Text Mining Frees Customer Insights Trapped in Unstructured Content

In a perfect world, every customer would fill out a monthly survey so businesses could easily quantify their experiences. In the real world, things are decidedly messier.

Text conveys nuance that numbers simply can’t 

Customers are constantly dropping clues as to how they are feeling about the brands they do business with, sharing sentiment, emotion, opinions, and intent in emails, chatbots, social media posts, online review sites, and other hard-to-analyze places. These rich customer insights are trapped in unstructured content that requires substantial manual effort and cost to extract. 

IDC estimates there will be 175 zettabytes of data globally by 2025 and 80% of that data will be unstructured. (To put it in perspective, 175 zettabytes is the equivalent of 175 trillion USB sticks with a 1GB capacity). With customer insights hidden, enterprises are missing out on a 360-degree view of their customers that could be used to inform everything from product development to brand narrative to return policies and beyond. 

A lack of customer insights can also mean enterprises are leaving money on the table. According to PwC, 43% of consumers would pay more for greater convenience and 42% would pay more for a friendly, welcoming experience.

Dig out trapped insights with text mining

Traditional methods for gaining customer insights – like combing through 3rd-party review websites, Google Analytics, competitive research, and survey results – are slow and expensive. They also leave a lot of the good stuff buried because it’s too difficult to pull out. 

What is text mining? 

Text mining turns unstructured text into a structured format to identify useful information and insights. It uses technology like natural language processing (NLP) and machine learning to identify trends, patterns, and relationships that would otherwise stay hidden. With the vast amounts of unstructured textual data generated daily through channels like email, social media, and other forms of digital communication, text mining is a powerful tool organizations can count on to transform unstructured content into shareable, actionable insights. 

Robust text mining in action

OpenText™ Magellan™ Text Mining uses AI and machine learning to transform unstructured content into insights that would otherwise be almost impossible to detect.  The technology can analyze any unstructured user-generated content from email servers, content stores, application data, and processes or workflows. Text can be buried in any of the following:

• Emails 
• Chats 
• Survey answers 
• Audio and video transcripts 
• Blogs 
• Editorials 
• Letters

It then gets down to work, performing the following functions: 

• Language Detection 
• Concept Extraction 
• Text Classification 
• Named Entity Extraction and Relationships Extraction 
• Text Summarization 
• Sentiment, Intention, and Emotion Analysis – including tonality, subjectivity, emotional, empathetic concerns, personal distress, hate speech, and more. 

The unstructured user-generated content is transformed into shareable, actionable insights that enable everything from intelligent routing and escalation to formulating highly empathetic answers and identifying product issues. The result is better decision-making and information governance while freeing up precious resources and time. 

View the Text Mining infographic

Get the best insights to the right people, fast

Your customers are dropping clues as to how they’re feeling all the time. If you don’t have a way to pull these insights out of unstructured content and into the light, you’re literally leaving opportunities (and money) on the table.

Learn more about how you can bring customer insights out of the dark and into an actionable state.