Guide for Comparing the Best Tools for Text Analytics

Knowledge, as they say, is power. But written words aren’t the same thing as knowledge. If you have tons and tons of written text, you need some way to make sense of it. That’s where tools for text analytics comes in.

Text analytics is the practice of combing through large quantities of text to derive useful data. Human beings aren’t capable of handling the quantities of text we’re talking about. Instead, you need to harness the power of software and artificial intelligence. But how does this work, and what tools should you use? Here’s everything you need to know.

What is Text Analytics?

Text analytics is sometimes referred to as text mining, but they’re not quite the same. Both are used to glean data from large quantities of unstructured text. However, text mining is meant to gather qualitative information. Tools for Text analytics, on the other hand, takes that data and uses it to create quantifiable information. It can then create graphs, tables, and charts to visualize this information.

In most cases, text analytics and text mining are used together. Companies use these tools to investigate emails, social media post, customer support interactions, surveys, and other bulk data.

One common text mining method is sentiment analysis, where brands comb social media to analyze how customers feel about them. Another is topic detection, which can be useful for customer support tickets or product reviews. For example, if you sell a set of earbuds and two-thirds of the negative reviews are about the batteries, you know where you need to improve.

Text analytics, on the other hand, would identify patterns in those results. Suppose you develop an app and release a free patch. Your bug testing wasn’t as thorough as you thought it was, and the patch breaks one of the app’s features. It’s a minor feature, but it’s one many users rely on, and negative reviews start rolling in. A text analytics tool would detect the spike in bad reviews and give you insight into what went wrong.

How Can Text Analytics Help Your Business?

The amount of text on the internet is almost unfathomable. So is the rate of growth. Each minute, social media users post 456,000 tweets and 510,000 Facebook comments. And that’s just a drop in the bucket compared to the 156 million emails generated per minute. Obviously, you’re not going to be analyzing all of that data. But it’s a good illustration of how much text is out there.

The main benefit of text analytics software is that you can improve your customer satisfaction. It’s more accurate than simply looking at an aggregate star rating on a site like Amazon. Instead, you can get insight into what people like about your products and where you can do better. You can also monitor the reputation of your brand as a whole. For example, what do people think of your customer service? What are they saying about your new logo? These kinds of data are invaluable for taking your brand to the next level.

What Features Should I Look For in a Text Analytics Tool?

Now that we have a better understanding of text analysis, what makes for good text analysis software? At a bare minimum, you should look for the following features:

  • Data extraction – This is the actual harvesting of data from different sources. Depending on what you’re analyzing, this could mean monitoring customer support chats, trawling through social media posts, or scanning thousands of emails and online reviews.
  • Topic clustering – Topic clustering allows you to create your own topics, and to group those topics as you see fit. You should be able to put them into searchable categories and arrange them in a hierarchy.
  • Sentiment analysis – Determining the emotional state of whoever wrote the text. A given piece of content can be categorized as positive, negative, or neutral.
  • A visual dashboard – A good text analytics tool doesn’t just analyze your data. It can also provide that data in visual formats like charts or graphs.

Other Considerations

Data extraction, topic clustering, sentiment analysis, and a visual dashboard are all important features. But you should expect more from a high-quality text analytics tool. Here are some other things to think about when you’re shopping around:

  • Does it have extra capabilities? Not everything you want to analyze will be written as plain text. Maybe you need OCR capabilities to capture text from images or PDF files. Maybe you need voice recognition to analyze customer support phone calls. Some tools can even recognize handwriting. Before you invest in a text analytics tool, make sure it will analyze all the data you need to analyze!
  • Can you use an open source option? Open source text analytics tools might sound like a cheap alternative, but it’s actually the opposite. Tools like Apache OpenNLP, General Architecture for text Engineering (GATE), or Natural Language Toolkit (NLTK) might be free, but they’re incredibly powerful, with key capabilities like natural language processing. Basic text-mining tools like the Cochrane system don’t offer these advanced features. Unfortunately, you need an experienced IT team that already understands the technology.
  • Should you outsource your text analytics? If you need more capabilities than an off-the-shelf option but your IT team can’t manage an open source system, you can always outsource the job. There are several third-party firms that specialize in text analytics.
  • How big is your company? If you’re a smaller company, you’ll probably be better off with an off-the-shelf subscription plan. These tools provide everything you need for call center transcript analysis, social media monitoring, and other basic functions. If you’re a larger company, you’ll want a more powerful platform with features like predictive analysis and the ability to track customer satisfaction across several channels.
  • Remember the human element. Tools for Text analytics software can only do so much. For example, a survey of online reviews could raise a number of red flags. But you wouldn’t want to rewrite your entire playbook on that basis alone. Instead, your customer service teams could study the data and perform a systematic review of each issue. After they make their annotations, you could move forward with an intervention if necessary.

Use VizRefra to Help Grow Your Business!

If you’re looking for an experienced text analytics partner, consider VizRefra. Their website has a free widget that can analyze any website or plain text document. That’s pretty cool, but it’s just a demonstration of what they’re capable of.

VizRefra is a firm that specializes in text and visual analytics. They provide several powerful tools that businesses can use to analyze their own data. They also provide consulting services to help you harness those tools to your best advantage.