By Vidhu Nautiyal, Co-Founder and Chief Revenue Officer, CloudConnect Communications Pvt Ltd
May 13, 2023: In today's world, customer satisfaction is paramount for the success of any business.  With customers being the backbone for success of any organisation, brands today are constantly on the lookout for ways to improve customer satisfaction, and sentiment analysis in real-time is proving to be a game-changer in this regard.
As AI-powered chatbots have gained popularity, several have begun to consider how to add sentiment analysis to their functionality. Sentiment analysis is the process of analyzing data to determine the sentiment or emotion behind it. In the context of customer satisfaction, sentiment analysis involves analyzing customer feedback in real-time to determine their sentiments towards a particular product or service. This is done using natural language processing (NLP) techniques, which help to identify the tone and context of customer feedback.
Decoding the Sentiment Analysis Talk
The technology can be used to analyse client chats and ascertain their emotion to improve customer service. Businesses can learn important information about the thoughts and experiences of their consumers by applying sentiment analysis to customer discussions, which helps them make better decisions.
An emerging field of artificial intelligence technology is sentiment analysis. Chatbots can infer the user's emotional state by analysing the user's input. This is accomplished by analysing user input using natural language processing to determine the sentiment level. Then, the chatbot can answer more individually after the assigned sentiment score.
The sentiment analysis procedure uses an automated method to decide whether the text has a good, negative, or neutral sentiment. To monitor client happiness, businesses utilise it to analyse text from live chats, online reviews, surveys, and customer service issues. Among the various applications of sentiment analysis are social media monitoring, customer service analysis, and customer feedback analysis. In addition, sorting can benefit from machine learning technologies and natural language processing.
Sentiment Analysis and Customer Experience
Sentiment analysis is a tool that businesses may use to determine the present sentiments of their customers and take relevant action. When users experience problems with a service or a product, they turn to support. Customers who need to be promptly provided with the necessary support may depart an online platform, forum, or social media channel with unfavourable feedback. Sentiment analysis can assist companies in getting a sneak peek at client reactions to make more informed decisions to enhance customer service. 
These days, customers can contact their sellers and service providers through various channels, including chats, calls, and emails, to resolve issues relating to the brand's services or products. Customer service gaps can be identified by analysing the sentiment of such exchanges between the customer and the support person.
The technology can assess subtleties in support tickets to efficiently assign the appropriate case to the appropriate agent. When the right person handles difficult situations or angry clients, the customer experience is improved. As a result, the problem is resolved more quickly, and the consumer is happier with the service.
Many bots use sentiment analysis and natural language processing to interpret and carefully consider user replies. Focusing on them and hearing what they say is the finest way to interact with customers. The sentiment analysis solution uses the Text Analytics API to extract information by identifying recurrent themes and subjects that would otherwise go unnoticed in data sources. As a result, one can increase competitive intelligence, contribute to better decisions regarding product quality, enhance product segregation, and enhance customer service.
Facilitating higher customer retention
The best method to deal with customer churn and competition is to focus on customer experience and retention. Essential procedures that may instantly affect the client must be considered in the plan. To begin with, improving personalisation on customer calls is required, and interactions driven by data can enhance tailored dialogues.
The addition of real-time sentiment analysis can help quicker call redirections so that a seasoned agent or a superior can handle a customer's service ticket who is upset or has a high-ticket size. However, customer service cannot prevail on its own. Product teams must recognise product and service feedback and use this chance to modify the product following client requirements.

Businesses in various industries can benefit in numerous ways from sentiment analysis. For example, it allows you to shape your market strategy, beat rivals, and obtain real-time data on your products, clients, and staff.
The insights gathered can be applied to improve operational effectiveness, customer and employee experience, brand awareness, and market share, depending on the demands. To fully benefit from the advantages of this technology, pick the appropriate AI solutions supplier and specify product requirements precisely.
Sentiment analysis is a lifesaver for your brand's reputation since it precisely gauges the temperature of the customer's feelings towards the brand, product, services, and interactions. To promote profitability and enhance other business activities, businesses must take advantage of this technological innovation and raise the bar on customer service.
CloudConnect is a business telecom provider offering a fully operated and managed cloud-based mobile-first platform