Guide to Text Analytics Tools

Harvey Rañola |
 12/29/21 |
6 min read

Guide to Text Analytics Tools

There’s a mountain of data out there for brands to sift through in hopes of gaining insights into their industry and consumer base. But without the right text analytics tools, you’ll likely miss critical intel. Text analysis helps break down this data for you, and we’re about to share how it does this.

We’ll cover these main points:

  • What text analysis is
  • Clustering content for easier digestion
  • Text categorization
  • Discovering driving sentiments behind text

And these statistics reveal how important text analytics tools can be:

  • 80% of the world’s data is unstructured.
  • It’s estimated that by 2025 global data generated on a daily basis will reach 463 exabytes. One exabyte is equal to 1.04 million terabytes; one terabyte is 1,000 gigabytes.
  • Artificial intelligence breaks down texted-based data sets for analysis using a process known as natural language processing (NLP).
  • Consumer purchase decisions are driven by emotion – text analytics tools can read the sentiment behind your consumers’ words.
  • The global revenue from the NLP market was $3 billion back in 2017 and is predicted to increase 14-fold to $43 billion in 2025.

Now, let’s explore!

What is Text Analysis?

The amount of global data generated in one day is on the rise. It’s estimated that it will reach 463 exabytes. That’s a mind-numbing amount of data floating around. Thanks to artificial intelligence (AI) and text analytics tools you don’t have to be the one to sort it.

NetBase Quid’s text analysis uses AI to break down text-based data sets for analysis using a process called natural language processing (NLP).  This tech processes and sorts data while analyzing and generating insights from text. It rapidly identifies themes, sentiment, trends and many other indicators found within.

Spotting this intel informs brands on how to position themselves, how to react to pressing concerns and enables them to make important decisions quickly. In fact, text analysis provides insights for all kinds of business use cases, capturing nuanced consumer, media and market understanding. It enables your brand to dissect conversations for actionable insights that inform:

  • Brand health & perception
  • Campaign strategy
  • Product innovation & launch
  • Trend analytics
  • Mergers & acquisitions
  • Competitive intelligence
  • Crisis management
  • Voice of the customer
  • Influencer & KOL marketing
  • Technology scouting

To gain a clearer understanding and see it at work, we’ll explore more below!

What’s in a Cluster?

The ability to process and gain insight from datasets quickly and accurately is critical to your brand’s success. Why? Because 80% of the world’s data is unstructured text from different sources. That’s where text analytics tools come in.

Text analysis uses AI algorithms to aggregate, organize and cluster together text into semantically similar categories. This text data is gathered from social media channels and also from blogs, articles, research papers, consumer reports, even patents. Think of it like a giant kid’s Lego bin. It takes those Legos and sorts them by color, shape, size and any other way it can be sorted into – but in clusters.

These clusters help bring visual clarity to whatever you’re researching or trying to find – whether it’s checking the temperature of your consumer, or finding out what the world thinks about hybrid vehicles.

As an example of text analytics tools at work, our clusters below are the result of a search on hybrid cars and sustainability over the last year. Text analysis reads the room, and breaks this large conversation into smaller clusters, and categorizing them.


But it goes beyond just merely clustering like-conversations. Text analytics tools take brands beyond and derive meaning from text to extract topics, attributes, sentiments and much more.

Text Categorization

To simplify text categorization, think of Boolean searches and their operators. This is text categorization, and it helps to identify ultra-specific topics and mentions to create actionable consumer and market research.

And it goes further, once all your text is aggregated into clusters, text analytics tools analyze and extract themes, keywords, sentiments and even sort out behaviors and attributes. To lay it out plainly, text analysis uses text categorization to:

  • Read and decipher the meaning of consumers’ social media opinions with a high level of accuracy.
  • Analyze data based on all variations of search queries as they occur – in over forty different languages.
  • Identify misspellings, sarcasm, emojis, and brand logos from images to extract information and sentiment.
  • Identify urban words or “slanguage,” for example, “This laptop is so cheugy.”
  • Understand alternative spellings, for example, “boi,” “smol,” or “periodt.”
  • Recognize abbreviations like “LMFAO” or “BRB”

Having a text analysis tool which performs deep parsing of your dataset is entirely essential for understanding things like customer preferences, passions, and behaviors. None of the insight is optional today, not with the constant increase of digital conversations happening. Text categorization illuminates how consumers and the media feel about various facets of your business. Providing context where it previously didn’t exist is an invaluable capability for brands to accentuate their strengths and address any hot spots where conflict is brewing.

Below, we have a text analysis of a top quick serve restaurant. The results reveal top trending terms used by consumers when speaking about this brand. And it’s mostly geared towards the vaccine.


Digging in, we uncover many social media posts speaking to those hesitant to get vaccinated due to not knowing what is in the vaccine. Some customers of this quick serve brand post that ‘now one knows what’s in this chicken recipe either, but they’re eating it.’ It’s a conversation that’s gained some traction, and good to be aware of in our current environment. And that’s the point – text analytics tools help to uncover trending terms and unlikely connections that your brand should be aware of in case something strange comes up. Or in case one mistakenly counts that spike in mentions as purchase intent when it may not be.

Uncovering Sentiments

We, as humans, are a sentimental bunch and our purchase decisions are driven by emotion. And it is emotion which is directly responsible for increasing sales and loyalty to your brand. That’s why it’s paramount to understand the driving sentiments behind a consumer’s post. Text analytics tools worth their weight in retweets should pull this intel and guide your next steps.

For example, someone may post that they “love” their new sweater, but they may be expressing sarcasm. In today’s witty online world, love doesn’t always mean love. Text analysis can tell the difference, understanding the subtle inflections of a post. Having this intel will inform you of a hitch in the works that needs to be addressed before it becomes a crisis.

As an example, this text sentiment analysis reveals a lot of words with both good (green) and negative (red) sentiment behind them. The size of the words indicates the volume.


Most are obvious, however in red is best place.  Clicking on this term reveals that this top meal prep company is limited when it comes to dietary options and it’s not the “best place” to find keto, or vegan dishes. That’s important intel to have about your brand – or about a competitor.

Text analytics tools without the ability to read these subtle differences would have put this in the good press pile. Luckily, NetBase Quid’s tool can spot these differences – and what a difference it can make! If this has been a post which gained more traction, it could have impacted this brand’s health. If this brand is using NetBase Quid, they’ll see it for what it is and take quick steps to get ahead of that conversation before it grows.

With any great tool you can set alerts to warn your brand of any negative sentiments, saving precious time, embarrassment, and frustration. And the key to capturing these sentiment drivers is using a text analysis tool with natural language processing. If your present tool doesn’t include it, then you’re starting out behind. It’s a tech that more businesses are adopting and if you don’t have it, you’ll get lost in the shuffle. Tis the season to level up your listening!

What else are you missing when it comes to consumer conversations online? Reach out for a demo and gain a complete understanding of how consumers, the media and the market are talking about your brand and your overall category. The best text analytics tools allow you to capture all of that and more – and we’re happy to show you how that looks!

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