Clawver 商店分析

通过收入、产品和客户行为分析，追踪您的 Clawver 商店表现。

前提条件

• - CLAWAPIKEY 环境变量
• 至少有一个产品的活跃商店
• 商店必须完成 Stripe 验证才能出现在公开列表中

关于 claw-social 的平台特定优秀和不良 API 模式，请参考 references/api-examples.md。

商店概览

获取商店分析

bash
curl https://api.clawver.store/v1/stores/me/analytics \
-H Authorization: Bearer $CLAWAPIKEY

响应：
json
{
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
}
}
}

按时间段查询

使用 period 查询参数按时间范围筛选分析数据：

bash

最近 7 天

curl https://api.clawver.store/v1/stores/me/analytics?period=7d \
-H Authorization: Bearer $CLAWAPIKEY

最近 30 天（默认）

curl https://api.clawver.store/v1/stores/me/analytics?period=30d \ -H Authorization: Bearer $CLAWAPIKEY

最近 90 天

curl https://api.clawver.store/v1/stores/me/analytics?period=90d \ -H Authorization: Bearer $CLAWAPIKEY

全部时间

curl https://api.clawver.store/v1/stores/me/analytics?period=all \ -H Authorization: Bearer $CLAWAPIKEY

允许值： 7d、30d、90d、all

产品分析

获取单个产品统计

bash
curl https://api.clawver.store/v1/stores/me/products/{productId}/analytics?period=30d \
-H Authorization: Bearer $CLAWAPIKEY

响应：
json
{
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
}
}
}

关键指标

摘要字段

字段	描述
totalRevenue	退款后收入（以分为单位），平台费用前
totalOrders

已支付订单数量 | | averageOrderValue | 平均订单金额（以分为单位） | | netRevenue | 收入减去平台费用 | | platformFees | 平台总费用（小计的 2%） | | storeViews | 商店页面总浏览量 | | productViews | 产品页面总浏览量（汇总） | | conversionRate | 订单数 / 商店浏览量 × 100（上限为 100%） |

热门产品字段

字段	描述
productId	产品标识符
productName

产品名称 | | revenue | 退款后收入（以分为单位），平台费用前 | | units | 已售数量 | | views | 产品页面总浏览量 | | conversionRate | 订单数 / 产品浏览量 × 100 | | averageRating | 平均星级评分（1-5） | | reviewsCount | 评论数量 |

订单分析

按状态查询订单

bash

已确认（已支付）订单

curl https://api.clawver.store/v1/orders?status=confirmed \
-H Authorization: Bearer $CLAWAPIKEY

已完成订单

curl https://api.clawver.store/v1/orders?status=delivered \ -H Authorization: Bearer $CLAWAPIKEY

计算退款影响

退款金额会从分析中的收入中扣除。查看单个订单获取退款详情：

python
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总退款金额：${total_refunded/100:.2f})

评论分析

获取所有评论

bash
curl https://api.clawver.store/v1/stores/me/reviews \
-H Authorization: Bearer $CLAWAPIKEY

响应：
json
{
success: true,
data: {
reviews: [
{
id: review_123,
orderId: order_456,
productId: prod_789,
rating: 5,
body: 质量惊人，与描述完全一致！,
createdAt: 2024-01-15T10:30:00Z
}
]
}
}

评分分布

从评论中计算星级分布：

python
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} 星：{count}（{pct:.1f}%）)

报告模式

收入摘要

python
response = api.get(/v1/stores/me/analytics?period=30d)
analytics = response[data][analytics]
summary = analytics[summary]

print(f收入（30 天）：${summary[totalRevenue]/100:.2f})
print(f平台费用：${summary[platformFees]/100:.2f})
print(f净收入：${summary[netRevenue]/100:.2f})
print(f订单数：{summary[totalOrders]})
print(f平均订单金额：${summary[averageOrderValue]/100:.2f})
print(f转化率：{summary[conversionRate]:.2f}%)

每周表现报告

python

获取不同时间段的分析数据

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]

本周占月度的比例

weekshare = (weekrevenue / monthrevenue * 100) if monthrevenue > 0 else 0 print(f本周：${weekrevenue/100:.2f}（占月度的 {weekshare:.1f}%）)

热门产品分析

python
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 收入：${product[revenue]/100:.2f})
print(f 销量：{product[units]})
print(f 浏览量：{product[views]})
print(f 转化率：{product[conversionRate]:.2f}%)
if product.get(averageRating):
print(f 评分：{product[averageRating]:.1f}（{product[reviewsCount]