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Documentation Index

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Segments let you split your participant data into groups and compare their responses side by side — answering questions like “Do customers and non-customers feel differently about this?” or “How do US and UK participants compare?”

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What Are Segments?

A segment is any subgroup of participants defined by a shared characteristic. That characteristic can be a screener answer, a demographic attribute, a URL parameter, or any combination of these. Once you define your segments, Listen filters the analysis for each group and displays them in parallel so you can spot differences immediately.

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Creating Segments

To set up segments, go to the Analysis tab, click Segments in the filter panel, and click Add Segment. From there, define your criteria using any of the following:
  • A screener question and its qualifying answer(s)
  • A demographic attribute such as age range, country, or gender
  • A URL parameter value (for example, group=US)
Give your segment a clear name — something like “Current Customers,” “Ages 18–34,” or “US Market” — and repeat the process for each comparison group you need.

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Using Segments in Analysis

Once defined, every view in the Details tab updates to show analysis side by side for each segment. You can compare theme frequency to see whether one group mentions a topic more than another, sentiment and emotional tone across groups, average ratings and quantitative scores broken down by segment, and verbatim quotes filtered to each group. You can also ask Research Agent to run segment-level comparisons directly. Try prompts like “Compare responses between our US and UK segments” or “What are the top differences between customers and non-customers?”

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Common Use Cases

  • Market comparison — Compare reactions across countries in a single study. Combine segments with Listen’s translation features to analyze all markets together rather than running separate studies per country.
  • Customer vs. non-customer — See whether familiarity with your product changes perceptions, expectations, or emotional reactions.
  • Demographic analysis — Compare responses across age groups, genders, or income brackets to understand how different audiences experience the same content.
  • Concept assignment — Compare how participants who saw Concept A responded versus those who saw Concept B, with statistical significance testing built in.
For multi-market studies, combine segments with Listen’s translation features to analyze all markets in one study rather than running separate studies per country.