Open-ended responses
Understand opinions. Gain deeper insights.
Open responses reveal what matters to people, how they experience products and brands, and the reasons behind their ratings. With Cauliflower, you can explore these qualitative insights even in large volumes of text: identify themes and relationships, compare the perspectives of different target groups and delve into your analysis down to the original statement.
Understand what lies behind a rating.
Which experiences shape opinions about a product? What excites one target group, and what concerns another? Combine topic frequencies with sentiment, summaries and original statements. This helps you recognise the different experiences and reasons behind the results.
How Cauliflower solves it
Create or adopt a coding frame
The AI develops a coding frame from the responses or works with an existing uploaded coding frame.
Structure responses automatically
Verbatims are assigned to relevant aspects and aspect categories and can be coded multiple times.
Interpret content
Cauliflower determines sentiment for each aspect and creates summaries for topics, target groups, and subsamples.
Prioritise drivers
Shapley-based analyses and Kruskal–Wallis tests show which aspects are associated with satisfaction, NPS, or other available KPIs.
All assignments remain editable and can be traced back to the respective original response.
Which names stay top of mind?
Analyse unaided mentions of brands, car models or names of brand endorsers. Cauliflower groups mentions into categories for analysis. With Top of Mind, you can also see which name was mentioned first. Compare results by target group, country or survey wave.
Modules used
From individual statements to a structured overall picture
Unstructured feedback becomes a traceable analysis that connects quantitative frequencies, qualitative relationships, and specific original statements.
A complete picture that preserves individual voices.
Connect the overview of topics and target groups with the specific statements behind them. Use the results to develop new questions, interpret differences and support your recommendations with traceable insights.
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