Everything you need to know about Sentiment analysis.

What is Sentiment Analysis?

When you are having a heated conversation with someone, you can read their feelings and get a sense of their ideas towards the subject through the words they use, their voice tone, their facial expressions and their body language. Imagine not being able to see them and just judge their feelings towards a topic through a written response. Let us convey the same using technical jargon.

Why do you need Sentiment Analysis?

Sentiment analysis (also called as “Opinion Mining”) is a method of natural language processing. It is analyzing a text and trying to classify the emotions the text tries to convey. It is using artificial intelligence to contextually analyze and mine a text, extracting subjective information. This extracted information is extremely beneficial for businesses to understand the social sentiment of their brand, product, or service, so that they can improve and better their business.

Ultimately people always prefer to go through reviews before buying any products or services. So, text analysis or data mining can give you a better idea on where your products are lagging behind than your competitors and also gives you actionable insights on what to do further.

Where can Sentiment Analysis be used?

The text for sentiment analysis can be gathered from product reviews, customer interactions, or customer tickets where customers contact the company to ask questions about the product or consult about a problem they are having. Where ever there is a scope to measure the customer satisfaction, there is a chance to use text analysis. Few spaces where this can be used are:

• Social Media Monitoring
• Customer Testimonials or Customer Feedback
• Customer Support
• Brand Reputation Management
• Market Research
• Competitive Research
• Voice of Employees

We cannot just limit the scope to the corporate sector but this can also be done to the movie reviews as well. Basically, it can be done on any textual data that represents your businesses values. It gives you an overall idea on what kind of sentiments your customers hold in the market by using the feedback as input, and gives you a better understanding of your customer needs.

How does Sentiment Analysis work?

By gathering this data for text, one can classify how much of the text carries positive, negative, mixed or neutral feelings to get a sense of what kind of social presence the product has. If majority of the text analysis has positive feedback, this is a good indicator that the business is on track and doing well. If, however, majority of the text has negative or mixed analysis of the emotion, this indicates that there is something wrong with the product, service and brand in question and it calls for change. With more advanced sentiment analysis tools, certain words can be extracted to help the businesses identify the key contributors to the problem and tackle that issue. What sentiment analysis does is that it helps the users understand and identify what might be causing the problem, but of course deeper root cause analysis needs to take place in order to dig deep and solve the problem.

On a bigger scale, sentiment analysis is used to gain valuable insights from the customers and helps keep the two engaged. Sentiment analysis automates and speeds the process of getting insights about the key aspects of the product in question directly from the customers and understands the customer pain points and aspects of concern, all by the human level accuracy created by the artificial intelligence technology.

Sentiment analysis, can be scaled in so many different directions; not only can it be used to get insights on customer behavior to better businesses, but it can also be used to predict human behavior. Mainly, it can be used to predict human behavior based on what people are posting on their social medias. For instance, twitter is such platform that generates a great amount of text containing political insights. Through generating and analyzing such texts, the participants of any party can predict the results of the election and try to change this trend through certain practices or policies.

As you now know, sentiment analysis is a valuable tool that can be used to get insights regarding human behavior. Anything you put out on the internet: an amazon review, a question under a “Frequently Asked Questions” section, a comment under a blog post, or a tweet about what kinds of music you like to listen to, will potentially be used for a sentiment analysis, and this is the reality of living in the highly technologically advanced world of the 21st century.