Sentiment Analysis helps improve Customer Experience1

Sentiment Analysis helps improve Customer Experience

Customer Experience

Ensuring an excellent customer experience can be tricky but an effective guide can help.


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In this competitive business world, customer experience is the topmost priority for all companies across every industry. According to Gartner, 89% of companies compete in the market for customer experience. Understanding customer experience helps you gain insights into how you can grow your company. 

Surveys have always been one efficient way to gather data on CX. However, Sentiment Analysis may have just made its way into being an effective approach to deep dive and understand your customer’s mind in a more intimate way.

Watch the video below to learn how Voxco can help you can enhance your overall customer experience.

Customer experience

What is Sentiment Analysis?

Sentiment Analysis is an automated tool that helps unveil how customers feel about your brand and the products and services you offer. The AI-powered tool with Natural Language Processing helps analyze customer sentiment directly from customer interaction from all over the web. 

Sentiment Analysis is a text-mining tool that extracts customer sentiment from textual data across social media posts, surveys, blogs, reviews, news articles, and other such channels and then establishes the sentiment score. 

It provides a deeper understanding of customer’s genuine opinions of your brand. As a result, you can determine whether customer’s opinions or attitudes towards your brand, product, or service are positive, negative, or neutral.

How Sentiment Analysis can help improve Customer Experience?

Sentiment Analysis helps improve Customer Experience2

Sentiment Analysis can help businesses comprehend customer interactions. Using this information they can further evaluate:

  • How do customers feel about the services and experience they receive from your brand?
  • How do customers feel about the products and services you offer them?

These insights can help you improve customer perception of your company and company offerings. You can understand their pain points and you can use the data to make customer-centric decisions to improve customer experience. 

Voice of customers is the ultimate and most effective source to understand what brings out a positive or negative sentiment for a customer. The text-mining tool helps transform customer’s voices into actionable data and assists a brand to offer a flawless customer experience. 

Let’s see in what ways Sentiment Analysis helps an organization improve customer experience.

Provides proactive service to prevent escalation 

Customers leave traces of huge amounts of data all over the internet which can be used by organizations to predict potential issues. You can use Sentiment Analysis to track customers’ feelings in real-time. 

Track social media

Customers express their displeasure with products, services, or a brand in general on social media platforms.

You can use sentiment analysis to track customer’s feelings about their experience in real-time. This can help you detect emotions behind the comments which can help you understand pain points in customer experience. As a result, you can offer immediate solutions thus preventing PR crises and improving their experience.

Monitor live interaction with Customer Support

There is a lot of information to uncover when customers interact with support agents. 

  • Is the customer unhappy or frustrated?

Sentiment Analysis can be used to analyze the conversation customers have with the support agent in order to prevent any escalation. Insightful data on customer’s real-time emotions can empower agents with the knowledge that can help them better serve the customer and diffuse the tension. Agents can offer proactive solutions thus increasing customer satisfaction. 

Be it during live interaction or in social media comments, any potential issue can be dispatched to the right agent. Friendly service and knowledgeable help at the right moment can make a positive impact on Customer Experience. The real-time analysis helps prevent any crisis, resolve the pain points, and provide seamless customer services.

Resolves cases faster by improving Customer Service

Customers seek help from Customer Support when they have issues to resolve. Sentiment Analysis can help your agents understand the customer’s current mood and take necessary measures based on that. 

Customers use different channels like chats, calls, and emails to interact with customer support to resolve their problems regarding the services or products offered by the brand. Using sentiment analysis on such interaction between customer and support agent can help discover the gaps in service received by the customer. 

Sentiment Analysis can be used to evaluate nuances in support tickets to measure customer sentiment scores. This can help streamline the process of assigning the right case to the right agent more effectively. 

When the right agent deals with a challenging situation or angry customer it leads to a faster resolution of the issue. This helps improve customer satisfaction with the service and thus improves Customer Experience.

Improves product/ service offering

Using Sentiment Analysis on product reviews left by customers on your website, e-commerce sites, surveys, and other channels can help you uncover the gaps in customer expectation and the product features delivered. It can also help you observe product performance. 

Sentiment Analysis can help you understand the root causes that lead to negative customer sentiment scores regarding the products and services. Real-time customer sentiment analysis helps discover the bugs immediately before it causes more trouble for other customers. 

You need to track customer’s feelings over time about the brand offerings to track the shift in customer behavior. By monitoring the reviews you can measure customer perception about your products and services at a more granular level. With the data, you can improve product features, or enhance services to provide excellent customer experience.

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Personalize Customer Communication

Sentiment Analysis can decode customer’s emotions which can help you personalize the interaction in order to improve Customer Experience. Customers are expecting personalized messages from organizations. They want the organization to know exactly what the customer wants and feels and offer relevant experiences tailored for their needs and demands. 

  • Sentiment Analysis can evaluate the past as well as live interactions among customers and agents, to provide agents with insight that they can use to customize the communication. 
  • Sentiment Analysis can also identify what type of messages triggers negative or positive emotion in customers. 

In both cases agents can customize friendly responses that can positively impact customer’s emotions and leave them with a positive experience. 


Sentiment Analysis empowers an organization to truly understand what a customer feels about your brand and their experience with you. It offers you all the data from all over the internet to assist you in delivering an exceptional customer experience. 

Sentiment Analysis paves the way to reduce any potential issue that can upset your customers and reach out to them to offer them a delightful experience. The text-mining tool identifies the emotional triggers and helps you optimize your customer service to engage loyal customers. 


Customer Sentiment Analysis is a combination of AI and NLP (Natural Language Processing) that uncovers emotions in textual data online. The tool identifies how customers feel about a brand and its products and services.

There are four types of Sentiment Analysis:

  • Fine-grained Sentiment
  • Emotion Detection Sentiment
  • Intent Analysis
  • Aspect-based Sentiment

A sentiment Score is a measurement system that indicates the emotional depth of the text which you are evaluating. The score detects the positive or negative emotion on the text and associates it with a score. The score makes it easy to understand customer sentiment.