---

name: revenue-data-validator description: Identifies and filters test/dummy revenue data from real customer transactions across all revenue streams (affiliates, gallery, subscriptions).

Revenue Data Validator Skill

This skill helps identify test/dummy data vs. real customer revenue across the platform.

Problem Statement

The platform currently shows inflated revenue numbers because test data exists in:

• Affiliates table: Test earnings showing $9,609.49
• Photo orders: Test gallery purchases
• Subscriptions: Admin account subscription ($9.99/month)

Current Reality: $0 in actual revenue, but dashboard shows thousands in test data.

Solution: Revenue Validation Rules

1. Affiliate Revenue Validation

Test Data Indicators:

• Earnings created before official launch date
• Affiliate accounts with test/dummy email patterns (e.g., test@, admin@, demo@)
• Round number earnings (e.g., $100.00, $500.00, $1000.00)
• Earnings without corresponding click/conversion records
• Affiliate IDs that match known test accounts

SQL to Identify Test Affiliates:

-- Find test affiliate accounts
SELECT id, email, total_earnings, created_at
FROM affiliates
WHERE 
  email LIKE '%test%' 
  OR email LIKE '%demo%'
  OR email LIKE '%admin%'
  OR total_earnings::numeric % 100 = 0  -- Round numbers
  OR created_at < '2026-01-01'  -- Before launch
ORDER BY total_earnings DESC;

SQL to Get Real Affiliate Revenue:

-- Get only real affiliate revenue
SELECT COALESCE(SUM(total_earnings), 0) as real_revenue
FROM affiliates
WHERE 
  email NOT LIKE '%test%' 
  AND email NOT LIKE '%demo%'
  AND email NOT LIKE '%admin%'
  AND created_at >= '2026-01-01'  -- Adjust to actual launch date
  AND total_earnings > 0;

2. Gallery Revenue Validation

Test Data Indicators:

• Orders from test email addresses
• Orders created during development/testing phase
• Orders with test payment IDs (PayPal sandbox transactions)
• Orders from admin/developer accounts

SQL to Identify Test Gallery Orders:

-- Find test photo orders
SELECT id, email, total_amount_cents, payment_status, created_at
FROM photo_orders
WHERE 
  email LIKE '%test%'
  OR email LIKE '%demo%'
  OR email LIKE '%admin%'
  OR created_at < '2026-01-01'  -- Before launch
ORDER BY total_amount_cents DESC;

SQL to Get Real Gallery Revenue:

-- Get only real gallery revenue (in dollars)
SELECT COALESCE(SUM(total_amount_cents), 0) / 100.0 as real_revenue
FROM photo_orders
WHERE 
  email NOT LIKE '%test%'
  AND email NOT LIKE '%demo%'
  AND email NOT LIKE '%admin%'
  AND created_at >= '2026-01-01'  -- Adjust to actual launch date
  AND payment_status = 'completed';

3. Subscription Revenue Validation

Test Data Indicators:

• Admin account subscriptions
• Test user subscriptions
• Subscriptions created during development

SQL to Identify Test Subscriptions:

-- Find test subscriptions
SELECT ps.id, ps.user_id, u.email, ps.tier, ps.created_at
FROM platform_subscriptions ps
JOIN auth.users u ON u.id = ps.user_id
WHERE 
  u.email LIKE '%test%'
  OR u.email LIKE '%demo%'
  OR u.email LIKE '%admin%'
  OR ps.created_at < '2026-01-01'  -- Before launch
ORDER BY ps.created_at DESC;

Implementation in Dashboard

Update Admin.tsx Revenue Calculation

Add a launch date constant and filter logic:

// Add at top of file
const PLATFORM_LAUNCH_DATE = '2026-01-15'; // Adjust to actual launch date

// In the revenue calculation section:
const isTestEmail = (email: string) => {
  const testPatterns = ['test', 'demo', 'admin', 'dev', 'staging'];
  return testPatterns.some(pattern => 
    email?.toLowerCase().includes(pattern)
  );
};

