How Organizations Thrive Using AI, NLP & Text Analytics Technology on Social Media

Social media is a powerful tool for organizations of all sizes. It allows organizations to interact with customers and prospects in real-time while providing access to information they would otherwise not have access to. Social media also provides a way for companies' brands and products to get exposure on a global level.

Perhaps the most fascinating part about the power of social media for business is that there is a way for smart organizations to gain valuable insights that the billions of people using social media whisper. It's called social listening.

According to Statista, a company specializing in market and consumer data, social media usage is one of the most popular online activities. In 2021, over 4.26 billion people were using social media worldwide, a number projected to increase to almost six billion in 2027.

Social Media and Social Listening

What is social listening?

Social listening is the act of monitoring and tracking mentions, conversations, reviews, and other content related to your brand or product/services. It allows you to gain valuable insight into what people are saying about your brand or business on social media channels to improve your customer experience and meet customer needs better.

How does text analytics for social media work?

Text analytics for social media uses natural language processing (NLP) technology to analyze all the words in a given piece of text content. In this case: tweets from Twitter users—and identify essential information such as sentiment (positive versus negative), topics discussed, unique authors, etc.

Deeper dive into text analytics and natural language processing

Text analytics is the process of extracting meaningful information from unstructured text.

NLP is a subfield of AI that analyzes human language to make sense of it, often by implementing statistical models and machine learning techniques. NLP is used in many industries—from healthcare to marketing—and has applications in big and small data scenarios.

For example, you might use NLP on social media posts to determine which words are most frequently used by your target audience or which hashtags they commonly use alongside specific phrases.

Text analytics and sentiment analysis

One of the biggest changes in business over the last decade is how companies interact with their customers. In today's digital world, customer service and marketing strategies have evolved to include social media channels like Facebook and Twitter.

The challenge is that this new medium provides a wealth of information that needs to be analyzed and acted upon quickly if you're going to stay ahead of your competitors.

That's where text analytics comes in. Text analytics refers to using software tools that can analyze large amounts of unstructured text—think social media posts—and extract valuable insights about what your audience thinks about your brand or product offerings.

Your organization can leverage the insights from social media conversations to get ahead of potential issues, identify key influencers and find new opportunities.

Customized text analytics tools can help you identify key influencers and build a data-driven strategy for your business that will improve the way you do business with your customers.

Conclusion

In this post, we've taken you through how text analytics for social media works and provided a brief overview of how this revolutionary technology can help your organization avoid potential issues and identify new opportunities.

Contact us today to explore the possibility of leveraging AI, NLP, and text analytics tools like eClerx's Minerva.