What is sentiment analysis?
Sentiment analysis is a subfield of Machine Learning (ML) and Natural Language Processing (NLP) that deals with extracting thoughts, opinions, or sentiments from the voice or textual data.
It includes real time narrative mapping that allows your chatbot to identify the important words in a sentence and assign them a relative value of positive, neutral, objective, or negative, giving the bot an understanding of the entire tenor of the conversation. In short, sentiment analysis helps in developing the bot’s emotional intelligence.
How does it work?
While ML helps to personalize the chatbot’s performance by harnessing historical customer data, NLP helps to evaluate and interpret the information sent by the customer in real-time.
These two features collectively help chatbots to deliver relevant responses and conduct meaningful conversations.
How does it benefit your business?
- It allows users to configure offensive/negative words & emojis. If the bot finds offensive/negative words or emoji in a visitor’s message, it will show a response as per Sentiment Survey Flow design under Fallback which may include transfer to human agent option configured by the user.
- The bot will detect negative emotion only if the customer message contains bad words/phrases which match exactly with pre-defined/user-configured bad words/phrases/emojis.
How to enable sentiment analysis while building your bot?
- Once you customize your bot profile and move to the ‘Fallback’ option, you have to enable the ‘Sentiment Analysis’ flow.
- When you come to the ‘Sentiment Analysis’ section you can ‘Add the offensive words and emojis’ for your bot to identify user’s sentiment during the conversation.
You can update the list by adding words to make your bot smarter to capture the user sentiments closely and make conversations effective.