What Is A Chatbot?
A chatbot is an intelligent software that can interact with a human and get things done for them. It has an interface that understands human language and responds accordingly with the relevant information.
Chatbots can be built on an already existing platform as well, such as Skype, Facebook Messenger, and Slack. On the other hand, the chatbots can easily be displayed on the web pages as well as mobile applications. Chatbots can replace a man-powered customer service and play a major role in the customer support system.
What Is A Chatbot Mainly Made Of?
It is the heart, the most essential part of its implementation. The component can be implemented and deployed in a manner similar to a backend server component of a web or a mobile application. The middleware acts as the central controller and carries out a few tasks. The tasks are as follows.
- It receives messages from messaging and voice channels
- Checks the context of the message it receives in the dialog box
- Interaction with the NLP (Natural Learning Process) engine to extract the user’s messages’ intents and entities
- Receive user-related information and data by integrating with the Backend System of Record
- Store conversations to analytical storage for analysis in the future
A channel connector, as the name suggests, connects the backend with the user interface. To simply put, messaging platforms like Slack, Skype for Business, Facebook Messenger are a form of channel connectors in this case.
NLP (Natural Language Processor) Engine:
The NLP Engine plays a crucial part in helping Healthcare chatbots understand the user’s intent. The engine has a decision tree that helps the bot understand what action to perform in the conversation. It takes in the main words from the user’s message and provides information on its basis.
This is where all the information is stored and when a user asks or inquires a particular query, the chatbot checks its context store to see where the user is and continue the conversation from that point onward. This specific functionality in a chatbot helps it to carry out conversations with a gap of hours and also ask questions to the users.
SOR – Enterprise Backend:
This backend may not be required technically, but it improves the user’s experience. For instance, a sales assistance bot understands the accountants queries much better and gives precise results rather than a bot that follows the English. Hence, it lets users have a better experience of that particular field.
Some Optional Components That Are Used In The Making As Required:
Although the following components are optional, they help provide the user with an enhanced experience, and the bots work better.
These services include image recognition, sentiment and tone analysis, and language translation.
To see the performance of the scale, it is best to include the insights while building it so that the necessary changes or improvements can be made. There are various applications that can be added to the bots through conversational logging. Some of them are:
- Analyzing bot performance and user adoption
- Check the critical errors that the bots make as well as their abandonment rate
- Train the bot to respond better to users’ queries by understanding new areas
Bots, although designed to respond to user’s queries, cannot answer all the questions that it receives. They can easily answer the most frequent questions by might not be able to perform as well when it comes to requests that might need a human touch; they stop. Hence, adding an agent escalation will help the bots redirect the message to an agent so that the users can continue the conversation.
Identity And Authentication:
For an increased security level, healthcare industries and the banking sectors might need this particular functionality in their bots to authenticate and validate users’ identities.