Why start from customs data
The first mistake exporters make in a new market is trying to guess “who needs our product”. The answer is already recorded: in many countries every container clearing customs is public record, with importer and supplier visible. Before searching for customers, find companies already importing what you sell.
This piece walks the chain - customs data → HS mapping → country priority → company list → decision-maker → outreach - with concrete tools and templates, in 6 steps. It ends with a 30-day calendar and how to run the whole workflow on Sighthem.
Step 1: Nail the right HS / GTIP code
The foundation of the entire chain is correct classification. A broad category (“aluminium profile”) and a narrow product (“anodized architectural profile”) fall under different codes; a wrong code leads to wrong countries and wrong companies later.
- HS 6 digits: International common. TradeMap and UN Comtrade query at this level.
- 8-10-12 digits: Country-specific. US HTS 10, EU CN 8, Türkiye GTIP 12.
- Multiple products: Pick the main product’s code first; treat secondary products as separate analyses, do not merge.
How to actually find the right code is a topic of its own; see How to find the right HS code.
Step 2: Rank target countries (TradeMap)
Open a free account on trademap.org, go to “Trade Statistics” → “Product”, enter the HS code, switch to “Imports”. You will see 50+ countries that import the code most, with volume and growth.
Apply four filters:
- Import volume: Top 10; market size threshold.
- Annual growth: Prefer growing markets (flat = saturated).
- Your country’s share: Below 1% = a big gap, above 15% = saturated; mid-share is the sweet spot.
- Geo/logistics logic: Closer markets mean lower freight and faster turnaround.
Land on 5-8 target countries. Do not pursue them in parallel; focus on 2 in the first 60 days, measure signals, then expand.
Step 3: Identify companies in the target country
Time to move from abstract volume to a concrete company list. The source depends on the market. The table below lists the data sources trade teams actually use and what each is good for.
| Source | Region | Cost | Best for |
|---|---|---|---|
| TradeMap (ITC) | Global (220+ countries) | Free account | Country-level import/export flows; fastest way to see the largest importing countries. |
| UN Comtrade | Global | Free | Official country-to-country trade statistics; for cross-validation. |
| ImportYeti | US imports | Free search, premium 49 USD/mo | Search US-bound containers by importer company name. Gold for US-market plays. |
| Volza | 78+ countries | 120-500 USD/mo | Importer-exporter matching in India, Latin America, and Asia. Trial available. |
| Panjiva (S&P) | Global | Enterprise (~500+ USD/mo) | Broad coverage, enterprise reporting. For larger teams. |
| Eurostat Comext | EU 27 | Free | Intra/extra-EU flow totals. Company-level data is confidential in the EU; use country aggregates. |
| US Census Bureau | US trade | Free | Official US import/export stats (USA Trade Online). |
| 52wmb | China exports | Freemium | Search China-outbound containers by buyer; also useful for supplier scouting. |
| Trademo | Global | Trial + enterprise | Supply-chain visualization with sanctions/risk overlay. |
| TÜİK Dış Ticaret İstatistikleri | Türkiye | Free | Türkiye’s HS-code/country breakdown; useful for competitor-export benchmarking. |
Company-level customs data in Germany, France, Italy and other EU countries is confidential by law. Eurostat Comext gives you country totals; you build the company list manually via (a) European buyers visible in US/India customs data, (b) industry association member directories, (c) LinkedIn Sales Navigator with company-size filters.
Open ImportYeti, search the HS code, take the first 30-50 names from “Top Importers”. For each company: annual container count, last shipment date, most-used supplier country. Export CSV, sort by “current supplier country”. Companies that buy heavily from China, Vietnam, or Italy but not yet from your country are your prime targets.
Step 4: From company to decision-maker (LinkedIn boolean)
You have a company list. Now reach the right person inside each. LinkedIn Sales Navigator (~80 USD/mo) is the standard tool here; free LinkedIn allows limited search and Google dorks partially compensate.
