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TEXT ANALYSIS SOFTWARE

You can't possibly read all of your customers' survey responses. Text iQ™ can.

Often, the most actionable insights are hidden deep in open text responses. Analysing them is painful. And at scale? It's impossible. Text iQ - Text Analytics powered by Qualtrics iQ instantly analyses open text so you can understand what, in your customers and employees own words, matters most.

Automatically uncover trends, problems, and opportunities. No manual tagging required.


  • Powerful machine learning and native language processing let iQ discover patterns and trends in open text.
  • Trending topics are automatically brought to the attention of the people that need to see them most.
  • Discovered topics are fully integrated into all Qualtrics reporting functions so they can be classified into topic hierarchies, filtered, analysed, and shared with ease. Plus, our text analysis tool now offers industry text topics to give you confidence in tracking the right topics from day one.

It's always listening—freeing you up for everything else.


Natural language processing automatically organises comments by topic and assigns sentiment scores to incoming open text feedback. In layman's terms: You'll know immediately which parts of your customer journey to focus on next.

Drive action to the frontline and monitor issues over time.


Text iQ automatically updates reports and dashboards for frontline employees, giving them the insights across all quantitative and qualitative data to make changes in the moment.

It's also monitoring key topics over time. Emerging topics are identified before they evolve into widespread issues—ensuring the changes you make become the results you expect.

Powerful text analytics in the palm of your hand.


Get full Text iQ features and functionality to analyse, filter, and share insights from your phone with the Qualtrics Mobile app. Download it today on the Apple App Store and Google Play.

Get more insight out of your open text feedback with Stats iQ


  • Get richer insights out of your text topics and sentiments by running statistical models using Stats iQ
  • Uncover richer insights from key topics and sentiment in your data.

Watch Text iQ Demo Video


What is text analysis?

Text analysis is a process which automatically extracts machine-readable information from unstructured text (or data) to uncover insights and support data-driven strategies.

Unstructured text (or data) can take the form of survey responses, emails, support tickets, call center notes, product reviews, social media posts, rich media, feedback and much more.

Text analytics uses advanced statistical techniques, automation and machine learning to analyze huge quantities of text-based data at scale.

This allows organisations to effectively understand open-text feedback at and surface the most important topics and challenges. For example, how customers feel about a certain product or service, or what marketing campaigns resonated the most.


Learn more about text analysis

Frequently asked questions


Text analytics combines artificial intelligence and statistical techniques to automatically process large volumes of unstructured text and uncover insights from it.

Though text analytics and text mining are often used interchangeably, text mining involves the use of statistical techniques to retrieve quantifiable data for further applications.

Text analytics, however, is more about business intelligence: it enhances the data to draw patterns, insights, sentiment and trends for customer or employee experience programs.
Organisations, researchers and individuals can use text analysis tools to derive insights and patterns from unstructured data. For example, they can use sentiment analysis to uncover how respondents feel about a product feature, or topic modeling to identify customers' most common challenges or pain points.

With this data, they can then make informed decisions on business, market or product strategy. Text analytics focuses on insights discovery to help drive action within specialised fields like experience management.