Customer sentiment analysis: why it is excellent for your brand

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Customer sentiment analysis is one of the most useful yet unknown strategies to improve the value of your brand. Marketers think that it is just another way to monitor what people say on social media, but it is far more. More importantly, it is a way to understand clients, their needs and their opinions about you, your company, your services or products.

Knowledge is one of the most important goals we can achieve in our job. It is the key for happy customers and valuable services. And customer sentiment analysis is perfect for reaching these goals.

It is a different, yet a crucial point of view that we are going to discuss right now.

Let us know what you think about it and if you use sentiment analysis in this way!

What is customer sentiment analysis?

Emotions are everywhere and drive our customer experience. They are an essential part of our definition as human beings, and they participate in any of our actions.
When someone loves us, we are happy. When someone betrays us, we are sad.

What happens when it comes to brands?

When people interact with brands, there is always some emotion. It is excellent if the feelings are positive! If not, well, maybe something isn’t going so well. But how can you figure it out? 

Sentiment analysis gives you access to this kind of information to know customers better.
You can understand why they are feeling negative emotions, why, and do something about it. 

It is an automated process that can track and identify emotions in online communications. In this way, it can find out how customers feel about products and services, or the brand itself.
It is useful for brands because they can obtain new insights and answer to their customers most effectively.

Tools based on sentiment analysis allow you to analyze people’s comments and opinions about you and use those data to catch what it needs to fix before it is too late. It is useful if your community counts hundreds or thousands of people – you can’t analyze all their comments by hand, one by one. You would lose time, money and probably even your head!

You can automate the task, so you don’t need to do it manually.

Let’s see how.

Keyword-based sentiment analysis

You can apply keyword-based criteria to identify words associated with positive/negative emotions. For example, “love”, “happy”, “wonderful”, “grateful”, and so on are usually positive, whereas “upset”, “ate”, “horrible”, “awful”, are typically negative.

But, words are one of the most exciting yet complex elements of human beings.

Humour, sarcasm, irony, genuine enthusiasm and more are statuses expressed with the same words but different context. The context is critical to define the meaning that we are assigning to what we are saying.

Here is where the Artificial Intelligence algorithm dramatically improves your results.

How Machine Learning and NLP boost your sentiment analysis

“Great job” sometimes is ironic. “It has been the best experience of my whole life” is sarcastic—the context and the intent track the line between what we say and what we mean.

The use of artificial intelligence algorithms, and specifically Machine Learning, Natural Language Understanding (NLU) and Natural Language Processing (NLP) ones, work for that.

Natural Language Understanding and Natural Language Processing algorithms understand the sentence in its wholeness. Like a human, adequately trained, they can understand the differences in the usage of the words according to intent and context.

Then, it’s time for the Machine Learning algorithms to classify and split the different contents by sentiment.

Why does it work and is suitable for brands?

Now that we know everything about sentiment analysis, you have some new clues to understand why it is so good and fundamental to brands.

If you can detect people’s emotions, you will know how they feel towards your brand. You can catch requests, unhappiness, strategy mistakes and best practices you are already implementing.

Sentiment analysis provides useful insights that can go from customer behaviour to decision-making processes. Every step of the customer journey can have an emotional impact or an emotional intent, and knowing it is crucial to improve and create better marketing strategies.

We need to remember that opinions are strictly subjective, and this is why they are so valuable: they allow focusing and collecting on several perspectives. 

Customer service is one of the elements that benefit more from sentiment analysis because it is one of the touchpoints that have more to do with human emotions.

Let’s see together three reasons why sentiment analysis is the game-changer for your next marketing activities.

Improving strategies 

Sentiment analysis can be a goldmine when it comes to creating better strategies, products and services.

If you know how customers feel towards a specific product or service, you can use those suggestions to improve it or even create something new.

Who better than your customers can tell you what they’d like to see improved?

Customer service

Our Ghostwriter AI algorithms are unique in discovering and classifying emotions and customers’ behaviours.

For example, we are helping some of our customers in detecting satisfaction or dissatisfactions in their customer support phone calls activities.

Other customers are using our sentiment analysis to support their sales if you know the sentiment of your prospect and get data about that you can improve future calls and increase the sales with a higher conversion rate.

Brand reputation

No brand is perfect, but how can you discover if there is any flaw in your touchpoints? You guessed it – thanks to sentiment analysis. 

By checking their text – on Twitter or Facebook, for instance – you can understand what they think about your brand and products. Is there any problem? Something wrong happened in a specific town with your retailers? You are probably going to find out.

Sentiment analysis is excellent for brand reputation because it allows you to check and detect emotions across different channels. 

For example, we help some of our customers analyze emotions across their social channels but also through feedback, chat, emails and assistance requests. Classifying the content and the feelings you have actionable insights to improve what you are doing and improve your business objectives.

What data can we analyze?

Short answer – a lot!

Long answer: bits of information are everywhere; you only have to know where to look. You can pick a lot of data sets from numerous sources.

There are emails, comments on at least four different social media platforms, private and direct messages, reviews… you don’t have to worry about having enough sources!

However, what matters here is the quality of the elements you are going to analyze, and the real challenge is to extract the good value from them.

Also, there are variations in the information you can acquire from the text. There are personal opinions, concerns, popularity issues, technical issues. It is too much for a human being, so we can say thanks to algorithms and AI!

Conclusions

Sentiment analysis is more than a tool that tells you how people feel on social media comments.

It is a set of assets that allows any brand to improve its relationship with the audience, fix their strategies, and make the customer service as of right as possible. 

Moreover, don’t forget that sentiment can help you a lot in comparisons over time. If you keep monitoring your sentiment, and you discover it became dreadful, you can find out when the change occurred and try to understand what happened and why.

Like almost everything else, the secret for good sentiment analysis is the correct analysis of data. And in this, your best friend is Artificial Intelligence!

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