Analyze survey text and discover valuable insights


IBM SPSS Text Analytics for Surveys software enables you to transform unstructured survey text into quantitative data and gain insight using sentiment analysis. It uses natural language processing (NLP) technologies specifically designed for survey text. The solution categorizes responses and integrates results with other survey data for better insight and statistical analysis.

Efficient way to make text responses count

This solution is an ideal tool for categorizing text responses and quantifying customer, employee or student satisfaction, so you can integrate the new results for analysis with the rest of your data.

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Automates the categorization process

Eliminate the time and expense of manual coding, and get faster results

Uses linguistics-based technologies

Reduce the ambiguities of human language, and uncover patterns in the attitudes, beliefs and opinions of others

Easy to use and control

Benefit from a setup wizard and visualization features to help you see and manually refine categories, rules or results


Explore detailed information about this product, its uses and how it can help your business.

See how it works

Check out this demonstration of IBM SPSS Text Analytics for Surveys to help you get up and running quickly.

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Easily make your survey text responses usable in quantitative analysis.

Read how you can quantify text responses for analysis along with other survey data—thoroughly, reliably and quickly.

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Features Spotlight

  • Automated categorization and reuse
  • Visualisation and collaboration
  • NLP features
  • Data management


Streamlines the data preparation process so that you can get ready for analysis faster and reach more accurate conclusions

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Quickly develop reliable forecasts and predict trends using time-series data

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Powerful modeling techniques for analysing complex relationships

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Uncover data patterns, gain predictive accuracy and improve decision making

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Interested to find out how analytics can help you achieve your goals?
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