Glaut Intelligence vs Displayr: which tool keeps the researcher in the analysis?
Glaut Intelligence and Displayr both handle open-end coding and crosstab generation for quantitative market research. They solve different problems for different people, and the difference matters most at the moment the field closes, and the clock starts.
Side by side
|
Glaut Intelligence |
Displayr |
| Built for |
The researcher who owns the brief |
Data analysts and DP specialists |
| Starting point |
The brief — analysis plan proposed based on research context |
The data — imported from your survey tool |
| Analysis plan |
AI proposes full plan (open-ends, question transformations, weighting) based on your brief; you review and approve each step |
No brief-driven analysis plan; you configure analysis manually from the data |
| Open-end coding |
AI proposes code frame; you review theme-by-theme on the verbatim and approve before anything is applied |
AI auto-identifies themes; you fine-tune after generation |
| Crosstabs |
Generated in a few clicks; first observations surfaced automatically |
Full crosstab suite with statistical testing, significance flags, and banner points |
| Question transformations |
Recode scales, collapse categories, create derived variables inside the platform |
Data cleaning and recoding available within Displayr |
| Weighting |
Included in the analysis plan pipeline |
Available |
| Statistical depth |
Core quant analysis pipeline — coding, transformations, crosstabs, findings |
Extensive: MaxDiff, conjoint, TURF, factor analysis, driver analysis, regression, cluster analysis |
| Findings layer |
AI drafts findings from validated data; each finding traceable back to the data; you accept, rewrite, or discard |
AI can summarize tables and generate recommendations; output oriented toward reporting |
| Reporting output |
PPT export of charts, analysis, and findings — ready to copy-paste into your own deck |
PowerPoint automation with live-updating, template-driven reports; dashboards and data apps |
| Environment |
Survey data analyzed inside Glaut — same platform as the brief context |
Standalone analysis platform; data imported from survey tools |
The core difference
- Displayr is centered on data. Displayr AI analyzes open-ended responses to identify key themes automatically and allows you to group related ideas and refine themes. It’s a powerful tool, but it lacks awareness of a brief. It doesn’t understand why the study was conducted, the hypotheses the client had at the start, or the underlying business questions behind the research. This context resides in the researcher’s mind and doesn’t accompany the data when it moves into a dedicated analysis platform.
- Glaut Intelligence begins with the brief. The analysis plan is developed based on the research context, not solely on the data structure. The researcher who created the questionnaire and participated in the briefing remains involved in the analysis until the final output. Coding is performed on the verbatim for review. The findings are editable and can be traced back. At each stage, the model offers suggestions, but the researcher has the final say. No process proceeds without approval.
The main difference in workflow appears during the debrief. When a DP specialist runs the tables in a separate tool and provides the output, the researcher then presents findings based on someone else’s analysis. With Glaut Intelligence, however, the researcher who understands the business question has built every part of the answer and can explain the reasoning behind any finding directly to the client.
When Displayr is the right choice
Displayr is the stronger option when:
When Glaut Intelligence is the right choice
Glaut Intelligence is the stronger option when:
- The researcher who owns the brief needs to own the full process to build the final storytelling and report for the end-client, not review someone else's output after the fact.
- Your team doesn't have a dedicated DP specialist and the researcher currently hands off to a colleague who wasn't in the briefing, or to an external DP house.
- You want an analysis plan that starts from the research question rather than from manually configuring the data.
- Traceability matters: every finding needs a clear path back to the verbatims and the data that generated it.
- The final output is a researcher-built deck: charts, analysis, and findings exported to PPT and dropped into your own presentation, with the judgment and framing entirely yours.
The briefing question
The simplest way to choose: does the tool know what the brief was?
- Displayr is a powerful analysis environment. It processes your data well. It doesn't know your brief, your hypotheses, or why the questionnaire was designed the way it was.
- Glaut Intelligence is built for the researcher who needs both in the same place, and who can't afford to lose the context behind the research question at the moment the analysis begins.
See how Glaut Intelligence handles the full pipeline from brief to findings.
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