Several hundreds of thousands of raw data files are uploaded by users every day to social media sites. Online user data provides access to an enormous amount of information regarding products, services, places, and events, which makes it suitable for sentiment analysis. Valuable information can be extracted by analyzing the sentiment of the data. It is a method for interpreting opinions within a text that uses Natural Language Processing (NLP) to extract positive, negative, and natural meanings from user-generated content shared on social media platforms. Sentiment analysis has been previously applied to products or movie reviews to understand customers' interests better and, thus, improve outcomes and service offerings.

In a world where a single tweet can make or break a brand, it is crucial for companies and brands to invest in social media automation and analysis to derive actionable insights on brand perception. You would not like to wait for 12 hours to reply to that negative comment while #quit prefixed with your brand name trends on Twitter and Instagram, would you? Studies have shown that customers tend to be more vocal and frank with their views on social media. How they perceive a particular brand, its products/services fundamentally influence their behavior. So, for brands, being able to dig deep into the comments, replies, conversations, etc from customers can help uncover an unbiased view of their customers' behavior and persona, helping them understand customer intent and sentiments better.

Today's marketers are rightfully obsessed with metrics. But don't forget that your customers are more than just data points. And yeah, it's easy to overlook our customers' feelings and emotions, which can be difficult to quantify. However, consider that emotions are the number one factor in making purchasing decisions. With so many consumers sharing their thoughts and feelings on social media, it quite literally pays for brands to have a pulse on how their products make people feel.

Before delving into the nitty gritty of exactly how sentiment analysis works, let's break the concept down into something a little more tangible, shall we. Have you ever wondered what the South African public thought about, let's say, Iceland's football team defeating England in the Euro 2016? Well, that right there my friends, is why sentiment analysis software exists – to make vast quantities of data easily understandable at a glance. Think of it like a snapshot of the emotional response to a given topic. You might be asking yourself, but what about online surveys and polls, isn't that their purpose?