// Filter affiliates
if (affiliates) {
  affiliateRevenueTotal = affiliates
    .filter(a => {
      // Add email field to the select query first
      return !isTestEmail(a.email) && 
             new Date(a.created_at) >= new Date(PLATFORM_LAUNCH_DATE);
    })
    .reduce((sum, a) => {
      const earnings = typeof a.total_earnings === 'string' 
        ? parseFloat(a.total_earnings) 
        : (a.total_earnings || 0);
      return sum + (isNaN(earnings) ? 0 : earnings);
    }, 0);
}

// Filter gallery orders
if (orders) {
  galleryRevenueTotal = orders
    .filter(o => {
      // Add email field to the select query first
      return !isTestEmail(o.email) && 
             new Date(o.created_at) >= new Date(PLATFORM_LAUNCH_DATE) &&
             o.payment_status === 'completed';
    })
    .reduce((sum, o) => sum + (o.total_amount_cents || 0), 0) / 100;
}

Update Supabase Queries

Modify the queries to include email and created_at fields:

// Affiliate query
const { data: affiliates, error: affError } = await supabase
  .from('affiliates')
  .select('total_earnings, email, created_at');

// Gallery orders query
const { data: orders, error: ordersError } = await supabase
  .from('photo_orders')
  .select('total_amount_cents, email, created_at, payment_status');

Quick Cleanup Commands

Option 1: Mark Test Data (Recommended)

Add a is_test_data boolean column to track test records:

-- Add column to affiliates
ALTER TABLE affiliates ADD COLUMN IF NOT EXISTS is_test_data BOOLEAN DEFAULT false;

-- Mark test affiliates
UPDATE affiliates 
SET is_test_data = true
WHERE 
  email LIKE '%test%' 
  OR email LIKE '%demo%'
  OR email LIKE '%admin%'
  OR created_at < '2026-01-01';

-- Add column to photo_orders
ALTER TABLE photo_orders ADD COLUMN IF NOT EXISTS is_test_data BOOLEAN DEFAULT false;

-- Mark test orders
UPDATE photo_orders 
SET is_test_data = true
WHERE 
  email LIKE '%test%'
  OR email LIKE '%demo%'
  OR email LIKE '%admin%'
  OR created_at < '2026-01-01';

Then filter in queries:

.eq('is_test_data', false)

Option 2: Delete Test Data (Use with Caution)

-- BACKUP FIRST!
-- Delete test affiliate data
DELETE FROM affiliates 
WHERE 
  email LIKE '%test%' 
  OR email LIKE '%demo%'
  OR email LIKE '%admin%';

-- Delete test gallery orders
DELETE FROM photo_orders 
WHERE 
  email LIKE '%test%'
  OR email LIKE '%demo%'
  OR email LIKE '%admin%';

Monitoring & Alerts

Add alerts when test data is detected:

// In Admin.tsx alerts generation
if (affiliateRevenueTotal > 0) {
  // Check if any test data exists
  const hasTestData = affiliates?.some(a => isTestEmail(a.email));
  if (hasTestData) {
    newAlerts.push({
      id: Date.now() + 100,
      type: 'warning',
      message: 'Test affiliate data detected - revenue may be inflated',
      time: 'Just now',
      read: false
    });
  }
}

Best Practices

1. Always use launch date filtering - Set PLATFORM_LAUNCH_DATE to when you actually started accepting real customers
2. Mark, don't delete - Use is_test_data flag instead of deleting test records (useful for debugging)
3. Email pattern matching - Maintain a list of test email patterns
4. Regular audits - Periodically check for new test data that slipped through
5. Separate test environment - Use different Supabase projects for dev/staging/production

Current Action Items

1. ✅ Set PLATFORM_LAUNCH_DATE = '2026-01-15' (or actual launch date)
2. ✅ Update affiliate query to include email, created_at
3. ✅ Update gallery query to include email, created_at, payment_status
4. ✅ Add isTestEmail() helper function
5. ✅ Add filtering logic to revenue calculations
6. ⏳ Run SQL to mark test data with is_test_data = true
7. ⏳ Verify dashboard shows $0.00 for all revenue streams