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As the world is advancing into an age of constant like, loves, tweets, comments and live-feeds, it has become critical for a brand to understand and track the overall sentiment of its customers and users at any given time.

After a positive customer experience, more than 85 percent of customers purchased more. After a negative experience, more than 70 percent purchased less. So, getting this wrong can prove a costly exercise”, says a Mckinsey study.

Customer sentiments have emerged as the number one factor that drives purchasing decisions in customers. Sentiments have the power to drive or destroy value for your business, and most often they are hidden.  Though sentiments are hidden, they play a large role on customer behavior, and influence what customers buy and when they buy.

“To succeed in business, you need to be original, but you also need to understand what your customers want.” – Richard Branson, business magnate, investor and author. 

But how do we know what customers want, what do they feel about our products and services? Are we evoking the right feeling in people to make them drive value for our business?

Imagine that you operate a small apparel store. You generally receive about 50 customer responses in the form of survey responses, emails or messages every month. This is a manageable amount, and you can go over each response yourself to find the sentiment of each of your customer, their preferences and expectations. But image if you start receiving 5,000 responses every month!!

Needless to say – impossible!

In today’s online world, where we’re justifiably suffering from data overload, companies have access to mountains of customer feedback. But if humans try to sort and analyze the data manually, it becomes an impossible task to conclude the analysis without any errors or bias.

But Hold on!

There seems to be a pot of gold at the end of the rainbow for companies who struggle to wade through the ocean of customer data.

Welcome to the Automated sentiment analysis!!  

When you have access to a lot of information about your customers, rather than ignoring your customers’ sentiments, brands should translate those feelings into actionable business insights.

Further into this article, we’ll explain sentiment analysis and its importance, the different areas where sentiment analysis can be applied, and the various tools that you can use for sentiment analysis. 

What is Sentiment Analysis?

In simple yet powerful terms, Sentiment analysis is the way to track the heartbeat of your brand.

Going by the definition, Sentiment analysis is a type of data mining that measures the inclination of people’s opinions through natural language processing (NLP), computational linguistics and text analysis, which are used to extract and analyze subjective information from the Web – mostly social media and similar sources”

The analyzed data quantifies the general public’s sentiments or reactions toward certain products, people or ideas and reveals the contextual polarity of the information. Sentiment analysis is also known as opinion mining. 

When people post on social media, there are a lot of emotions or sentiments behind every post. Sentiment analysis will help you to tap into customer opinions.  

Paul Hoffman, the CTO of Space-Time Insight, once said, “If you want to understand people, especially your customers…then you have to be able to possess a strong capability to analyze text”.

We couldn’t agree more with Paul!!

In sentiment analysis, a piece of text is automatically scored based on the sentiments and the opinions that the text expresses.

The opinions expressed in the text are generally categorized into three perceived sentiments:

  • Positive sentiment
  • Neutral sentiment
  • Negative sentiment

For example:

“The car is fantastic” (sentiment=positive/satisfaction)

“I’m not sure if I like the new design” (sentiment=Neutral)

“The car ride quality is bad” (sentiment=negative/dissatisfaction)

 So, if you want to deep dive into the sentiments and emotions of your customers to know how they feel about your business, sentiment analysis can do the trick.  

Why Sentiment Analysis Is Important?

According to projections from IDC, 80 percent of worldwide data will be unstructured by 2025. 

Unstructured data poses a unique challenge for organizations that wishes to use the data for further analysis. This is where sentiment analysis comes handy. Sentiment analysis allows companies to derive sense from the sea of unstructured text by automating the analysis of customer conversations and to get actionable insights, thereby saving hours of manual data processing, and bringing in higher accuracy.

What is Sentiment Analysis Used For?

Sentiment analysis is great to derive insights and to understand what customers are looking for in a product. To apply sentiment analysis correctly, you need to understand what sentiment analysis is used for.  

Here are 5 solid reasons for using sentiment analysis to improve your business performance:   

1. Track customer perception 

“It comes down to how your customer experiences the brand – and how that brand makes a person feel.” ~ Alex Allwood, The Holla Agency  

Perhaps the first and foremost use to sentiment analysis is to track customer perception, that will help you in brand building. Sentiment analysis gives you an opportunity to track current customers, online audiences, industry experts and social media influencers to identify discussions happening online about your brand.  

For instance if you want to dive deep into customer perception for the company Slack, you can visit Capterra. There are more than 16,000 reviews that have valuable and authentic opinions about Slack. With the help of sentiment analysis, Slack can consolidate all the reviews and analyze them to extract customer opinions. Sentiment analysis helps them to easily dissect what customers feel about Slack.

Sentiment analysis gives you the ability to process huge amount of information that can be used to deep dive into the customer perception. 

2. Step-up customer service

Customer service is all about making your customers fall in love with you. Good customer service dramatically increases your revenue, whereas poor customer service can be detrimental to your business.

For example,

“I don’t like their refund policy” 

and 

I was waiting for 28 days with no clue about my refund. Their refund policy is really bad”

The above two customer opinions throw a lot of light when you perform sentiment analysis. The first sentence is very generic and just says that refund policy is not good. There is no additional information on why the customer is unhappy. But, if you look at the second example, it clearly says there was a long waiting period of 28 days. The dissatisfaction is very loud and clear.

