b2b-customs-data

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
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"]
category	数据分析
version	1.0.0
author	Foreign Trade Assistant

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

| Metric | What It Tells You |
|--------|-------------------|
| **Frequency** | How often they buy (monthly/quarterly/annually) |
| **Volume trend** | Growing, stable, or declining purchases |
| **Seasonality** | Peak buying seasons |
| **Supplier concentration** | Do they rely on few or many suppliers? |
| **Price sensitivity** | Volume vs. price correlations |

### 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

| Criteria | Weight | Score (1-5) |
|----------|--------|-------------|
| Industry match | 25% | How well product aligns |
| Volume potential | 25% | Order size and frequency |
| Geographic fit | 20% | Your ability to serve |
| Accessibility | 15% | Ease of outreach (LinkedIn, email, etc.) |
| Growth trend | 15% | Purchase volume trend |

### Priority Classification

| Total Score | Priority | Action |
|-------------|----------|--------|
| 4.0 - 5.0 | **P1 — Hot** | Immediate outreach within 24h |
| 3.0 - 3.9 | **P2 — Warm** | Personalized outreach within 1 week |
| 2.0 - 2.9 | **P3 — Medium** | Add to nurture sequence |
| < 2.0 | **P4 — Low** | Periodic check-ins only |

## 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。
7. **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