So you have perfected your content strategy and your posts are ready to roll out, but can you analyse what your audience thinks of that?

You can do this with social media sentiment analysis. Monitoring the audience’s sentiment about your brand or business is one of the key elements in your online success. Most of us can gauge, to some extent, how good our brand is doing by the number of comments or likes.

However, sentiment analysis goes much deeper than mere numbers. It is about the thoughts, feelings, and opinions the public has formed about your brand. Thus, it is the “sentiment” that people have.

Why AI for sentiment analysis and how it works

There are a host of conventional tools that allow sentiment analysis, but as we are living in the era of the AI boom, it would be unwise to not take advantage of AI for sentiment analysis as well.

To understand how AI can boost our effectiveness when it comes to sentiment analysis, let’s take a dive into the history of this practice.

Sentiment analysis used to rely on the words being used by the public which would allow us to evaluate what they are thinking. For example, if there are tons of phrases like “excellent product”, “very useful”, and “solved my problem”, you can know that your product is doing very well in the eyes of the public.

However, this method took a lot of time and effort as scraping data is hard. Then, evaluating all the comments is even more time-consuming.

Then came the machine learning techniques which sped up the process exponentially. But the problem here was that language is nuanced, and it’s quite hard to make a machine understand things like sarcasm.

Fast forward to today, we now have advanced AI models thanks to technologies like neural networks, which understand linguistics on a deep level, allowing us to conduct a sentiment analysis with little margin of error.

At its core, it’s all about using AI algorithms to understand and predict the emotion and tone behind the text.

Using AI for sentiment analysis is like upgrading from a steam engine to a space rocket. The makers of Graft, a solid AI layer for organisational intelligence, say about AI models, “Foundation models are versatile and powerful. They’re trained on what seems like everything the internet has to offer. They get language, context, humour, and even those little cultural quirks.”

Major advantages of AI in sentiment analysis

Enhanced accuracy

AI algorithms excel in accurately identifying and categorising sentiment expressed in social media content, providing your business with nuanced insights.

Streamlined efficiency

With AI at the helm, sentiment analysis processes can be automated, freeing up valuable time and resources that would otherwise be consumed by your team’s manual monitoring efforts.

Real-time intelligence

AI-powered sentiment analysis also delivers real-time data on audience sentiment, allowing businesses to swiftly address emerging issues or capitalise on opportunities.

The use cases of AI sentiment analysis

Customer feedback and brand perception

One of the most important, and obviously the most common application of sentiment analysis, would be to gauge how the public is perceiving your brand or business. This is highly crucial when it comes to building a successful online brand because you cannot know how to navigate the digital world without knowing what the public wants.

Getting a sentiment analysis of how well your business is perceived by the public is like getting a roadmap which gives you directions on what to capitalise on and what to subtract from your brand.

Market trends

Even if you are not looking directly for customers’ perception of your brand, or if your brand is just taking off, you can still benefit from sentiment analysis as it can help you identify market trends.

By knowing what the public likes or what it desires in the market, you can build a good understanding of how to carry your brand forward.

Crisis management

Getting concerns from your customers about your product or service that can tarnish your brand’s reputation?

Well, sentiment analysis can help you make quick decisions in times of such crises.

Therefore, it is a great tool when it comes to maintaining good public relations and addressing your customers’ concerns quickly.

Social sentiment monitoring

Apart from monitoring what is directly related to your brand, you can also use sentiment analysis to get a general idea of what the social or political views of the public are.

This can be especially useful for any business which works in a niche that overlaps with social or political issues, such as sustainability or climate change.

Insights from the field

According to a case study by Gartner, AI tools can resolve around 75% of all customer interactions without the need for any human intervention. As this is the turn the industry is taking, it would not be smart to sit back on AI when it comes to social media sentiment analysis.

A similar trend has been noted by Forbes in their study on how businesses are using artificial intelligence in 2024. They claim that “nearly two-thirds (64%) of business owners believe AI will improve customer relationships.”

Considering all these stats from the field experts, it is high time to start integrating AI tools for social media sentiment analysis. Harnessing AI for social media sentiment monitoring will equip your business with invaluable perspectives on how your brand, products, and services are perceived by your audience.