How sentiment analysis can strengthen a customer support workforce

The boom of big data is not showing any signs of slowing down. And with over half of North American companies utilizing this particular technology, more and more businesses are reaping the benefits of smoother operations and overall reduced costs. CEOs around the globe are catching on to the fact that analytics has become a necessity in order to stay competitive and profitable. In fact, Maryville University’s industry outlook for business data analytics predicts that the U.S. market is expected to reach $95 billion by 2020. In particular, sentiment analysis — also known as conversation mining — is transforming the way industries rely on customer service operations.

Businesses that have adopted sentiment analysis have seen an immense improvement in the quality of their customer service. A survey by Opus Research reveals that a whopping 72% of companies believe that sentiment analysis leads to improved customer experience, while 68% agree that it reduces costs overall.

Sentiment analysis is especially beneficial for support conversations, where the business is dependent on a high level of customer satisfaction. The technology extracts crucial points from the data received through tickets on a daily basis and provides value through advanced analytics. It is able to categorize and process this information to provide real-time suggestions and solutions to agents and supervisors.

Through sentiment analysis, data received from various departments in the company can be compiled and made sense of as a whole, instead of remaining disjointed and disorganized. Below are some of the best examples of the ways this technology can strengthen your customer support workforce.

Immediate agent performance feedback

Sentiment analysis is often employed to improve customer satisfaction, but the first necessary step may be to use it on your own employees. Automated scoring is one of the major advantages of having the tech in place because it provides real-time feedback and scoring which can be implemented across workers after each interaction. 

The feature can be especially useful when training new employees, as it can help managers immediately identify what the new hires have to work on.

Real-time customer problem solving

Tools available through sentiment analysis can help identify distressed or unhappy customers and notify managers or supervisors to step in. By combing through the available information from conversations with the customer, the tech can provide suggestions and solutions based on customer trends and previous interactions.

Customer service maturity assessment

Data-driven scripts

Sentiment analysis can identify which agents have had the most positive customer interactions, and collate their conversations. Managers can then use this information to improve or alter existing scripts. Furthermore, sentiment analysis can monitor the way employees deliver their scripts by detecting if they are using the correct tone, intonation, and choice of words. This data is invaluable for supervisors during employee evaluations and training.

Round the clock availability

Not all companies can afford to hire hundreds of agents to respond to all incoming conversations 24/7. Enter sentiment analysis and artificial intelligence, which can allow businesses to run non-stop without the need to hire more people. The tech is no longer limited to automated and generic responses either because chatbots nowadays have the capacity to have meaningful conversations with clients. Bots can respond and resolve problems, answer questions and provide suggestions, just like a person. Using sentiment analysis in this way means making your customers happy with the fastest response rate possible.

Personalized responses

Having touched on the technology’s capacity to have in-depth conversations, it’s important to note that this feature can greatly boost customer satisfaction and loyalty to the company. Research published by The Financial Brand indicates that 80% of customers are more likely to engage with a company if it employs a degree of personalization. Sentiment analysis is able to capture information about individual customers and relay this to agents during live conversations. Knowing the customer’s expectations and previous reactions can help the agent personalize their responses and provide a better customer experience.

Reduced costs and increased revenue

All the benefits of sentiment analysis can also be seen in a company’s financial reports. As a result of using this technology, businesses can expect a reduction in unnecessary callbacks because of improved agent performance. Moreover, there is a great chance that live calls are lessened since a reliable chatbot is in place on the company website. Lastly, less money will be spent on recruitment because staff retention will be higher as a result of effective problem identification and early training.

Overall, there is no doubt that sentiment analysis is the future of the customer support workforce. The vital role that agents play cannot be underestimated, and insights that sentiment analysis can provide will reinforce their skills and interactions. Businesses dependent on customer satisfaction who haven’t invested in reliable sentiment analysis programs should integrate them into their marketing strategies as soon as they can. Companies who do this will have improved operations, loyal customers, effective agents, and a seat at the forefront of the customer service industry.