SellerSprite Market Research
This skill helps screen and rank Amazon category markets using SellerSprite market-research data.
Core Concepts
- 类目市场级分析:不是商品级列表,而是按类目/节点聚合后的市场画像。
- 市场规模:月均销量、月均销售额、商品数量等。
- 竞争结构:卖家/品牌集中度、头部集中度、自营占比、FBA/FBM 占比。
- 新品机会:新品数量、新品占比、新品均价/评分/销量等。
API Usage
- Endpoint:
POST https://tool-gateway.linkfox.com/sellersprite/market/research - Auth: Header
Authorization: <api_key>(LINKFOXAGENT_API_KEY) - See full details in
references/api.md. - Runnable script:
scripts/sellersprite_market_research.py
Key Parameters
该接口支持大量筛选项(70+),以下为高频参数;完整说明见
references/api.md。
| 参数 | 类型 | 必填 | 说明 |
|---|---|---|---|
| marketplace | string | 是 | 站点编码,默认 US |
| month | string | 否 | nearly 或 yyyyMM |
| nodeIdPath | string | 否 | 类目节点路径 |
| departmentKeyword | string | 否 | 类目关键字路径 |
| page / size | integer | 否 | 分页,默认 1/50,size 最大 200 |
| orderField / orderDesc | string/boolean | 否 | 排序字段与方向 |
| minAvgRevenue / maxAvgRevenue | number | 否 | 月均销售额范围 |
| minAvgUnits / maxAvgUnits | integer | 否 | 月均销量范围 |
| minGoodsCount / maxGoodsCount | integer | 否 | 商品数量范围 |
| minGoodsCrn / maxGoodsCrn | number | 否 | 商品集中度(%) |
| minSellerCrn / maxSellerCrn | number | 否 | 卖家集中度(%) |
| minBrandCrn / maxBrandCrn | number | 否 | 品牌集中度(%) |
| minNewProportion / maxNewProportion | number | 否 | 新品占比(%) |
| minAvgPrice / maxAvgPrice | number | 否 | 平均价格范围 |
| minAvgRating / maxAvgRating | number | 否 | 平均评分范围 |
| minAvgProfit / maxAvgProfit | number | 否 | 平均毛利率(%) |
Usage Example
{
"marketplace": "US",
"month": "nearly",
"minAvgRevenue": 10000,
"maxGoodsCrn": 40,
"minNewProportion": 10,
"maxSellerCrn": 50,
"orderField": "total_amount",
"orderDesc": true,
"page": 1,
"size": 50
}
Display Rules
- 先给出市场候选 Top N,再展示核心指标(市场规模、集中度、新品占比)。
- 清晰标注单位:比例字段是
%,金额按站点币种。 - 显示筛选条件回显,便于用户复现。
- 若结果过少或过多,建议用户调整关键阈值(如集中度、规模阈值)。
Important Limitations
- 必填参数:
marketplace - 每页最多 200 条
- 历史月份范围受第三方限制(通常近24个月)
Feedback:
Auto-detect and report feedback via the Feedback API when any of the following apply:
- The functionality or purpose described in this skill does not match actual behavior
- The skill's results do not match the user's intent
- The user expresses dissatisfaction or praise about this skill
- Anything you believe could be improved
Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.