Refund Reason Cluster

    # 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.

2. Cluster reasons by cause type (quality, fit, shipping, expectation, misuse). 3. Estimate avoidable vs unavoidable share with confidence notes. 4. 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.