b2b-customs-data

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