CX Dictionary

What is Text Analytics?

Text analytics is the process of drawing meaning out of written communication.

In a customer experience context, text analytics means examining text that was written by, or about, customers. You find patterns and topics of interest, and then take practical action based on what you learn.

Text analytics can be performed manually, but it is an inefficient process. Therefore, text analytics software has been created that uses text mining and natural language processing algorithms to find meaning in huge amounts of text.

Why do you need text analytics?

Emails, online reviews, tweets, call center agent notes, survey results, and other types of written feedback all hold insight into your customers. There is also a wealth of information in recorded interactions that can easily be turned into text.

Text analytics is the way to unlock the meaning from all of this unstructured text. It lets you uncover patterns and themes, so you know what customers are thinking about. It reveals their wants and needs.

In addition, text analytics software can provide an early warning of trouble, because it shows what customers are complaining about. Using text analytics tools gives you valuable information from data that isn’t easily quantified in any other way. It turns the unstructured thoughts of customers into structured data that can be used by business.

Clarabridge's Proprietary Text Analysis

Clarabridge understands text analytics. We pioneered the use of text analytics tools for customer experience management. Clarabridge was identified as a leader in The Forrester WaveTM: Big Data Text Analytics Platforms, Q2 2016. In fact, we were the only customer experience management vendor included in the report.

Clarabridge’s text analytics tools are unique in a number of ways, including patented algorithms and proprietary Natural Language Processing.

Understanding your customers is the foundation of any successful customer experience management program. Text analytics provides an in-depth look into what your customers saying, in their own words.