Open-end coding at scale
Thousands of open-ended answers coded automatically, replacing manual coding cycles and crossing directly with the quant data.
AI Text Analysis
ezSummary · Qualitative Synthesis
Turns transcripts, open ends and qual material into structured, reportable results that connect with quant — opinions quantified, verbatims traceable, insight compounding.
86–92%AI parsing accuracy in delivered VOC work
1次投入invest once, reuse everywhere
Core capabilities
What ezSummary does
- 01
Opinion quantification
Extracts and counts opinions precisely, so qualitative material finally supports proportions and crosstabs like quant data.
- 02
Comparative analysis
Cohort comparison, merged-question synthesis and wave-over-wave analysis, all from one structured base.
- 03
Compounding insight assets
Delivered online for cross-project integration — every study makes the next one faster and sharper.
- 04
Auditable human-AI workflow
Every AI tag and cluster is visible and auditable line by line, with researcher corrections built in — accuracy verified, not claimed.
In the field (anonymized)
How teams use it
Transcript structuring
Interviews from ezChat, ezSee and ezTalk structure into an opinion library that powers reporting and later re-mining.
FAQ
Frequently asked
How is coding accuracy assured?
Delivered VOC projects run at 86–92% parsing accuracy (industry norm ~60%). Every tag is auditable line by line with researcher corrections, so accuracy is continuously verified in production.
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