Through further sentiment analysis, you will be able to find whether there are more customers saying the same feedback, and you can analyze if there is a pattern. This way you can step-up your customer service by working on fixing the problem.

3. Plan Product Improvements

Every brand wants to build a product that is desired by customers. Entrepreneurs love to see customers queuing up waiting for stores to open so that they can lay their hands on their favorite products.

But how can brands do this? Of course, the only way to do this is to know what people want. That’s when sentiment analysis comes handy. Sentiment analysis can be extensively used to learn about product improvements.

For example, in a study conducted by a student of Oklahoma State University, Amazon reviews were analyzed to find out brand preference. Samsung phone models (Galaxy S6 & Galaxy S7) and Apple (iPhone 6 & iPhone 7) were used for the study. It came out that customers who had a higher preference for a reliable battery and a good screen went on to buy Samsung phones, whereas iPhones were preferred by customers who are more attracted towards design and camera.

Filtering comments by topic and sentiment, you can also find out which features are necessary and which must be eliminated. Armed with sentiment analysis, the product development team of an organization will know the features that customers are looking for. 

4. Prevent an upcoming crisis

Can sentiment analysis help to identify issues before they become bigger problems? 

Absolutely!! Spotting and preventing a potential crisis is one of the main advantages of sentiment analysis.

When a brand is constantly monitoring the emotions that are expressed by the online audience, it can avert a huge disaster that can happen due to negative comments.

We have seen the example of Taco Bell who undermined the power of social media. A video where an employee started calling the police when a deaf man was trying to order food at a drive-thru, went viral on social media after it was posted by the mother of the victim.

When a brand starts seeing some negative comments, sentiment analysis can contextualize the crisis:

It will analyze the volume of the negative opinions – too many or just few

It will analyze the tone of the comments – too angry or just a little angry

Sentiment analysis can also back-track the data and get data that belong to a specific time period, to perform a trend analysis.

This information will allow the company to take charge of the situation and fix it before it snowballs. By identifying a sudden influx of negative online comments early on, brands can easily spot the upcoming crisis and take enough measures to stop it before it spreads. 

5. Gain competitor insights 

What do you do if you have to beat your competition? You can closely monitor your competition – not actually to copy them but importantly to discover smarter ways of reaching the audience – which both are targeting.  

Competitor analysis is yet another reason to look at sentiment analysis –  based on keywords that matter to your industry.

You do not want to conduct sentiment analysis to look at what your own brand does well – I assume that you already know this!! Sentiment analysis is used to know what your competitors are doing well (or not doing well), and how this information should be used to change your approach.

See the example of Bud Light’s new “victory fridge” campaign that targeted the Cleveland Browns fans. They set up locked “victory fridges” in Cleveland bars that would be unlocked when the team wins. The company received a lot of love for the gimmick.

These positive sentiments helped other brands to pinpoint where competitors are succeeding. At the same time, negative sentiments will reveal opportunities for your brand allowing you to fill the void.

Sentiment Analysis is difficult, but AI-based tools have an answer!  

So far, companies have followed the traditional methods of analyzing sentiments. Surveys, questionnaires, focus group discussions, and telephonic interviews were just enough to understand the sentiment of customers. 

With the influx of internet and the data available online, machine learning and artificial intelligence (AI)-backed technologies are emerging to analyze sentiments from a wide variety of text  – with a greater degree of accuracy. 

Below listed are companies providing tools and APIs for sentiment analysis or sentiment annotation. 

  1. Clootrack 

Clootrack is an Artificial Intelligence-based analytics platform that effectively gives companies the prevailing sentiment of their customers. It allows to derive highly actionable insights that they can use to devise and execute more effective strategies, product improvements, better customer service, and marketing promotions. These would further enhance positive perceptions, while addressing and ultimately eliminating the negative ones.

2. Monkey Learn

The company offers pre-built classifiers for automated text classification and text extraction tasks. They also have developed text classification and text extraction APIs for sentiment analysis. You can upload CSV/Excel files or connect with your apps via direct integrations, Zapier or API.

3. Gavagai 

Gavagai sentiment analysis agency conducts meaning-based text analysis with their Gavagai explorer. The Gavagai explorer API allows you to integrate with the Gavagai explorer.

4. Lionbridge

Lionbridge offers custom-made AI training datasets so that companies don’t have to worry about collecting and annotating data. They offer AI solutions such as natural language processing component development, custom data collection programs, and secure, on-site annotation services.

A Powerful Tool in The Right Hands 

Sentiment analysis, in a composed and a self-assured manner, is preparing to have big impact on brands in the near future. The algorithms used in sentiment analysis can help brands to multiply their reach by assisting in crafting brand messages and analyze what makes customers tick.

There has been a growing number of sentiment analysis tools and platforms that provide all the necessary resources to get started without any excuse for being left behind.

Smart brands, who prepare to embrace sentiment analysis early on either by choosing intelligent tools or by building their own, will see the light of the day.

Listen to Your Customers and Move With Them!