Top Product Performance

Rank products by revenue, units sold, and refund rate over a date range by aggregating order line items.

shopify-admin-top-product-performance


Purpose

Ranks products by revenue, units sold, and refund rate for a given date range by aggregating order line items and refund line items across all orders in the period. Useful for identifying top performers and products with high refund rates. Read-only — no mutations are executed.


Prerequisites

  • Authenticated Shopify CLI session: shopify auth login --store
  • API scopes: read_orders

  • Parameters


    ParameterTypeRequiredDefaultDescription
    storestringyesStore domain (e.g., mystore.myshopify.com)
    formatstringnohumanOutput format: human or json
    dry_runboolnofalsePreview operations without executing mutations
    date_range_startstringyesStart date in ISO 8601 (e.g., 2025-01-01)
    date_range_endstringyesEnd date in ISO 8601 (e.g., 2025-01-31)
    top_nintegerno20Number of top products to show in the ranked output
    sort_bystringnorevenueRanking metric: revenue, units, or refund_rate

    Workflow Steps


  • OPERATION: orders — query
  • Inputs: first: 250, query: "created_at:>='' created_at:<=''", pagination cursor

    Expected output: All orders in range with line items (title, quantity, originalTotalSet, refundableQuantity) and refund line items; paginate until hasNextPage: false; aggregate in-memory per product: sum originalTotalSet for gross revenue, sum refund amounts for net revenue, sum quantities for units sold, compute refund rate


    GraphQL Operations


    # orders:query (for product revenue) — validated against api_version 2025-01
    query OrdersForProductPerformance($first: Int!, $after: String, $query: String) {
      orders(first: $first, after: $after, query: $query) {
        edges {
          node {
            id
            createdAt
            lineItems(first: 50) {
              edges {
                node {
                  title
                  quantity
                  variant {
                    id
                    sku
                    product {
                      id
                      title
                    }
                  }
                  originalTotalSet {
                    shopMoney { amount currencyCode }
                  }
                  refundableQuantity
                }
              }
            }
            refunds {
              refundLineItems(first: 50) {
                edges {
                  node {
                    quantity
                    lineItem {
                      variant {
                        id
                        product { id title }
                      }
                    }
                    subtotalSet {
                      shopMoney { amount currencyCode }
                    }
                  }
                }
              }
            }
          }
        }
        pageInfo {
          hasNextPage
          endCursor
        }
      }
    }
    

    Session Tracking


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


    On start, emit:

    ╔══════════════════════════════════════════════╗
    ║  SKILL: top-product-performance              ║
    ║  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):

    ══════════════════════════════════════════════
    OUTCOME SUMMARY
      Orders processed:   <n>
      Products ranked:    <n>
      Date range:         <start> to <end>
      Sort by:            <revenue|units|refund_rate>
      Errors:             0
      Output:             none
    ══════════════════════════════════════════════
    

    For format: json, emit:

    {
      "skill": "top-product-performance",
      "store": "<domain>",
      "started_at": "<ISO8601>",
      "completed_at": "<ISO8601>",
      "dry_run": false,
      "steps": [
        { "step": 1, "operation": "OrdersForProductPerformance", "type": "query", "params_summary": "<date_range_start> to <date_range_end>", "result_summary": "<n> orders processed", "skipped": false }
      ],
      "outcome": {
        "orders_processed": 0,
        "products_ranked": 0,
        "date_range_start": "<date_range_start>",
        "date_range_end": "<date_range_end>",
        "sort_by": "revenue",
        "results": [],
        "errors": 0,
        "output_file": null
      }
    }
    

    Output Format

    Ranked table displayed inline (no CSV), truncated to top_n entries:


    RankProductUnits SoldGross RevenueRefunded AmountNet RevenueRefund Rate %
    1..................

    For format: json, results is an array of objects with keys: rank, product_id, product_title, units_sold, gross_revenue, refunded_amount, net_revenue, refund_rate_pct.


    Error Handling

    ErrorCauseRecovery
    No orders returnedNo orders in date rangeWiden date range
    variant is null on a line itemProduct or variant was deletedStill aggregated by title; product_id will be null
    Rate limit (429)Too many paginated requestsNarrow date range

    Best Practices

  • For stores with many orders, use a 30-day window first. Wider windows paginate more aggressively and take longer.
  • sort_by: refund_rate highlights products with quality or expectation issues — a refund rate above 10% is worth investigating.
  • Revenue figures are gross (before refunds) and net (after refunds) — use net revenue for accurate profitability ranking.
  • Products that have been deleted will still appear if they were purchased in the date range — they show with product_id: null and their title from the order line item.
  • Combine with discount-ab-analysis to see which discount codes drove the most revenue for your top products.