How Customer Sentiment Analysis can Benefit Businesses

A customer may display varied emotions (positive or negative) while engaging with a brand. These emotions determine if the customer is likely to revisit the brand or junk it altogether. According to a McKinsey study, more than 85 percent of customers are likely to purchase from a brand again after having a positive customer experience. A negative customer experience, on the other hand, can reduce the number of customers by 70%. So, how do businesses know whether their customers are happy while engaging with their brand? Instead of merely depending on assumptions, the answer lies in analyzing customer sentiment.

Customer sentiment analysis can let businesses know about the different emotions customers go through while dealing with a particular brand, product, or service. Customer experience insights can help brands offer more of the elements that make customers happy. Moreover, it can improve the customer satisfaction index, customer lifetime value, and customer loyalty, thereby maximizing profits. So, let us discuss this important metric in detail.

What is customer sentiment analysis?

Customer sentiment analysis helps detect customers’ emotions when the latter interact with a brand, product(s), and service(s). The process leverages Natural Language Processing (NLP) and algorithms to identify whether the emotions are neutral, positive, or negative. Here, "neutral" means the customers are happy with the brand but expect more. The algorithms evaluating customer sentiment use two parameters to categorize:

l Polarity: Shows whether the emotions are positive or negative.

l Magnitude: Shows the intensity of the emotions.

Further, the sentiments driving customer experience assurance can be analyzed from customer responses in the form of comments, tweets, or feedback. This process is used by businesses to understand how their customers feel about their brand, products, or services and to improve them. This helps them drive sales and stay competitive.

What are the benefits of customer sentiment analysis?

The process of customer sentiment analysis is leveraged by various businesses for real-time user monitoring, improving customer experiences, and driving profits. The benefits of the process are as follows:

Deliver better customer service: Since bad customer service can make the customer feel unwanted and uncared for, the chances of him or her rejecting the brand or its products and services are fairly high. However, by analyzing the sentiments of customers while using specific products or services, businesses can gauge the issues (if any), and work towards mitigating them. The process offers insights into the negative emotions experienced by customers and the factors responsible for them. Thereafter, businesses can eliminate the factors that contribute to the negative sentiments.

Enhance the quality of products and services: Sentiment analysis can not only capture complaints from customers but alert businesses about the inherent vulnerabilities/issues/glitches plaguing the products and/or services. These can then be fixed by businesses, thereby improving the quality of products and services. Customer responses analyzed through the process can act as a guideline for quality improvement, better product development and service delivery, minimizing customer churn, and enhancing product marketing and presentation.

Develop better marketing strategies: With more insights gained from using the customer experience assurance tools, business enterprises can develop an effective marketing strategy. Further, specific marketing campaigns can be created for the target audience by observing customer conversations related to the brand.

Increase sales revenue: With sentiment analysis capturing the impressions of customers towards a brand, products, and/or services, businesses can work towards optimizing the quality of the product/service. This can make the customers feel good when they come to know that the organization is all ears to their problems. This "feel good" sentiment can enhance their trust in the company and drive them to buy more, thereby increasing the company's sales revenue.

Improve crisis management: Customer complaints can quickly turn into a crisis situation unless they are promptly addressed by taking cues from sentiment analysis. By taking timely preventive actions, businesses can nip any crisis in the bud and save themselves from inviting a chain of negative comments in the public domain.

Use cases scenarios

Some of the use cases to enhance user experience monitoring are:

Identify your key promoters and detractors: Customers are wont to comment on various aspects of a business, and it may not be advisable to get worked up with every comment of theirs. Businesses need to identify the areas/aspects that may affect their NPS score using data science. It is only by correlating such aspects with both promoters and detractors that businesses can understand the ones influencing the NPS score more.

Target detractors: It is said that negative comments travel fast and their impact can be more debilitating for the business. Think about the scathing remarks made by such detractors on social media and the impact they can have on people’s perceptions of a brand. So, how about targeting such people spewing venom about the brand on a priority basis? This can be done by approaching them, understanding their pique, and working towards defusing the situation. For instance, if an apparel company identifies people who are not happy with the return process and works towards mitigating their issues, they can even be turned around to become promoters of the brand.

Track customers’ sentiments: Mere tracking of the NPS may not always yield the right results. What is needed is to track customers’ sentiments related to the specific areas of a business. For example, customers buying merchandise from an eCommerce portal may not be happy with the latter’s return policy and customer service. It is only by tracking their sentiments over time that the portal can improve these segments and address the issues plaguing customers.

Conclusion

After understanding the nitty-gritty of customer sentiment analysis, businesses need to apply the same, especially to customer feedback. Starting with collecting data using marketing surveys, the next step is to analyze the data and assign scores. This can either be done manually or by using specific software applications. Finally, the outcomes of this analysis need to be implemented to garner great results.

Michael works for Cigniti Technologies, which is the world's first Independent Software Testing Company to be appraised at CMMI-SVC Level 5, and an ISO 9001:2008 & ISO 27001:2013 certified organization.