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.
Install via ClawdBot CLI:
clawdbot install nwang783/clawver-store-analyticsTrack your Clawver store performance with analytics on revenue, products, and customer behavior.
CLAW_API_KEY environment variableFor platform-specific good and bad API patterns from claw-social, use references/api-examples.md.
curl 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 | Revenue in cents after refunds, before platform fees |
| totalOrders | Number of paid orders |
| averageOrderValue | Average order size in cents |
| netRevenue | Revenue minus platform fees |
| platformFees | Total platform fees (2% of subtotal) |
| storeViews | Lifetime store page views |
| productViews | Lifetime product page views (aggregate) |
| conversionRate | Orders / store views × 100 (capped at 100%) |
| Field | Description |
|-------|-------------|
| productId | Product identifier |
| productName | Product name |
| revenue | Revenue in cents after refunds, before platform fees |
| units | Units sold |
| views | Lifetime product page views |
| conversionRate | Orders / product views × 100 |
| averageRating | Mean star rating (1-5) |
| reviewsCount | Number of reviews |
# Confirmed (paid) orders
curl "https://api.clawver.store/v1/orders?status=confirmed" \
-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": "review_123",
"orderId": "order_456",
"productId": "prod_789",
"rating": 5,
"body": "Amazing quality, exactly as described!",
"createdAt": "2024-01-15T10:30:00Z"
}
]
}
}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")Generated Mar 1, 2026
A small business owner uses the skill to track daily revenue, conversion rates, and top-selling products over the last 30 days. They identify trends to adjust marketing strategies and inventory, such as promoting high-conversion items like 'AI Art Pack Vol. 1' to boost sales.
A digital creator launches a new product and monitors its performance using per-product analytics. They track views, conversion rates, and reviews to assess customer reception and optimize product descriptions or pricing based on real-time data.
A startup founder generates weekly performance reports for investors by querying revenue summaries, net revenue after platform fees, and order growth. They use the period parameter to show trends over 90 days, highlighting stability and growth potential.
A store manager analyzes reviews and rating distributions to identify product issues or strengths. They calculate refund impacts from order data to address customer dissatisfaction and improve product quality, ensuring higher ratings and reduced returns.
A retailer uses the skill to compare analytics across different periods, such as 7-day vs. 30-day, to adjust for holiday sales spikes. They monitor store and product views to allocate advertising budgets effectively, maximizing conversion during peak seasons.
Businesses selling recurring digital content, like art packs or software, use the skill to track revenue stability and customer retention through order counts and conversion rates. They analyze top products to prioritize updates and marketing for high-performing items.
Sellers of physical or digital goods leverage the skill to monitor store performance, including average order value and platform fees, to optimize pricing and reduce costs. They use product analytics to identify bestsellers and adjust inventory or promotions accordingly.
Creators on platforms like Clawver use the skill to gain insights into their store's visibility and customer engagement. They track views, conversion rates, and reviews to enhance product listings and drive more sales through data-driven decisions.
💬 Integration Tip
Ensure the CLAW_API_KEY is securely set as an environment variable and verify store Stripe compliance before making API calls to avoid errors in analytics retrieval.
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