Sales Navigator sample query (food sector, Germany, import-related roles):
Free alternative - Google dork:
For each decision-maker capture: full name, title, company, LinkedIn URL. Expect 60-100 names from 30 companies (2-3 relevant roles per company is typical).
Step 5: Email discovery and verification
You have names and companies; now find each person’s work email. Combine two methods: pattern guessing + verification. Start with the most common email pattern on the company domain:
first.last@company.com(most common in EU and US)first@company.com(start-ups)flast@company.com(corporate)last@company.com(Germany, Netherlands)
This is where Sighthem’s Email Verification service comes in: it predicts the decision-maker’s address from the company domain (pattern + name match), validates it in real time over SMTP (catch-all, role-account, and disposable detection included), and tags each result valid / risky / invalid. Risky addresses are excluded from campaigns; only valid ones enter the outreach sequence. Bounce stays under 3%; otherwise IP reputation collapses and follow-ups land in spam.
Your sending domain must have SPF + DKIM + DMARC records set. A new domain sending more than 20-30 messages a day needs “warming”: gradual ramp over 14-30 days.
Step 6: Outreach - email + LinkedIn in parallel
Email 1 - first touch (personalized, short, concrete):
Subject: Türkiye-sourced olive-oil option for {Company}
Hi {Name},
We see {Company} has imported extra-virgin olive oil mostly from Italy and Spain in the last 12 months. I want to introduce a Türkiye-Aegean supplier - IFS/BRC certified, with private-label capability.
At your shipment scale (~4-6 containers/month) MOQ is 18 tons, lead time 21 days, with an 8-12% EUR cost advantage on average. {Reference customer, similar profile} moved to the same program in Q3 2025.
Are you open to a 15-minute call in the next 2 weeks? If “no”, I will not push - just wanted to ask once.
{Name} · {Title} · {Company}
{Phone} · {Email}
Email 2 - follow-up (4-5 business days later):
Subject: RE: Türkiye-sourced olive-oil option for {Company}
Hi {Name}, my last note probably got lost.
Maybe useful: I am dropping a 2-page brief with Q1 2026 price trend and harvest outlook - [link]. Information, not a pitch.
If interest dropped I understand; happy to hear either way.
Email 3 - break-up (10-14 days later):
Subject: Should I close this thread?
Hi {Name},
I wrote twice and did not hear back. If you are not the right contact, could you point me to the colleague who is? If no reply, I will close the loop - this is my last note.
LinkedIn parallel flow:
- Day 0: Connection request with a 300-char personal note: “Writing a short note on {Company}’s olive-oil sourcing; wanted to be connected here too. Best.”
- Day 3 (if accepted): No sales pitch; sector note: “Aegean harvest outlook came out this week; we summarized our grower-network data in 2 pages - happy to share if useful.”
- Day 10: Short pitch + invite to email.
- Day 21: Passive follow-up, end-of-month sector update.
Email and LinkedIn run in parallel lifts reply rate by roughly 1.6-2x versus a single channel.
Step 7: Mail tracking and engagement scoring
Outreach is out the door; now you need to see who is engaging, who never even opened, and who reopened three times without replying. Routing warm leads to the call queue and cold leads to a B-series with a different theme is impossible without that visibility. Three dimensions to track:
- Open: Detected via a 1x1 pixel. Apple Mail Privacy Protection and Gmail image proxy create 20-30% “auto-open” noise; a properly built campaign module isolates real opens by filtering proxy IPs and User-Agent signatures.
- Click: Link rewrite logs every click. A far more reliable signal than open; corporate security scanners’ robot-clicks are filtered out.
- Device and client: User-Agent yields iPhone/Android/Mac/Windows split, Gmail/Outlook/Apple Mail/Thunderbird client detection, country and time-zone. “Opened three times on Outlook desktop during business hours, clicked pricing page, Hamburg 14:20” tells a very different buying-stage story than “single 11pm open on iPhone Apple Mail”.
These three dimensions combine into an engagement score (0-100). Leads crossing the threshold land in the rep’s “call today” queue automatically; low-score leads move into a B-series with a different subject and theme after 14 days. Without this layer, “who opened, who clicked” data sits in a spreadsheet and never turns into action. Sighthem’s campaign module runs the full chain - discovery → verification → send → open/click/device tracking → engagement score → automatic trigger - on one screen; no need to wire a sender, a verifier, and an analytics tool separately.
30-day calendar
| Week | Output |
|---|---|
| Week 1 | Correct HS code + TradeMap analysis + 2 target countries + 50 target companies via ImportYeti/Volza. |
| Week 2 | 80-120 decision-makers via LinkedIn boolean + email discovery and verification via Sighthem’s Email Verification service. |
| Week 3 | First email + LinkedIn connect (50-80 targets, 15-20/day cap). All outbound logged in one pipeline. |
| Week 4 | Follow-up emails + 15-min discovery calls with leads above the engagement-score threshold + low-score leads moved to B-series + 3-8 qualified leads in pipeline. |
35-50% open · 3-8% reply · 1-3% meeting accept · 1-3 qualified pipeline per 50 cold emails.
The 6 most common mistakes
- Single-channel bet: Only fairs, only B2B platforms, only cold email - low yield. Run at least 3 channels in parallel.
- Unverified emails: 5%+ bounce burns your IP; messages land in spam within 2 weeks. Sighthem’s Email Verification service tags every address before send - verification is non-negotiable.
- Generic “Hello, introduce”: Messages that do not name the company, sector, or current supplier profile get <1% reply.
- Wrong HS code: Analysis on a broad code points to the wrong country and the wrong companies; a month wasted.
- Expecting EU company-level data: It does not exist; in the EU, go through distributors, associations, and LinkedIn.
- Running leads in Excel: 100 companies, 100 decision-makers, a 3-step sequence - 3 weeks in, who got what when becomes a mystery. Excel does not carry that weight.
How this workflow runs on Sighthem
Without the right system, the output of the 6 steps above leaks. Sighthem keeps the chain end-to-end in one pipeline:
- CSV import → lead list: Import ImportYeti, Volza, or TradeMap CSVs directly. Each company lands as a Lead; the Source field is auto-tagged “Customs Data (ImportYeti)”, “LinkedIn”, or “Cold Email”. Later ROI measurement depends on that tag.
- HS code + country profile: Set HS code and country on each lead. Sighthem shows the suggested Incoterm (FOB/CIF/DAP), active sanctions warnings, and typical payment-risk note for that country in one click - before you ever send a quote. Why DDP for Germany, or a sanctions flag for Iran, is no longer a surprise.
- Email discovery + verification: Sighthem’s Email Verification service discovers and validates the decision-maker’s address from the lead’s domain over SMTP - no separate third-party finder subscription needed.
- Outreach sequence: The 3 emails + 4 LinkedIn steps above run as a sequence from saved templates. The moment a reply arrives, the sequence stops automatically and the lead moves to Qualified.
- Campaign module - mail tracking: Every send is tracked via 1x1 pixel + link rewrite. The lead card shows the behavioral trail in one line: opens, which link was clicked, which device (iPhone / Android / Mac / Windows), which client (Gmail / Outlook / Apple Mail), country, and time. Auto-open and robot-click noise from Apple Mail Privacy Protection and corporate security scanners is filtered out - only the real signal stays. Engagement score is computed automatically; leads above the threshold land in “call today”, low-score leads move to a B-series after 14 days. Which subject got the most opens, which link earned the most clicks, which device/client showed the highest engagement - all surfaced in the campaign report, so the next sequence is designed from data, not guesswork.
- 24-72-168-hour reminders: After contact, a follow-up task fires automatically when due - no manual calendar to maintain.
- Lead → Order → Shipment → Collection: A won lead flows to order, shipment, and collection on the same data model. You do not re-introduce the customer to a separate “ERP module”.
- Channel report: How many qualified leads each source (Customs Data, LinkedIn, Cold Email, Referral) produced, how many closed, and average cycle - on one dashboard.
Practical difference: running the same 50-company playbook with Excel + Gmail loses 30-40% of context by Week 4 (“what did I write, when, to whom”). With Sighthem, the same target list yields 3-4x more pipeline - not because of channel investment, but because of pipeline discipline.
Frequently Asked Questions
Is customs data actually accurate? Does it include unreported shipments?
In the US, India, Latin America, and many Asian markets, customs declarations are public record; importer company, container count, HS code, and shipment date are visible. The data reflects legal trade flows, not grey-market activity. The EU does not publish company-level data due to privacy rules; only country aggregates are available. Coverage is typically 85-95%; missing flows are usually small parcels or air cargo.
If the EU has no company-level data, how do I crack the German market?
Two routes. First: US/India customs data often shows German buyers because of re-distribution flows through ports like Rotterdam. Second: use Eurostat Comext to size Germany’s import volume by HS code vs your country, then build the company list manually via LinkedIn Sales Navigator + industry association member directories. In the EU, distributor search, association directories, and LinkedIn replace customs data.
Is cold email legal under GDPR/CAN-SPAM?
B2B one-to-one emails to a relevant professional, with an easy opt-out, generally qualify under GDPR’s "legitimate interest". Buying a list and blasting it does not. Practical rule: (1) state clearly who you are, (2) include an unsubscribe line, (3) honor opt-outs immediately and keep a record. In the US, CAN-SPAM requires a physical address and unsubscribe link.
Is email open and click tracking legal? GDPR-compliant?
For B2B one-to-one mail sent on a legitimate-interest basis, open pixels and click rewrites are generally accepted - provided you are transparent. Practical rule: (1) your privacy policy must state "campaign mail is measured for opens and clicks", (2) an opt-out request must stop both sending and tracking, (3) do not share engagement data with third parties outside the sales purpose. Sighthem’s campaign module appends an unsubscribe link to every send and, on unsubscribe, halts sending, the pixel, and click tracking at once - no manual step.
Which free source should I start with?
Order: (1) TradeMap to find the top 10 importing countries by HS code, (2) ImportYeti to scan US-market companies and see what kinds of buyers are active, (3) your own national statistics to read your country’s current market share in that HS code (gap = opportunity). All three are free and doable in one day. Then pay for Volza/Panjiva for deeper coverage.
My reply rates are low, what should I fix?
Three suspects: (1) List quality - unverified emails (>5% bounce) burn your IP and push later mail to spam. Sighthem’s Email Verification service tags every address valid / risky / invalid before send; only let valid ones into the sequence. (2) Subject and first line - replace "Hello, we want to introduce" with a line that names the recipient’s company and a specific angle. (3) Value proposition - drop the self-pitch; show a concrete edge ("X% shorter lead time", "more flexible MOQ", "FX advantage"). Show you understand their context.
What happens if I pick the wrong HS code?
Wrong HS → wrong market analysis → wrong company list. Example: "aluminium profile" is broad; if your product is anodized architectural profile, you need a different code. 6-digit HS is enough on TradeMap; for company-level work in a target country, the local 8-10-digit national code is more precise. With a bad HS, the country’s import volume looks high but it represents a different product family, and your outreach lands flat.
How should I manage leads once I find them with this workflow?
Most critical step. 100 companies from customs data, 30 LinkedIn replies, and 15 email responses get lost in 2-3 weeks if they do not land in one pipeline. Every lead’s source (Customs Data: ImportYeti, LinkedIn, Cold Email), assigned owner, country, HS code, and last-touch date must be visible on one screen. Sighthem enforces this with source tagging, 24-72-168-hour auto reminders, and a per-country profile (Incoterm, sanctions, payment risk).