Shopify Admin Discount Ab Analysis

Purpose

Compares how different discount codes perform against each other by redemption count and revenue generated. Useful for A/B testing promotional offers without a dedicated analytics app — provide two or more codes and a date range, and the skill queries Shopify for discount metadata and order revenue, then produces a side-by-side comparison table. Read-only: no mutations are executed.

Prerequisites

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

Parameters

| Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | store | string | yes | — | Store domain (e.g., mystore.myshopify.com) | | format | string | no | human | Output format: human or json | | dryrun | bool | no | false | Preview operations without executing mutations | | discountcodes | array | yes | — | Array of 2 or more discount code strings to compare (e.g., ["SAVE10", "WELCOME15"]) | | daterangestart | string | yes | — | Start date in ISO 8601 (e.g., 2025-01-01) | | daterangeend | string | yes | — | End date in ISO 8601 (e.g., 2025-01-31) |

Workflow Steps

1. OPERATION: discountNodes — query

Inputs: first: 50, query: "code:" (one query per code in discount_codes) Expected output: Discount metadata: title, code strings, asyncUsageCount, status, startsAt, endsAt per code

1. OPERATION: orders — query (one paginated query per discount code)

Inputs: first: 250, query: "discount_code: created_at:>='' created_at:'", pagination cursor Expected output: Orders containing the discount code with totalPriceSet; paginate until hasNextPage: false; aggregate: count, sum revenue, compute avg order value

GraphQL Operations

# discountNodes:query — validated against api_version 2025-01
query DiscountNodes($first: Int!, $query: String) {
  discountNodes(first: $first, query: $query) {
    edges {
      node {
        id
        discount {
          ... on DiscountCodeBasic {
            title
            codes(first: 10) {
              edges {
                node {
                  code
                  asyncUsageCount
                }
              }
            }
            usageLimit
            status
            startsAt
            endsAt
          }
          ... on DiscountCodeBxgy {
            title
            codes(first: 10) {
              edges {
                node {
                  code
                  asyncUsageCount
                }
              }
            }
            status
          }
          ... on DiscountCodeFreeShipping {
            title
            codes(first: 10) {
              edges {
                node {
                  code
                  asyncUsageCount
                }
              }
            }
            status
          }
        }
      }
    }
  }
}

# orders:query (by discount code) — validated against api_version 2025-01
query OrdersByDiscountCode($first: Int!, $after: String, $query: String) {
  orders(first: $first, after: $after, query: $query) {
    edges {
      node {
        id
        createdAt
        totalPriceSet {
          shopMoney { amount currencyCode }
        }
        discountCodes
      }
    }
    pageInfo {
      hasNextPage
      endCursor
    }
  }
}

Session Tracking

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

On start, emit:

╔══════════════════════════════════════════════╗
║  SKILL: discount-ab-analysis                 ║
║  Store:                        ║
║  Started:              ║
╚══════════════════════════════════════════════╝

After each step, emit:

[N/TOTAL]   
          → Params: 
          → Result: 

On completion, emit:

For format: human (default):

══════════════════════════════════════════════
OUTCOME SUMMARY
  Codes analyzed:   
  Date range:        to 
  Errors:           0
  Output:           none
══════════════════════════════════════════════

For format: json, emit:

{
  "skill": "discount-ab-analysis",
  "store": "",
  "started_at": "",
  "completed_at": "",
  "dry_run": false,
  "steps": [
    { "step": 1, "operation": "DiscountNodes", "type": "query", "params_summary": " codes queried", "result_summary": " discount nodes found", "skipped": false },
    { "step": 2, "operation": "OrdersByDiscountCode", "type": "query", "params_summary": "date range  to ", "result_summary": " orders aggregated", "skipped": false }
  ],
  "outcome": {
    "codes_analyzed": 0,
    "date_range_start": "",
    "date_range_end": "",
    "results": [
      {
        "code": "SAVE10",
        "async_usage_count": 0,
        "orders_in_range": 0,
        "total_revenue": "0.00",
        "avg_order_value": "0.00",
        "revenue_per_use": "0.00"
      }
    ],
    "errors": 0,
    "output_file": null
  }
}

Output Format

A comparison table per code (displayed inline):

| Code | Uses (asyncUsageCount) | Orders in Range | Total Revenue | Avg Order Value | Revenue per Use | |------|------------------------|-----------------|---------------|-----------------|-----------------| | SAVE10 | ... | ... | ... | ... | ... | | WELCOME15 | ... | ... | ... | ... | ... |

For format: json, the results array contains one object per code with keys: code, async_usage_count, orders_in_range, total_revenue, avg_order_value, revenue_per_use.

Error Handling

| Error | Cause | Recovery | |-------|-------|----------| | Discount code not found | Code doesn't exist or was deleted | Verify code in Shopify admin | | No orders returned for a code | No orders used this code in the date range | Widen date range or verify code was active | | discount_codes has fewer than 2 entries | Can't do A/B with 1 code | Provide at least 2 codes | | Rate limit (429) | Too many paginated orders queries | Wait and retry; reduce date range |

Best Practices

1. asyncUsageCount is the lifetime usage count from the discount object — orders_in_range is what was redeemed in your date window. Both are reported for full context.
2. For codes with high usage, the orders query will paginate — larger date ranges may produce many API calls. Consider narrowing the date range for faster results.
3. Revenue per use is the best signal for comparing codes with different usage volumes.
4. Run this analysis at the end of a campaign period before deciding which discount strategy to repeat.
5. If asyncUsageCount is 0 for a code, check that the code was active during the date range and correctly applied at checkout.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: 40RTY-ai
• Source: 40RTY-ai/shopify-admin-skills
• License: MIT
• Homepage: http://skills.40rty.ai

Install and usage instructions live in the source repository linked above.