What Purpose Does Sentiment Analysis Serve?

Sentiment analysis studies human emotions scattered across the world wide web. It empowers brands and users with the ability to investigate what’s in their customers’ minds. Decoding a user’s emotions is done by employing Natural Language Processing (NLP) and automation tools, including Artificial Intelligence, machine learning, & data mining. Siphoning vast swathes of data available to us on social media websites and the internet has been made easier by modern automation tools.

Just mining data and amassing it is useless unless we can derive some conclusions. It is here that Sentiment Analysis comes into play. So, what purpose does sentiment analysis serve, and how does it help companies serve their customers efficiently? Let’s find out.

What is Sentiment Analysis?

Valuable insights into the sentiments of a person regarding any product or service are sentiment analysis. Sentiment analysis helps brands sell their products more efficiently. A company can excel in a certain industry if it knows what people want in a given service. Today’s age is characterized by data, with tons of it available online, with billions of social media users writing their hearts out on the world wide web. You can get tons of data regarding any specific item, which was elusive in the 20th century. However, with lots of data comes many variables and the need to process them.

While the machines may be excellent at collating and organizing data, they’ve to be taught when it comes to the interpretation of data. Machine learning and NLP (Natural Language Processing) helps machines interpret data. The ability to decode unlimited amounts of text and the context behind it is Sentiment analysis. It is a measure of the subjectivity in any given text. Social media sentiment analysis involves analyzing social media posts, including tweets, postings, blogs & internet articles. Whatever the case, Sentiment Analysis helps us get closer to the emotions of online texts.

What is Sentiment Analysis Used for?

Service providers and companies use sentiment analysis to maximize their profits, increase efficiency and improve their services by catering to customer reviews and experiences. Insights into the minds of the end-user can be beneficial if properly acted upon. Sentiment analysis can be used for various purposes, including finding out the polarity of people and their experiences towards a service or product. Here, polarity means the degree of positivity or negativity towards an item. The polarity of public opinion is extremely important to gauge any product’s popularity. Social media channels are a great source of finding out customer reviews and opinions.

Apart from polarity, it measures customers’ satisfaction, i.e., positive emotions with specific product characteristics and how they feel about the product. The monitoring of human experiences via social media is called opinion mining. These emotions can make a brand improve its service delivery and follow a path of continuous improvement of its products. Thus, maximizing the product’s usefulness to end-users. Also, it can help such companies avoid mistakes by addressing any negative sentiments of the customers. Furthermore, it helps ad agencies evaluate their marketing campaigns and new brands to conduct market research and help companies connect with their customers.

Types of Sentiment Analysis

Aspect Based

A thematic analysis of a product or a service is known as Aspect Based Sentiment Analysis. Aspect Based analysis uses a product’s characteristics to its advantage. Categorization of these characteristics is done by making clusters describing such characteristics. For example, when talking about a cellular phone, we can divide its features into categories such as processing power, memory, screen brightness, network capabilities, etc. Hence, when a customer mentions that the phone’s brightness could be better, the company can respond by increasing the brightness of their phone.

Aspect-based analysis decodes negative and positive sentiments through feedback forms, surveys, and social media posts. It helps the brand and the company realize its true potential by acting upon any negative mentions by customers to improve its product. It also leads to a robust QA/QC department that aims to improve the output of their product in line with customer demands and utility.


Another form of sentiment analysis is fine-grained, which revolves around sentiment scores. These scores are objective values regarding a product/service of its usefulness. Users can choose from a scale of 1-5 or 0-100 to give their approval about a certain product. Each score is assigned an approval rating. In the end, the results give us end users’ response, whether it is positive or leaning more towards negative.

Emotion Based

Human emotions can be an intriguing aspect to figure out, especially from online postings and social media posts. Emotion-based sentiment analysis uses machine learning to extract human emotional elements from the online text it analyzes. Using such analysis, a company can easily find out why a particular product performs better than others and how to improve its overall service delivery.

Benefits of Sentiment Analysis

Amassing data without the tools for its analysis is useless. Sentiment analysis is a harbinger of success in today’s age of data. Data is paramount in any success story, but a company must analyze it to one’s advantage. The importance of analysis is the difference between well-performing and struggling brands. Using sentiment analysis to gain meaningful insights into how customers view your products can help improve them.

Not only this, but it also helps gain customer trust, which will ultimately increase sales. Providing quick solutions to customer problems also results in a trustworthy brand. A brand that people will think of using long-term. It will help the company achieve its targets quickly and save on unnecessary marketing campaigns. Companies can drastically cut costs while advertising a given product once they know how to get into a customer’s mind.

Choosing the Best Tool

Selecting the best tool for a given job can be the deciding factor for the outcome of such a job. A mismatched tool will result in frustration, financial loss, and lost time. In contrast, the optimum tool will result in a successful venture and increased profits. Each sentiment analysis tool comes with its level of complexity and ease of use.

At VizRefra, say goodbye to expensive marketing campaigns and hello to targeted campaigns with maximum reach and turnover for your brand. Our team offers a range of data mining services, including sentiment analysis, to get actionable insights into the customer’s mind to target their preferences to your advantage. Be it news articles, blogs, website listings or user reviews; our sentiment analysis tools can give you the best feedback for your products.