Why You Should Be Using Sentiment Analysis for Social Media and Decision Making

Data might be supreme, but your customers are more than just data points. When they’re affected by your product, good or bad, you need to know to move forward or to pivot. Sentiment analysis has come a long way since the early days and can now predict with accuracy the underlying emotions your customers have about your service or product. 

[Related Article: Chat, Social, and Survey Interactions Using AI Idea Analysis]

Use that to your advantage. Customers want relationships more than ever, and utilizing sentiment analysis can help drive your social media campaigns, responses, and overall decision making. Here’s why.

Social Media Builds Branding

As business leaders, we want to build relationships with our customers and clients the way we did face to face, but with the anonymity of the internet, that can be hard to do. Sentiment analysis allows a business to create a desired, core feeling for customers and closely monitor if campaigns and responses match that feeling. 

For example, you want your brand to evoke feelings of family, comfort, and safety, but people rarely just outright say your target words. Combing through hundreds, thousands, even millions of mentions through social media channels is impossible. However, artificial intelligence can process data on that scale.

As you monitor your mentions, you can figure out pretty quickly if the things you’re doing online are building the types of target relationships people want with their brands. When clients and customers express either compliments in favor or complaints against your brand, you’ll know to continue doing what you’re doing or to pivot.

Monitored Sentiment Informs Decision Making

And it informs it in real-time. We used to gather what we could about business reputations and plug it into forecast reports that were cutting edge at the time. However, forecasting reports were never in real-time and made use of data from several previous quarters. Once you launched a campaign, you waited a while before finding the results.

Now, marketing can take a more agile approach. Sentiment analysis keeps a close eye on how your brand is shaping up day to day—everything from instant responses in customer service issues to instant reactions from a newly launched campaign, commercial, or even product. Did your commercial have unintended consequences? You can issue an apology and pivot in record time.

It could also help you predict things like product distributions and make better decisions about inventory control. It can help identify trends in the market well before competitors that aren’t using the same process. Sentiment analysis is sometimes more revealing than self-reporting because people are notoriously bad at identifying their real wants and needs.

It Supports Your Customers

I briefly mentioned responding to customers in the first section, but let’s revisit that. Even one negative comment or post could have dramatic consequences, especially if you don’t respond quickly. In the world of the internet, quickly means instantly.

You may have a marketing team and a customer service department. Still, complaints come in from all social media channels: Facebook, Instagram, Twitter, Reddit, Yelp, etc. etc. etc. and you could pay a team of 100 people to monitor those channels 24 hours a day. It’s impossible.

Sentiment analysis does that work for you so that your team can respond when necessary and devote all their energy to crafting the right response to help bolster your reputation. Sure the internet forgets quickly, but in the meantime, your reputation can tank.

The Data Alone is Worth It

Businesses run on data—big data—and having access to that data is a vital part of what will inform your decision making in the next phase of business intelligence. Sentiment analysis helps you keep tabs on what your customers are thinking, provides clarity into how they (really) feel about what you’re doing, and could be the most vital part of making your decisions.

Sentiment analysis can provide context to your data as well, which is a vital piece of the puzzle. Once you’ve implemented your program, you can receive new insights for critical decisions as you move forward without having to rely on information that’s months old. You won’t have to worry that a negative comment left unnoticed could bite you later. 

Sentiment analysis is an excellent example of “augmented” intelligence or allowing machines to handle tasks humans aren’t good at so that we can return to doing what we are good at. Machines can monitor the wide world of the internet, and your team can craft decisions, respond thoughtfully to comments, and maintain relationships.