A Comprehensive Guide on Sentiment Analysis: Tools & Use

Sentiment Analysis

Do you not think customer reviews on a product play a significant role in its branding? You are right if you said yes. In today’s rapidly advancing world, everything is running on customer reviews. Good customer reviews attract new customers, and companies analyse satisfaction by applying different methods. First of all, we will learn about this analysis called ‘sentiment analysis’, which plays a crucial role in examining customer satisfaction. The tools, applications, and pros and cons of this analysis will be discussed later. Thus, let’s start our discussion with the definition of sentiment analysis.

What is Sentiment Analysis?

It is a process of analysing customers’ positive or negative sentiment over a specific product. The customer’s feedback is typically in the form of text. The team of a particular company analyses feedback and make strategies in response to those reviews. Sentiment analysis provides answers to issues that are important for businesses.

Tools for Sentiment Analysis

After a brief introduction, you must know what sentiment analysis is. Now, one thing that you do not know is how to perform it. Of course, some tools and techniques are required to perform this analysis effectively. In this section, expert researchers of a PhD dissertation writing service will suggest those tools in detail. A brief description of such tools is as follows;

Lexalytics

Lexalytics is the first analysis tool to convert a text into profitable decisions. It requires previous knowledge of data science to run sentiment analysis tools. Lexalytic’s Semantria tool is the most powerful tool to perform analysis. Lexalytics performs social media monitoring, people analytics and voice of the employee, reputation management.

Awario

Awario is another social listening tool that performs sentiment analysis. This tool crawls through all the blog sites, social media pages, forums and other parts of the web to analyse the mention of keywords. Usually, the keyword is the promotional content of a particular company. The company can use this powerful tool to draw some actionable insights.

Brandwatch

Brandwatch, another powerful analysis tool, was named the leader of social listening in 2020. The capabilities and accuracy of its analysis are at par compared to other tools. Many businesses use this tool to analyse the voice of the customer. It also monitors its mentions on social media pages, and measures brand visibility 24/7. The machine learning customer classifiers are also available in this intelligent tool. The exciting thing about Brandwatch is its “image insights” tool. Beyond text, it also analyses how many times businesses’ logo has been shared. It even tells you the geographical reach of your company.

Social searcher

Social Searcher analyses the keywords, hashtags and usernames across social media pages during their professional career. It provides you with many social insights, including social analytics and audience insights. The free version of social searcher has a sentiment analysis tool. It provides you with the overall sentiment of social media data and a breakdown of posts. It breaks down the posts as negative and positive, which is a plus point.

MeaningCloud

Using MeaningCloud’s sentiment analysis API (Application Programming Interface), you can perform a multilingual analysis. The basis of this tool contains some aspects, such as positive, negative and neutral. Further, the tool tells you whether a specific product got customers’ positive, negative, or neutral reviews. The plus point of this tool is its dictionary. You can add specific vocabulary to analyse the business insights.

Uses of Sentiment Analysis

The applications of this analysis are endless. Businesses use this tool to draw conclusions on different issues and products. It is just a basic application. A brief description of a wide range of uses is as follows;

Brand Monitoring

Keeping an eye on every review and mention is tedious for many individuals. This statement is pretty right because of the amount of data and comments. No one can review and draw a valuable conclusion from all that information without online help. Continuous monitoring and reviews is, thus, necessary for a brand. Therefore, the sentiment analysis lets you monitor your brand with much ease.

Business Intelligence

Sentiment analysis may tell you a lot more than whether a customer is happy or unhappy. Data mining shows you the exact fault lines. It records the general public’s impression of your brand and tells you whether the market trends are in your favour or against you. With such information at your fingertips, making decisions gets a little easier.

Campaign Analysis

Customer opinions are mostly the deciders of the success or failure of campaigns. Their reviews can make your product successful or a complete failure. Thus, we can say that the fate of a particular brand is in the hand of its customers. Seeking frequent feedback from customers and analysing them is a great technique to enhance the acceptance of your products. Therefore, sentiment analysis is also helpful in campaign analysis.

Advantages of Sentiment Analysis

Besides its multiple applications, sentiment analysis also holds many advantages. Some of the significant advantages are as follows;

  • Identify Customers: It allows a company to identify its happy and sad customers. Happy customers are always most likely to be upselling.
  • Handling Customers: While chatting, sentiment analysis allows the agents of a company to handle multiple customers at a time. It also helps you identify which chat is going smooth and which needs attention.
  • Live Insights: Sentiment analysis prides you with live insights into the customer’s mood same like audience analysis. The visual indicators display how this mood changes over time.

Disadvantages

Besides its many advantages, sentiment analysis is not without some apparent disadvantages. Below are some of the cons;

  • Not Universal: Despite its extensive benefits, the sentiment analysis is not a complete replacement for reading responses. Sometimes, it just ignores much text.
  • Recognition: You can quickly analyse whether a statement is positive or negative. But this analysis shows a positive statement as negative.

Conclusion

Sentiment analysis is not an easy thing to carry out. Also, previous knowledge of data science and social management tools is necessary. Various uses and benefits of this analysis make it a charming one. The pros and cons mentioned above are only the major ones. There are many other advantages that you can look for on the internet.