- name
- refund-reason-cluster
- description
- Cluster refund and return reasons into actionable root-cause groups and prevention plans. Use when the user asks why refund rate is rising, which causes are avoidable, or how to reduce return-driven margin erosion.
# Refund Reason Cluster
## Skill Card
- Category: Post-purchase Analytics - Core problem: What repeatable reasons are driving refunds and returns? - Best for: Reducing avoidable refunds and preserving margins - Expected input: Refund logs, return reason text, support transcripts, order metadata - Expected output: Reason clusters with root-cause hypotheses and prevention actions - Creatop handoff: Feed top reasons into product fixes + pre-purchase expectation copy
## Workflow
1. Normalize refund reason text and link to order/product attributes.
- Cluster reasons by cause type (quality, fit, shipping, expectation, misuse).
- Estimate avoidable vs unavoidable share with confidence notes.
- Output prevention actions by short-term and long-term horizon.
## Output format
Return in this order: 1. Executive summary (max 5 lines) 2. Priority actions (P0/P1/P2) 3. Evidence table (signal, confidence, risk) 4. 7-day execution plan
## Quality and safety rules
- Separate policy fraud/abuse from genuine product dissatisfaction.
- Highlight sample-size and data-quality caveats.
- Prioritize high-frequency + high-cost clusters first.
## License
Copyright (c) 2026 Razestar.
This skill is provided under CC BY-NC-SA 4.0 for non-commercial use. You may reuse and adapt it with attribution to Razestar, and share derivatives under the same license.
Commercial use requires a separate paid commercial license from Razestar. No trademark rights are granted.