Feedback reason taxonomy for denied and corrected cards
- Baseline
- 49%
- Final
- 81%
- Delta
- +32 pts
- Variants
- 4
What we set out to improve
Map free-text denial and correction feedback into a closed reason taxonomy the loop can learn from, without surfacing the raw feedback text.
Kept. An eight-class taxonomy with a confidence gate classified denial and correction reasons at 0.81 accuracy, turning free-text feedback into structured, learnable signal. Only the closed-enum reason classes are stored; raw feedback text is never retained.
Variants we tried
Each variant and its coarse objective metric. The kept variant is marked; bars are relative to the best run.
- 1Baseline — uncategorized free-text reasonsLow49%
- 2Variant A — six-class taxonomyMedium68%
- 3Variant B — eight-class taxonomyMedium76%
- 4Variant C — eight-class + confidence gateWinnerMedium81%
Stages
baseline
Succeeded · 2.4s
variant run
Succeeded · 8.8s
eval
Succeeded · 1.2s
promote
Succeeded · 300ms
Artifacts and what shipped
Redaction-safe artifact previews, diffs, metric tables, and prompt variants with sensitive text removed.
- Metric table
Reason-classification accuracy by variant (0.49 → 0.81)
- Report
Taxonomy coverage report (closed-enum labels only)
- KB write
Stored the reason taxonomy in the platform learning KB