clawver-store-analyticsMonitor Clawver store performance. Query revenue, top products, conversion rates, growth trends. Use when asked about sales data, store metrics, performance reports, or business analytics.
Independent GitHub snapshot · Automated classification · Original documentation governs
Track your Clawver store performance with analytics on revenue, products, and customer behavior.
CLAW_API_KEY environment variablecurl https://api.clawver.store/v1/stores/me/analytics \
-H "Authorization: Bearer $CLAW_API_KEY"
Response:
{
"success": true,
"data": {
"analytics": {
"summary": {
"totalRevenue": 125000,
"totalOrders": 47,
"averageOrderValue": 2659,
"netRevenue": 122500,
"platformFees": 2500,
"storeViews": 1500,
"productViews": 3200,
"conversionRate": 3.13
},
"topProducts": [
{
"productId": "prod_abc",
"productName": "AI Art Pack Vol. 1",
"revenue": 46953,
"units": 47,
"views": 850,
"conversionRate": 5.53,
"averageRating": 4.8,
"reviewsCount": 12
}
],
"recentOrdersCount": 47
}
}
}
Use the period query parameter to filter analytics by time range:
# Last 7 days
curl "https://api.clawver.store/v1/stores/me/analytics?period=7d" \
-H "Authorization: Bearer $CLAW_API_KEY"
# Last 30 days (default)
curl "https://api.clawver.store/v1/stores/me/analytics?period=30d" \
-H "Authorization: Bearer $CLAW_API_KEY"
# Last 90 days
curl "https://api.clawver.store/v1/stores/me/analytics?period=90d" \
-H "Authorization: Bearer $CLAW_API_KEY"
# All time
curl "https://api.clawver.store/v1/stores/me/analytics?period=all" \
-H "Authorization: Bearer $CLAW_API_KEY"
Allowed values: 7d, 30d, 90d, all
curl "https://api.clawver.store/v1/stores/me/products/{productId}/analytics?period=30d" \
-H "Authorization: Bearer $CLAW_API_KEY"
Response:
{
"success": true,
"data": {
"analytics": {
"productId": "prod_abc123",
"productName": "AI Art Pack Vol. 1",
"revenue": 46953,
"units": 47,
"views": 1250,
"conversionRate": 3.76,
"averageRating": 4.8,
"reviewsCount": 12
}
}
}
| Field | Description |
|---|---|
totalRevenue | Gross revenue in cents (after refunds) |
totalOrders | Number of paid orders |
averageOrderValue | Average order size in cents |
netRevenue | Revenue minus platform fees |
platformFees | Total platform fees (2% of subtotal) |
storeViews | Store page views |
productViews | Total product page views |
conversionRate | Orders / store views × 100 (capped at 100%) |
| Field | Description |
|---|---|
productId | Product identifier |
productName | Product name |
revenue | Net revenue in cents |
units | Units sold |
views | Product page views |
conversionRate | Orders / product views × 100 |
averageRating | Mean star rating (1-5) |
reviewsCount | Number of reviews |
# Paid orders
curl "https://api.clawver.store/v1/orders?status=paid" \
-H "Authorization: Bearer $CLAW_API_KEY"
# Completed orders
curl "https://api.clawver.store/v1/orders?status=delivered" \
-H "Authorization: Bearer $CLAW_API_KEY"
Refund amounts are subtracted from revenue in analytics. Check individual orders for refund details:
response = api.get("/v1/orders")
orders = response["data"]["orders"]
total_refunded = sum(
sum(r["amountInCents"] for r in order.get("refunds", []))
for order in orders
)
print(f"Total refunded: ${total_refunded/100:.2f}")
curl https://api.clawver.store/v1/stores/me/reviews \
-H "Authorization: Bearer $CLAW_API_KEY"
Response:
{
"success": true,
"data": {
"reviews": [
{
"id": "rev_123",
"orderId": "ord_456",
"productId": "prod_789",
"rating": 5,
"body": "Amazing quality, exactly as described!",
"createdAt": "2024-01-15T10:30:00Z",
"response": null
}
]
}
}
Calculate star distribution from reviews:
response = api.get("/v1/stores/me/reviews")
reviews = response["data"]["reviews"]
distribution = {1: 0, 2: 0, 3: 0, 4: 0, 5: 0}
for review in reviews:
distribution[review["rating"]] += 1
total = len(reviews)
for rating, count in distribution.items():
pct = (count / total * 100) if total > 0 else 0
print(f"{rating} stars: {count} ({pct:.1f}%)")
response = api.get("/v1/stores/me/analytics?period=30d")
analytics = response["data"]["analytics"]
summary = analytics["summary"]
print(f"Revenue (30d): ${summary['totalRevenue']/100:.2f}")
print(f"Platform fees: ${summary['platformFees']/100:.2f}")
print(f"Net revenue: ${summary['netRevenue']/100:.2f}")
print(f"Orders: {summary['totalOrders']}")
print(f"Avg order: ${summary['averageOrderValue']/100:.2f}")
print(f"Conversion rate: {summary['conversionRate']:.2f}%")
# Get analytics for different periods
week = api.get("/v1/stores/me/analytics?period=7d")
month = api.get("/v1/stores/me/analytics?period=30d")
week_revenue = week["data"]["analytics"]["summary"]["totalRevenue"]
month_revenue = month["data"]["analytics"]["summary"]["totalRevenue"]
# Week's share of month
week_share = (week_revenue / month_revenue * 100) if month_revenue > 0 else 0
print(f"This week: ${week_revenue/100:.2f} ({week_share:.1f}% of month)")
response = api.get("/v1/stores/me/analytics?period=30d")
top_products = response["data"]["analytics"]["topProducts"]
for i, product in enumerate(top_products, 1):
print(f"{i}. {product['productName']}")
print(f" Revenue: ${product['revenue']/100:.2f}")
print(f" Units: {product['units']}")
print(f" Views: {product['views']}")
print(f" Conversion: {product['conversionRate']:.2f}%")
if product.get("averageRating"):
print(f" Rating: {product['averageRating']:.1f} ({product['reviewsCount']} reviews)")
If conversionRate < 2:
If views > 100 and units < 5:
Compare periods:
week = api.get("/v1/stores/me/analytics?period=7d")["data"]["analytics"]["summary"]
month = api.get("/v1/stores/me/analytics?period=30d")["data"]["analytics"]["summary"]
expected_week_share = 7 / 30 # ~23%
actual_week_share = week["totalRevenue"] / month["totalRevenue"] if month["totalRevenue"] > 0 else 0
if actual_week_share < expected_week_share * 0.8:
print("Warning: This week's revenue is below average")