Sentiment analysis is an increasingly valuable tool that enables businesses of all sizes to use machine learning to save time and money.

Given that this is a rapidly evolving technology, we decided to shed some light on how it works in practice and if it can really make a meaningful difference in your business?

How does sentiment analysis work?

Sentiment analysis is also known as opinion mining or emotion AI (Artificial Intelligence). In simple terms, it involves training a computer to do part of a human’s job to drastically reduce the time it would otherwise take us to achieve the same result.

Computers work hard and are always on. They are also much faster than humans at doing certain tasks and make fewer mistakes. We read about 200 to 250 words per minute, whereas robots are able to process thousands of words in seconds. Whenever we spend time reading or processing content in our business – for example when we assess the feedback to our online marketing campaigns – it amounts to an investment in labor dollars.

We can shorten that time (and save money) – by focusing our attention only on the content that is really important to our business. But when we are dealing with large-scale data, how do we quickly know which content is important? And once we know what to look at, how do we determine what’s positive or what’s negative? How do we ensure that we don’t miss infrequent or sporadic feedback given during times when we’re not working? Missing even just one important negative sentiment for example could have serious consequences for your business. On the plus side, catching a trending sentiment early might expose an opportunity to grow revenue and profit across the enterprise.

Through sentiment analysis – we are able to filter masses of content quickly to help us determine what’s important, what’s positive, negative or neutral and what’s worth responding to, and what’s not. It’s also on and always on the lookout, meaning nothing is missed.

Topic discovery

In our personal lives, we are inundated with information and choosing which content to read is time-consuming. We only want to consume content that’s important to us or entertaining. For example, we share emails or articles we believe our friends would enjoy – often opinionated.

We may not always be conscious of it, but the topics we are exposed to are usually discovered and filtered – by friends, family, news organizations or other interest groups.

In business, the articles, feedback and sentiments that could help us make important decisions, are not specifically filtered for us. They’re published and waiting to be found.

Identifying the right information in the sea of data out there is no easy task.

Even if you have a review monitoring system in place in your company, you’re always only looking at a very tiny corner of the big content space.  Combining topic discovery and sentiment analysis allows you to sift through mountains of data in a small amount of time to highlight important information relevant to your business. It does this by finding relevant information and then filtering it by sentiment to rank its priority to be read by the business owner. For example, if the topic is ”your product” and the sentiment index is100 (extremely positive), then it would indicate content worth checking.

Through topic alerts you are kept up-to-date with events relevant to your business on the Internet, allowing you to respond immediately to, for example, a bad article or to stay on top of trends in your industry. Reputation management systems monitor specific platforms such as Facebook, or an internal review system.

Feedback from feedback

Another way sentiment analysis helps to inform business decisions is by enabling business owners to accurately measure and compare the feedback to their campaigns and initiatives over time.

In this way you can get a view of feedback relevant to your business not only at a specific point but also over a longer period, allowing useful analyses that simply weren’t available previously.

For the first time, business managers are able to accurately assess – and have the data to prove – the impact of initiatives such as a marketing campaign or press release versus a baseline, as well as comparing it with the impact of previous campaigns or changes to products (for example widget 2.0) or services (for example new phone plans).

How are we doing over time?  What was the impact of the rebranding last year? How has it affected the sentiment towards our company? Do customers feel more positive now towards our company now than before?

Finally – thanks to sentiment analysis – we are able to answer these questions with solid data behind them, which is invaluable for informing future business decisions.

Use cases of sentiment analysis

There are countless applications of sentiment analysis in business, including brand monitoring, social media monitoring, product analysis, customer feedback and market research.

For example – imagine being able to analyze 100,000 free text customer reviews to identify key themes and the sentiment attached to those themes in a matter of hours without injecting any human interpretation bias.

Types of sentiment analysis

While there are various types of sentiment analysis approaches, those with the highest level of adoption include fine-grained sentiment analysis, emotion detection, aspect-based sentiment analysis, and intent analysis. Read more about different types of sentiment analysis in our previous post.

Responding vs reading

It is easy to see how sentiment analysis can add decision-making value to your business. The next step, of course, is to respond to this information. While sentiment analysis helps us find negative reviews, we still need a human to read, interpret and respond to the information.

Sentiment and topic discovery are useful identification tools, but humans ultimately read the selected content and construct a response or action. The ideal next step would be to automate the entire process, streamlining our business processes even further.

Sentiment analysis is becoming an essential element in today’s business toolkit, but choosing the correct goals, methods and tools for sentiment analysis is crucial to ensure the maximum benefit to your business.

To learn how to make sentiment analysis work for you, please download this free report and feel free to reach out to us.

Let the data experts at REEA Global show you how to get started with sentiment analysis today! Give us a shout — we’re ready to help you hit the ground running.