Sentiments, this word is available in almost everyone's vocabulary, be it the share market fluctuations, a movie review, or a relationship. All of us would have used this word many times in our daily lives. This simple word is of great importance in the world of customer experience and is wisely analyzed. It is a gold mine of suggestions, concerns, and gap solutions, from the customer's lens.

This article simplifies the core of "Sentiment Analysis" and its application in line with the expectations of new-aged customers.

What is Sentiment analysis?

Let us understand what it means. Today, customers raise their concerns via multiple channels, and one of them is "Social Media". A tweet from a customer about a bad experience is way more than a message. It has the customer's sentiments or emotions based on a particular experience. It will not be wrong to say that "Sentiment Analysis is judging the opinion of a text". This is widely applied to reviews, survey responses, and online and social media applications.

Sentiment analysis helps wade through that data and determine what people think. It uses machine learning and text mining to provide a complete picture. For example, the Obama administration used sentiment analysis to measure public opinion to campaign messages and policy announcements ahead of the 2012 presidential election.

Application of Sentiment Analysis?

Just Imagine that I am in charge of a product, and I am keen to know how customers view the product. So, I start going through tweets or reviews at the portal.

1. "Your product is so reliable! I love it."

2. "Don't use this product; it's a waste."

This is simple enough. Any basic sentiment analysis software will tell that the first tweet is positive and the second tweet is negative. But human tweets (or expressions) are often much more complicated than that. They convey a wide range of emotions and often require context to understand. Look at the following tweets:

• "This product is healthy and non-toxic, which makes it different from others."

• "They are not providing the refund, support, and service are so lazy."

At this moment, we want to find some keywords and make it a regression problem that gives a value between some ranges in sentiment value.

Our Sentiment Analysis tool-

1. Text Analysis

Before you can even begin building an automatic sentiment classifier, you'll need large amounts of diverse sentiment data. QDegrees has access to 500,000+ qualified contributors that can process, analyze, and label text data quickly and inexpensively based on client specifications.

2. Social Listening

Our crowd of contributors can analyze user-generated content about your brand, competitors, or products. Track, analyze, and respond to conversations about your brand with social media monitoring services like QDegrees is providing.

3. Emotion Analysis

Train a machine to recognize emotions with human-annotated emotion data. Whether you want to collect images of facial expressions from a diverse crowd or detect underlying emotions in text, Lionbridge's network of contributors can help gather the training data you need to train your model in emotion recognition.

Sentiment Analysis Uses:

The information gained from analyzing consumer sentiment can improve your business in many ways.

1. Drive Decisions

Our Sentiment analysis solution provides insight into any change in public opinion related to your brand that will either support or negate your business's direction. High or low sentiment scores help you identify ways to restructure teams or develop new creative strategies.

2. Highlight competitive advantage

There are strategic benefits in knowing consumer sentiment related to your competitors. Sentiment analysis can help predict customer trends, so keeping a pulse on the public opinion of other businesses in your industry provides a control group to compare your scores.

3. Predict product lifecycle

Data derived from sentiment analysis reveals how well your product is faring in the market, how you can improve this performance, and if it's time to pull it off the shelves.

4. Improve customer experience

Never underestimate the return on investment from a customer who feels like his voice has been heard. Understanding consumer sentiment provides a direct opportunity to fix the problems real users identify and put more resources behind what your business is doing well.

How We Are Different:

At QDegrees, businesses should be able to maintain speed, scale, and accuracy to understand what consumers are saying about their brands. Our opinion mining and sentiment analysis solution combines AI and machine learning with real-time visualization on business analyst tools to deliver the most accurate results, helping companies complete large-scale sentiment analysis projects in days.