---
name: shopify-admin-subscription-mrr-tracker
role: finance
description: "Read-only: for stores with subscription products, calculates MRR, ARR, active subscriber count, and rolling churn rate from subscription contracts."
toolkit: shopify-admin, shopify-admin-execution
api_version: "2025-01"
graphql_operations:
  - subscriptionContracts:query
status: stable
compatibility: Claude Code, Cursor, Codex, Gemini CLI
---

## Purpose
For stores selling subscription products via Shopify's native subscriptions, this skill aggregates active subscription contracts into the standard SaaS-style metrics finance teams care about: monthly recurring revenue (MRR), annualized recurring revenue (ARR), active subscriber count, average revenue per subscriber (ARPU), and a rolling churn rate. Read-only — no mutations.

## Prerequisites
- Authenticated Shopify CLI session: `shopify store auth --store <domain> --scopes read_own_subscription_contracts`
- API scopes: `read_own_subscription_contracts`

## Parameters

| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| store | string | yes | — | Store domain (e.g., mystore.myshopify.com) |
| churn_window_days | integer | no | 30 | Rolling window for churn calculation (cancellations / starting subscribers) |
| as_of | string | no | today (UTC) | ISO date for "as of" snapshot label |
| include_paused | bool | no | false | Treat `PAUSED` contracts as active recurring revenue |
| format | string | no | human | Output format: `human` or `json` |

## Safety

> ℹ️ Read-only skill — no mutations are executed. **This skill is only meaningful if the store sells subscription products.** If `subscriptionContracts` returns 0 contracts, the report exits with $0 MRR — that is the correct answer, not an error.

## Recurring Revenue Model

For each subscription contract, the contribution to MRR depends on its billing interval:

```
billing_amount = sum(line.currentPrice × line.quantity) for each line in contract
mrr_contribution =
  billing_amount                       if interval = MONTH and intervalCount = 1
  billing_amount / intervalCount       if interval = MONTH (e.g., every 3 months → /3)
  billing_amount × 4.345               if interval = WEEK (avg weeks per month)
  billing_amount × 4.345 / intervalCount if interval = WEEK with intervalCount > 1
  billing_amount / 12                  if interval = YEAR
  billing_amount × 30 / intervalCount  if interval = DAY
```

Aggregations:
- **MRR** = Σ mrr_contribution for all `ACTIVE` (and `PAUSED` if `include_paused`) contracts
- **ARR** = MRR × 12
- **Active subscribers** = unique `customer.id` count
- **ARPU** = MRR / active subscribers
- **Churn rate (period)** = contracts cancelled inside `churn_window_days` ÷ contracts that were active at the start of the window
- **Net new subscribers** = new contracts inside the window − cancelled contracts inside the window

## Workflow Steps

1. **OPERATION:** `subscriptionContracts` — query
   **Inputs:** `first: 250`, select `id`, `status`, `createdAt`, `updatedAt`, `nextBillingDate`, `customer { id, displayName }`, `currencyCode`, `billingPolicy { interval, intervalCount }`, `lines { edges { node { currentPrice { amount, currencyCode }, quantity, productId, variantId, title } } }`, pagination cursor
   **Expected output:** All subscription contracts; paginate until `hasNextPage: false`

2. Classify each contract by status: `ACTIVE`, `PAUSED`, `CANCELLED`, `EXPIRED`, `FAILED`

3. Compute `mrr_contribution` for each active (and paused if requested) contract using the model above

4. Aggregate MRR / ARR / subscribers / ARPU

5. For churn: count cancellations where `updatedAt` is within `churn_window_days` and status moved to `CANCELLED`; count contracts that existed and were `ACTIVE` at `as_of - churn_window_days`

6. Build a per-product breakdown so finance can see which subscription SKUs drive MRR

## GraphQL Operations

```graphql
# subscriptionContracts:query — validated against api_version 2025-01
query SubscriptionMRR($after: String) {
  subscriptionContracts(first: 250, after: $after) {
    edges {
      node {
        id
        status
        createdAt
        updatedAt
        nextBillingDate
        currencyCode
        customer {
          id
          displayName
          defaultEmailAddress { emailAddress }
        }
        billingPolicy { interval intervalCount minCycles maxCycles }
        deliveryPolicy { interval intervalCount }
        lines(first: 50) {
          edges {
            node {
              id
              productId
              variantId
              title
              quantity
              currentPrice { amount currencyCode }
            }
          }
        }
      }
    }
    pageInfo { hasNextPage endCursor }
  }
}
```

## Session Tracking

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

**On start**, emit:
```
╔══════════════════════════════════════════════╗
║  SKILL: Subscription MRR Tracker             ║
║  Store: <store domain>                       ║
║  As of: <YYYY-MM-DD>                         ║
║  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):
```
══════════════════════════════════════════════
SUBSCRIPTION MRR REPORT  (as of <date>)
  Active contracts:        <n>
  Paused contracts:        <n>
  Cancelled (last <n>d):   <n>
  ─────────────────────────────
  MRR:                     $<amount>
  ARR:                     $<amount>
  Active subscribers:      <n>
  ARPU:                    $<amount>
  Churn rate (<n>d):       <pct>%
  Net new (<n>d):          <n>

  Top subscription products by MRR:
    "<title>"   Subs: <n>   MRR: $<n>
    "<title>"   Subs: <n>   MRR: $<n>

  Output: subscription_mrr_<date>.csv
══════════════════════════════════════════════
```

For `format: json`, emit:
```json
{
  "skill": "subscription-mrr-tracker",
  "store": "<domain>",
  "as_of": "<YYYY-MM-DD>",
  "active_contracts": 0,
  "paused_contracts": 0,
  "cancelled_in_window": 0,
  "mrr": 0,
  "arr": 0,
  "active_subscribers": 0,
  "arpu": 0,
  "churn_rate_pct": 0,
  "net_new": 0,
  "currency": "USD",
  "by_product": [],
  "output_file": "subscription_mrr_<date>.csv"
}
```

## Output Format
CSV file `subscription_mrr_<YYYY-MM-DD>.csv` with columns:
`contract_id`, `status`, `customer_id`, `customer_email`, `created_at`, `next_billing_date`, `interval`, `interval_count`, `billing_amount`, `mrr_contribution`, `currency`, `product_titles`

## Error Handling
| Error | Cause | Recovery |
|-------|-------|----------|
| `THROTTLED` | API rate limit exceeded | Wait 2 seconds, retry up to 3 times |
| `subscriptionContracts` empty | Store has no subscription products | Exit cleanly — report $0 MRR; this is the correct value, not an error |
| Multi-currency contracts | Different `currencyCode` per contract | Group MRR per currency; do not sum across currencies — surface separately in output |
| Pre-paid contracts (`maxCycles` set) | Customer paid upfront for N cycles | Still contributes to MRR while ACTIVE, but the contract will end after `maxCycles`; flag in output |

## Best Practices
- This skill is only meaningful if the store actually sells subscription products. If you don't run subscriptions, MRR will be $0 — that's correct.
- Run on the **first day of every month** so MRR snapshots align with finance's monthly close cadence.
- Track MRR week-over-week to catch payment-failure spikes early — `FAILED` contracts that don't recover become churn within 30 days.
- Pre-paid annual subscriptions inflate ARR without inflating cash flow in any given month — keep them separate when reporting to investors who want a cash-flow view.
- Pair with `churn-risk-scorer` (transactional churn) to triangulate subscription churn vs. one-time-purchase churn — they deserve separate retention strategies.
- Multi-currency stores: report MRR per currency; converting via spot FX rates produces a misleading number that fluctuates with exchange rates rather than business performance.