Open-ended responses
Thousands of voices. Structured in minutes.
Cauliflower codes open-ended responses, assigns them to aspects and aspect categories, and connects qualitative content with quantitative results. The coding frame, sentiment, summaries, and driver analyses remain reviewable and editable at all times.
The problem
Manually reading and coding thousands of open-ended responses takes days or weeks. At the same time, codes must be applied consistently, multiple mentions must be taken into account, and results must remain traceable back to the original verbatim.
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.
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.
Days become minutes.
Analyse open-ended responses without giving up traceability or control. From the coding frame to the driver analysis, every step remains reviewable and editable.
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