refund-rate-analysis

Purpose

Analyzes orders with refunds to calculate refund rates by product, time period, and channel. Surfaces which products or product groups generate the most refund activity. Read-only — no mutations.

Prerequisites

• Authenticated Shopify CLI session: shopify store auth --store <domain> --scopes read_orders
• API scopes: read_orders

Parameters

Parameter	Type	Required	Default	Description
store	string	yes	—	Store domain (e.g., mystore.myshopify.com)
days_back	integer	no	30	Lookback window
group_by	string	no	product	Breakdown: product, vendor, or period
min_orders	integer	no	5	Minimum orders per group to include in rate calculation
format	string	no	human	Output format: human or json

Safety

ℹ️ Read-only skill — no mutations are executed. Safe to run at any time.

Workflow Steps

1. OPERATION: orders — query Inputs: query: "created_at:>='<NOW - days_back days>'", first: 250, select refunds { refundLineItems }, lineItems, pagination cursor Expected output: All orders with refund data; paginate until hasNextPage: false

2. For each refunded line item: record product, vendor, quantity refunded, refund amount

3. Aggregate by group_by: calculate refund_rate = refunded_units / total_units_sold × 100

GraphQL Operations

# orders:query — validated against api_version 2025-01
query OrdersWithRefunds($query: String!, $after: String) {
  orders(first: 250, after: $after, query: $query) {
    edges {
      node {
        id
        name
        createdAt
        lineItems(first: 50) {
          edges {
            node {
              id
              quantity
              product {
                id
                title
                vendor
              }
              variant {
                id
                sku
              }
            }
          }
        }
        refunds {
          id
          createdAt
          totalRefundedSet {
            shopMoney {
              amount
              currencyCode
            }
          }
          refundLineItems(first: 50) {
            edges {
              node {
                quantity
                lineItem {
                  product {
                    id
                    title
                    vendor
                  }
                  variant {
                    id
                    sku
                  }
                }
              }
            }
          }
        }
      }
    }
    pageInfo {
      hasNextPage
      endCursor
    }
  }
}

Session Tracking

Claude MUST emit the following output at each stage. This is mandatory.

On start, emit:

╔══════════════════════════════════════════════╗
║  SKILL: Refund Rate Analysis                 ║
║  Store: <store domain>                       ║
║  Started: <YYYY-MM-DD HH:MM UTC>             ║
╚══════════════════════════════════════════════╝

After each step, emit:

[N/TOTAL] <QUERY|MUTATION>  <OperationName>
          → Params: <brief summary of key inputs>
          → Result: <count or outcome>

On completion, emit:

For format: human (default):

══════════════════════════════════════════════
REFUND RATE ANALYSIS  (<days_back> days)
  Orders analyzed:       <n>
  Orders with refunds:   <n>
  Overall refund rate:   <pct>%
  Total refunded:        $<amount>

  By <group_by>:
    "<name>"   Sold: <n>  Refunded: <n>  Rate: <pct>%
  Output: refund_rate_<date>.csv
══════════════════════════════════════════════

For format: json, emit:

{
  "skill": "refund-rate-analysis",
  "store": "<domain>",
  "period_days": 30,
  "orders_analyzed": 0,
  "orders_with_refunds": 0,
  "overall_refund_rate_pct": 0,
  "total_refunded": 0,
  "currency": "USD",
  "output_file": "refund_rate_<date>.csv"
}

Output Format

CSV file refund_rate_<YYYY-MM-DD>.csv with columns: group, group_name, total_units_sold, refunded_units, refund_rate_pct, total_refund_amount, currency

Error Handling

Error	Cause	Recovery
THROTTLED	API rate limit exceeded	Wait 2 seconds, retry up to 3 times
No refunds in window	Clean period	Exit with 0% rate, expected
Deleted product on refund line	Product removed after refund	Log as "deleted product" in group

Best Practices

• A refund rate above 5–10% on specific products typically signals a listing, quality, or expectation mismatch issue.
• Use group_by: vendor to identify if quality problems are concentrated with a specific supplier.
• Cross-reference high-refund products with return-reason-analysis to understand whether the issue is product quality, wrong size, or customer expectation.
• Run before quarterly supplier reviews to support data-driven conversations about product quality and chargebacks.