Implementation of Natural Language Processing for sentiment Analysis

The application of NLP to the field of customer service has the potential to significantly raise levels of satisfaction among users and revenue generated from those users. Among the many applications of natural language processing in customer service discussed in this article are sentiment analysis, text categorization, and language creation. With the use of sentiment analysis, businesses may gauge the tone of a customer's feedback and tailor their response appropriately. Automatically forwarding customer service enquiries to the correct team is a viable use case for text categorization. Through the use of language generation, answers to commonly requested queries may be generated mechanically.Furthermore, the article delves into the economic gains that may result from using NLP in the service sector. Some examples of these advantages include reduced spending on administrative activities as a result of automating them, and an increase in sales as a result of happier customers. The necessity for extensive volumes of training data and the possibility of bias in the algorithms are two of the main obstacles and concerns for adopting NLP in customer service that are discussed in the article.