/install clawver-store-analytics
Clawver Store Analytics
Track your Clawver store performance with analytics on revenue, products, and customer behavior.
Prerequisites
CLAW_API_KEYenvironment variable- Active store with at least one product
- Store must have completed Stripe verification to appear in public listings
For platform-specific good and bad API patterns from claw-social, use references/api-examples.md.
Store Overview
Get Store Analytics
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
}
}
}
Query by Period
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
Product Analytics
Get Per-Product Stats
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
}
}
}
Key Metrics
Summary Fields
| 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%) |
Top Products Fields
| 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 |
Order Analysis
Orders by Status
# 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"
Calculate Refund Impact
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}")
Review Analysis
Get All Reviews
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"
}
]
}
}
Rating Distribution
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}%)")
Reporting Patterns
Revenue Summary
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}%")
Weekly Performance Report
# 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)")
Top Product Analysis
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)")
Actionable Insights
Low Conversion Products
If conversionRate \x3C 2:
- Improve product images
- Rewrite description
- Adjust pricing
- Check competitor offerings
High Views, Low Sales
If views > 100 and units \x3C 5:
- Price may be too high
- Description unclear
- Missing social proof (reviews)
Declining Revenue
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 \x3C expected_week_share * 0.8:
print("Warning: This week's revenue is below average")
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install clawver-store-analytics - 安装完成后,直接呼叫该 Skill 的名称或使用
/clawver-store-analytics触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
Clawver Store Analytics 是什么?
Monitor Clawver store performance. Query revenue, top products, conversion rates, growth trends. Use when asked about sales data, store metrics, performance reports, or business analytics. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 1923 次。
如何安装 Clawver Store Analytics?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install clawver-store-analytics」即可一键安装,无需额外配置。
Clawver Store Analytics 是免费的吗?
是的,Clawver Store Analytics 完全免费(开源免费),可自由下载、安装和使用。
Clawver Store Analytics 支持哪些平台?
Clawver Store Analytics 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 Clawver Store Analytics?
由 nwang783(@nwang783)开发并维护,当前版本 v1.0.1。