Sentiment Analysis – Positive, Negative and Neutral

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If you are a business, dealing with thousands of customers, a reliable sentiment analysis tool can help you analyze and optimize customers’ opinions. The opinions you collect can help with market research, product development, and reputation management.

What is Sentiment Analysis?

Sentiment analysis is the identification and interpretation of emotions by analyzing text feedback. Sentiment analysis has different classifications; positive, negative, and neutral. Depending on how detailed you want the sentiment analysis to be, you can extract text from a paragraph, sentence, or a complete document.

Sentiment analysis is a feedback process that digs deeper into text to find content that highlights a customers’ attitude towards your brand. In other words, sentiment analysis identifies opinionated views like happy or sad in customer feedback.

As you are well aware, diverse opinions are the reality in most brands. That’s why it is essential to combine different sentiment analysis to understand how people perceive your brand and plan for the future.

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Types of Sentiment Analysis

1. Fine-grained Sentiment Analysis

This sentiment focuses on the polarity of opinion. It gives you a simple positive, negative, or neutral distinction by offering precise views. If you want to dig deeper into the categories, you can expand and use terms such as very positive, positive, neutral, negative, and very negative. Fine-grained sentiments are common in most workplaces, and you can use them for 5-star rating – for example, very positive can represent 5 stars, and very negative = 1 star.

2. Emotion Detection Sentiment Analysis

This analysis detects emotions in the text. It uses lexicons and machine learning to identify the happy, sad, or angry types of emotions. It is an algorithm based sentiment analysis tool that helps a brand understand why a customer feels a certain way.

On the downside, emotion detection is complex to understand. Some terms such as “your products are a bomb” might be misinterpreted by lexicons. A bomb product can mean it is terrible and can explode, or it is exceptional and fulfills customer needs. For emotion detection sentiment to be successful, human interaction is necessary.

3. Aspect-based Sentiment Analysis

When customers give reviews on a particular product, they mention specific aspects and features that need your attention. To get a deeper meaning of the mentioned aspects, brands use aspect-based sentiment analysis to identify the positive, neutral, or negative features.

For example, aspect-based analysis helps a brand perceive a customers’ view about the features of a camera through a phone’s picture quality.

4. Intent Analysis

This analysis shows the intention of the customer. It analyzes the message to identify the purpose of the customer with your products. Sometimes, it checks to see if the customer intends to use the product or give it to someone. The intent analysis is standard in customer support systems and can help create an effective marketing strategy.

Why Perform Sentiment Analysis?

Massive volume of data is always a significant concern for most businesses. Emails, social media, chats, articles, and support tickets come in big numbers, and most are unorganized. For both the emerging and established businesses, manually sorting out the text data is next to impossible. That’s why automation, through sentiment analysis, is beneficial.

The benefits of sentiment analysis include:

  • Sorting and processing extensive amounts of data. Sentiment analysis saves on time and money you would normally spend on manual sorting.
  • Sentiment analysis identifies, prevents, and manages public relations crisis in a workplace in real-time.
  • It helps you know what is going on around your brand and you can use it to monitor your competitors’ business.
  • Sentiment analysis uses the same criteria to extract opinions from customers. By using the same processes, you reduce variance and gain consistent insight about your brand.

How a Sentiment Analysis Tool can Help You Boost Your Brand

When done right, sentiment analysis adds great value to a business. Sentiment analysis gives a more in-depth insight into how your customers feel and what they expect from your brand.

Monitor Social Media Mentions

Today, businesses rely on social media to reach, engage, and convert visitors. Companies regularly monitor their views and comments to determine the scope of their marketing campaigns. Most large brands receive tens of thousands of comments annually, but few can manually organize the content.

To gain deeper insights from the opinions, brands invest in sentiment analysis tools. Comprehensive sentiment analysis, like what’s offered by Tatvam, go through every comment to explain what’s happening in your brand.

You can use sentiment analysis to monitor Facebook, Instagram, and Twitter posts. From the results, sentiment analysis helps you categorize and label the mentions in order of urgency. You can then send the remarks to the support team for quick feedback.

Track Customer Feedback to Improve Brand Perception

Sentiment analysis allows you to know what customers’ like and don’t like about your brand. It consolidates the positive, negative, and neutral mentions to extract information that will let you learn what customers want.

If, for example, you launch a new TV and receive lots of positive mentions, it shows that customers appreciate the product and can recommend it to someone else. A neutral comment, like “it’s okay”, is a sign of concern since the customer can quickly turn to the positive or negative. Many negative comments mean something is wrong with the product and drastic changes need to be made.

Sentiment analysis can help you leverage customer reviews to improve a product, service, or brand. Sentiment analysis can help you step-up your customer service, so customers are satisfied with every aspect of your brand.

Gain Competitor Insights

In order to stay ahead of your competition you have to monitor their mentions to know what they are doing or not doing and how this can help your business. You can use sentiment analysis to discover the negative comments about a competitor and find ways to fill the gaps.

The positive mentions can help you learn what your competitors are doing well, which will help advance your strategies.

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Conclusion

Sentiment analysis is the present and future of emerging and established brands. By using sentiment analysis, brands can get a definite feel of how customers perceive their products and services. Sentiment analysis can transform how you analyze, interpret, and evaluate customer feedback. Sentiment analysis helps us discover new insights, understand our customers, and empower our teams to become more productive.