality click on the Train tab in the left panel and select the FAQ option.

2 Managing FAQs

Click on the Train button and navigate to the FAQ option

There are two ways to add FAQs to your bot 

One FAQ at a time: This is relevant for a scenario where the number of FAQs is limited or there are individual entries to be made from time to time. 

Multiple FAQs in one go: There is an upload FAQ option where a user can upload a file containing all the FAQs. This is relevant when the bot owner has a collection of FAQs available. 

2.1 Adding FAQs One By One

Click on Add FAQ button on the FAQ page.

  1. Category: You can create categories for your FAQs this helps you segment relevant queries together and also helps you apply an FAQ filter in a given path. A simple example can be an organisation that has multiple departments, let’s say finance, marketing, support, and operations. You can segregate all your queries into these categories. While using the support path you can limit the FAQs to the support category.
  2. Language: Engati provides support for multiple languages that can be added from the Languages tab under configuration. In FAQs, you can select from the list of languages activated for your bot. The default option available here is English. 
  3. Question: This is the query that a user asks the bot. You can add multiple questions/variations for a given response. This covers the variation that may occur when different users ask the same questions. 

          For example: To ask how to book a ticket 2 users may use a different query. 

               U1: How can I book tickets on the bot?

               U2: Is there a way to make reservations on the bot?

4. Entities: When a group of values leads to the same answer you can tag entities within the FAQ rather than creating separate FAQs for all the variables. 

Scenario

Query: How can I enrol in the IoT Course?

Now there may be the same procedure for enrolling in a set of subjects. Let’s say 

Database Management, Artificial Intelligence, Machine learning, Data Mining, and IoT. The procedure to enrol for each of them is the same. Instead of creating 5 FAQs, you can create an Entity of type Course with the name of all the courses in it. 

Creating an Entity Named Course. From Train Tab navigate to Entities and click on add entity

Prompt Message: This is Triggered if the query is triggered without a valid entity. 

Response Type: This can be a message as shown in the above use case or you can trigger a path in this response. A message will only provide static information while a path can lead to an interactive process.

Answer: When the response type is a message a user can add an answer for the query/question mentioned above. This will be static information and will not change in the bot flow.