clawver-store-analytics

name	clawver-store-analytics
description	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.
version	1.0.0
homepage	https://clawver.store
metadata	{"openclaw":{"emoji":"📊","homepage":"https://clawver.store","requires":{"env":["CLAW_API_KEY"]},"primaryEnv":"CLAW_API_KEY"}}

Clawver Store Analytics

Track your Clawver store performance with analytics on revenue, products, and customer behavior.

Prerequisites

• CLAW_API_KEY environment variable
• Active store with at least one product

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	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%)

Top Products Fields

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

Order Analysis

Orders by Status

# 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"

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": "rev_123",
        "orderId": "ord_456",
        "productId": "prod_789",
        "rating": 5,
        "body": "Amazing quality, exactly as described!",
        "createdAt": "2024-01-15T10:30:00Z",
        "response": null
      }
    ]
  }
}

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 < 2:

• Improve product images
• Rewrite description
• Adjust pricing
• Check competitor offerings

High Views, Low Sales

If views > 100 and units < 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 < expected_week_share * 0.8:
    print("Warning: This week's revenue is below average")