Store Product Analysis API Endpoint

API Information

• API Name: Store Product Analysis API Endpoint
• Request Method: GET
• API Address: /open-api/v1/data
• API Path: /v3/api/open/store/product-analysis
• API Description:
  • Query product statistics and analysis data for a specified store
  • Statistics on the number of products promoted on different platforms, category distribution, and price range distribution
  • Support filtering product data by time range
  • Help analyze store product strategy and pricing strategy
  • Pricing: Free

Request Headers:

• Content-Type: application/json
• Accept: application/json

Request Parameters

Request Structure

Request Body Parameters (params object)

Request Example

curl -X POST "https://www.pipispy.com/open-api/v1/data" \
  -H "Content-Type: application/json" \
  -H "Accept: application/json" \
  -d '{
    "key": "your_api_key_here",
    "uri": "/v3/api/open/store/product-analysis",
    "params": {
      "id": "9407a696eb444",
      "start_time": 1761408000,
      "end_time": 1763999999
    }
  }'

Response Parameters

Response Body Structure

{
    "code": 200,
    "message": "success",
    "data": {
        "total": {
            "all": 0,
            "total": 25,
            "tiktok": 25,
            "facebook": 0
        },
        "price": {
            "100": 4,
            "10-20": 0,
            "50-100": 16,
            "1-10": 0,
            "20-50": 5
        },
        "type": [
            {
                "ai_type_name_zh": "女装",
                "count": 12,
                "ai_type_name_en": "Women's Clothing",
                "ai_type": "62739c0138365b2f72048ed7"
            },
            {
                "ai_type_name_zh": "其他",
                "count": 2,
                "ai_type_name_en": "Other",
                "ai_type": "62739c2138365b2f72048edb"
            },
            {
                "ai_type_name_zh": "男装",
                "count": 2,
                "ai_type_name_en": "Men's Clothing",
                "ai_type": "62739c0d38365b2f72048ed8"
            }
        ]
    },
    "version": "v1",
    "timestamp": null,
    "sign": null,
  "remaining_credits": 9980,
  "consumed_credits": 0,
    "success": true,
    "fail": false
}

Response Field Descriptions

Response Result Information Fields

data Object Structure

total Object Structure (Platform Distribution Statistics)

type Array Element Structure (Product Category)

price Object Structure (Price Range Distribution, Unit: USD)

Response Examples

Complete Data Example

{
    "code": 200,
    "message": "success",
    "data": {
        "total": {
            "all": 0,
            "total": 25,
            "tiktok": 25,
            "facebook": 0
        },
        "price": {
            "100": 4,
            "10-20": 0,
            "50-100": 16,
            "1-10": 0,
            "20-50": 5
        },
        "type": [
            {
                "ai_type_name_zh": "女装",
                "count": 12,
                "ai_type_name_en": "Women's Clothing",
                "ai_type": "62739c0138365b2f72048ed7"
            },
            {
                "ai_type_name_zh": "其他",
                "count": 2,
                "ai_type_name_en": "Other",
                "ai_type": "62739c2138365b2f72048edb"
            },
            {
                "ai_type_name_zh": "男装",
                "count": 2,
                "ai_type_name_en": "Men's Clothing",
                "ai_type": "62739c0d38365b2f72048ed8"
            }
        ]
    },
    "version": "v1",
    "timestamp": null,
    "sign": null,
  "remaining_credits": 9980,
  "consumed_credits": 0,
    "success": true,
    "fail": false
}

Time Range Filter Example

Request parameters:

{
  "id": "12345",
  "start_time": 1704067200,
  "end_time": 1706745599
}

Response data (only returns products found within the specified time range):

{
  "code": 200,
  "message": "success",
  "data": {
    "total": {
      "total": 125,
      "tiktok": 95,
      "facebook": 68,
      "all": 38
    },
    "type": [
      {
        "ai_type": "fashion",
        "ai_type_name_zh": "时尚服饰",
        "ai_type_name_en": "Fashion & Apparel",
        "count": 52
      },
      {
        "ai_type": "electronics",
        "ai_type_name_zh": "电子产品",
        "ai_type_name_en": "Electronics",
        "count": 38
      },
      {
        "ai_type": "beauty",
        "ai_type_name_zh": "美妆护肤",
        "ai_type_name_en": "Beauty & Personal Care",
        "count": 35
      }
    ],
    "price": {
      "100": 2,
      "1-10": 45,
      "10-20": 52,
      "20-50": 20,
      "50-100": 6
    }
  },
  "version": "v1",
  "timestamp": null,
  "sign": null,
  "remaining_credits": 9980,
  "consumed_credits": 0,
  "fail": false,
  "success": true
}

Error Code Descriptions

Usage Instructions

1. Time Range Filtering

The API supports filtering products through start_time and end_time parameters:

• Filter Dimension: Product's latest found time (all_latest_found_time)
• No time parameters: Returns statistics for all products in the store
• Only start_time: Returns products found from that time point to now
• Only end_time: Returns products found from earliest to that time point
• Both provided: Returns products found within that time range

2. Platform Distribution Statistics Explanation

total Field Interpretation:

{
  "total": 850,      // Store has promoted 850 products in total
  "tiktok": 620,     // Of which 620 products have ads on TikTok platform
  "facebook": 480,   // Of which 480 products have ads on Facebook platform
  "all": 250         // Of which 250 products have ads on both platforms
}

Relationship Explanation:

• tiktok + facebook - all = Number of products promoted on single platform only
• TikTok only: tiktok - all = 370 products
• Facebook only: facebook - all = 230 products
• Both platforms: all = 250 products
• Total: 370 + 230 + 250 = 850 products

3. Product Category Statistics Explanation

AI Smart Classification:

• System uses AI algorithms to automatically identify product categories
• Each product has corresponding category code and Chinese/English names
• Category statistics help understand store product structure

Common Categories:

• fashion: Fashion & Apparel
• electronics: Electronics
• home_garden: Home & Garden
• beauty: Beauty & Personal Care
• sports: Sports & Outdoors
• toys: Toys & Games
• food: Food & Beverages
• pet: Pet Supplies
• etc.

4. Price Range Distribution Explanation

Price Statistics Rules:

• Priority uses product's USD price (usd_price)
• If no USD price but currency is USD, uses original price (price)
• Other currencies are temporarily not counted

Price Range Division: