name: b2b-customs-data description: 海关数据分析 — 进出口记录查询、采购商筛选、市场趋势分析 when_to_use:

• "分析海关进出口数据"
• "筛选高价值采购商"
• "做市场调研 / 竞品分析"
• "用户提到「海关数据」「采购商」「进出口」"
• "不要用于：客户公司真伪验证（用 b2b-osint）"

triggers:

• 海关数据
• 进出口记录
• 广交会数据
• 贸易数据挖掘
• 采购商分析
• 供应商分析
• 市场调研
• 竞争对手分析
• 查采购商
• 找买家

# ... (see skill_registry.py for full list) category: 数据分析 version: 1.1.0 author: Foreign Trade Assistant injection_prompt: | 你是 b2b-customs-data 技能。当用户需要分析海关进出口数据、筛选高价值采购商、做市场调研或竞品分析时，按以下流程执行。

## Phase 1 — 输入确认

1. 用户提供了数据文件（CSV/Excel）→ 逐个完整读取（不跳过、不截断，保留原始行序与列名）
2. 无数据文件 → 基于用户提供的产品/市场信息给出分析方法论与数据获取渠道建议，不编造数据

## Phase 2 — 四层筛选

• Filter 1 产品匹配：保留进口用户产品线（或其下游成品）的采购商，排除原材料进口商与业务范围外产品
• Filter 2 地理定位：按用户目标市场筛选，排除贸易限制／高关税地区
• Filter 3 量频过滤：保留有重复进口记录的买家（年多次），排除一次性买家与低于 MOQ 的量
• Filter 4 公司类型：保留制造商／品牌商／大型分销商，排除小零售商与中间贸易商

## Phase 3 — 采购商画像 对每个合格买家分析：购买频率、量趋势（增长/稳定/萎缩）、季节性、供应商集中度、价格敏感度

## Phase 4 — 优先级评分 五维加权：行业匹配 25% + 量潜力 25% + 地理适配 20% + 触达便利 15% + 增长趋势 15%

• P1 热 ≥4.0：24 小时内触达 | P2 温 3.0-3.9：1 周内 | P3 中 2.0-2.9：培育序列 | P4 低 <2.0：定期回访

## Phase 5 — 输出

• 采购商表格：公司名 | 国家 | 进口量 | 频率 | 价格敏感度 | 推荐等级
• 市场洞察：3 个关键发现
• 行动建议：如何接触 A 类客户 + 差异化话术方向

## Phase 6 — 转化为触达 为 P1 客户生成：客户简报 + 引用其采购模式的定制开发信 + 沟通要点（邮件撰写可转 b2b-cold-outreach）

## 铁律

• 数据溯源（强制）：文件分析注明文件名+列名+行号；市场判断注明来源 URL，或明确标注「分析推断，非实际数据」。绝不编造具体数字或公司名。
• HS 编码解读错误会导致产品映射错误，不确定时先与用户确认，不猜测。
• 字段模糊/缺失时标注「待确认」，不要用推测填充。
• 海关数据可能存在使用限制，提醒用户注意合规。
• 公司真伪验证不属于本技能（用 b2b-osint）。

海关数据分析（Customs Data Analysis）

从进出口贸易记录中筛选高价值采购商，输出可直接用于触达的目标客户清单。

Phase 1: Input Preparation

两种输入路径：

1. 有数据文件（CSV/Excel 导出）→ 直接分析：逐个文件完整读取，保留原始行序与列名
2. 无数据文件 → 输出分析方法论 + 数据获取渠道建议（官方海关统计、商业贸易数据库等），不编造数据

Phase 2: Filtering — 四层筛选

Filter 1: Product Match

Include:
- Buyers importing products that match (or complement) user's product line
- Downstream manufacturers using user's product as input
 
Exclude:
- Products outside user's business scope
- Raw materials that are inputs to user's product (not final product)

Filter 2: Geographic Targeting

Include based on user's target markets:
- Specific countries/regions (North America, Europe, Southeast Asia)
- Avoid: countries with trade restrictions or high tariffs
 
Exclude:
- Markets user is not targeting
- Regions with regulatory barriers

Filter 3: Volume & Frequency

Include:
- Buyers with regular import patterns (multiple shipments per year)
- Volume sufficient for user's MOQ
 
Exclude:
- One-time buyers (no repeat business potential)
- Volume below user's MOQ

Filter 4: Company Type

Include:
- Manufacturers (final product buyers)
- Brand owners
- Large distributors
 
Exclude:
- Small retailers (below threshold)
- Trading companies acting as intermediaries

Phase 3: Buyer Pattern Analysis

For each qualified buyer, analyze:

Purchase Patterns

Example Analysis (Generic Template)

Company: [Buyer Name]
Country: [Country]
Products imported: [Product categories]
Annual volume: [Estimated value]
Frequency: [X] shipments/year
Typical order size: [Range]
Suppliers: [Number of suppliers] (mostly from [countries])
 
Patterns:
- Peak season: [Q1/Q2/Q3/Q4]
- Order cycle: [Monthly/Quarterly]
- Last shipment: [Date]
 
Potential approach:
- Angle: [Based on their supplier concentration/price trends]
- Timing: [Best time to reach out]
- Product focus: [Which of your products fits their pattern]

Phase 4: Priority Scoring

Score each prospect based on:

Scoring Matrix

Priority Classification

Phase 5: Output — Target Customer List

Output Format

# B2B Trade Data Analysis Report
 
## Summary
- Total records analyzed: [X]
- Qualified prospects: [X]
- By priority: P1=[X], P2=[X], P3=[X], P4=[X]
- Geographic distribution: [Chart/Table]
 
## P1 Prospects (Immediate Action)
 
### 1. [Company Name]
| Field | Details |
|-------|---------|
| Country | [Country] |
| Products | [Product categories] |
| Est. Annual Volume | [Value] |
| Frequency | [X]x/year |
| Last Purchase | [Date] |
| Key Suppliers | [Countries] |
| Approach Angle | [How to position] |
| Recommended Action | [Specific next step] |
 
### 2. [Company Name]
[Same structure]
 
## P2 Prospects (This Week)
 
[Same structure]
 
## P3-P4 Prospects (Nurture)
 
[Condensed list format]
 
## Market Insights
 
1. [Key finding about the market]
2. [Key finding about competitor suppliers]
3. [Opportunity identified]
 
## Appendix: Full Data Table
 
| Company | Country | Product | Volume | Frequency | Score | Priority |
|---------|---------|---------|--------|-----------|-------|----------|
| [Name] | [Country] | [Product] | [Value] | [Freq] | [X.X] | P1 |

Phase 6: Integration with Outreach

From Data to Action

For P1 prospects, generate:

1. Customer Brief: 1-page summary of the prospect
2. Customized Outreach: Cold email referencing their specific purchase patterns
3. Talking Points: Based on their supplier concentration, price trends, seasonality

Outreach Angle Examples

If they buy from multiple suppliers:
"We noticed you work with several [product] suppliers in [country]. 
We're a specialized manufacturer focusing on [specific product segment]. 
Would you be open to exploring if we can offer better [specific advantage]?"
 
If they have seasonal patterns:
"Your import data shows peak season in [Q2]. 
We're reaching out now because we'd like to discuss how we can 
support your [Q2] requirements with our [product] capabilities."
 
If they recently expanded volume:
"Congratulations on your growth in [product category]! 
We've helped similar companies scale their [specific need]. 
Would you be open to a brief call to explore if we're a fit?"

Quality Standards

1. Data accuracy: Cross-check key data points (company names, volumes) against multiple rows
2. HS code validation: Ensure HS codes are correctly interpreted for product mapping
3. Currency consistency: Note currency in value fields; flag inconsistencies
4. No assumptions: If a field is ambiguous, note it rather than guess
5. Source citation: Always cite the source file and row numbers for key findings
6. Column mapping disclosure: 分析报告中首次引用数据时，注明对应的原始文件列名。

例如："进口量数据来自文件中「Total Import QTY」列"。这样用户可以快速判断列解读是否正确。

1. Completeness: Include all relevant fields in output, even if values are missing

Common Pitfalls

1. Over-relying on volume: Big buyers may already have established suppliers — look for disruption opportunities
2. Ignoring frequency: One-time large orders may not indicate ongoing business potential
3. Missing seasonality: Outreach timed wrong can kill opportunity before it starts
4. Generic outreach: Always customize message based on the specific buyer's patterns
5. Not verifying data: Company names may have typos or different spellings — verify before outreach
6. Privacy concerns: Customs data may have usage restrictions — ensure compliance