Every company in an import record is already buying your product category. Here is how to turn that record into a working prospect list.
Product names vary by market and by company. The HS code does not. Before you search anything, settle on the classification your goods travel under — chapter, heading, then subheading. If you are unsure, look at how comparable shipments were described in the customs record and work backwards to the code customs accepted.
Resist searching everywhere at once. Choose one destination country where you can actually service an order — where your certifications are valid, your logistics work and your price lands. A shortlist of twenty reachable buyers beats two thousand you cannot supply.
| Signal | What it tells you |
|---|---|
| Shipment frequency | Regular monthly buyers have an established need, not a one-off project |
| Volume trend | Growing volumes suggest a buyer adding suppliers, which is your opening |
| Supplier count | A buyer using several suppliers is more open to a new one |
| Declared unit value | Tells you the price band they buy in before you quote |
| Origin mix | Shows whether they already buy from your country |
Check that the importer has shipped consistently over at least a year, that the product description genuinely matches what you sell, and that their declared values sit in a band you can compete in. Skipping this is why most trade-data outreach fails.
Generic introductions get ignored. Referencing the specific product, the volume band and the origin they currently buy from shows you have done the work, and it changes the reply rate materially.
A record set will return every company that has cleared your tariff line, and most of them are not prospects. The difference is not size; it is whether the buying is an operating requirement or an episode. A company clearing consignments in most months has a need that recurs whether or not you contact them. A company with one large clearance eighteen months ago had a project, and that project has finished.
| Attribute | Prospect | Name on a list |
|---|---|---|
| Frequency | Most months, over years | Sporadic or single |
| Recency | Active in the last complete period | Nothing recent |
| Product match | Your line is a core part of their mix | An incidental line among many |
| Scale fit | Consignment size near your order size | Orders of magnitude away |
| Supplier count | Several origins already | One origin for years |
| Price band | Inside the range you can supply | Below your floor |
Every importer already has suppliers, and the record tells you who and roughly at what price. That is the most useful preparation available: it tells you what you are displacing, whether the account is single-sourced or already competitive, and whether your cost base can realistically win. Approaching an account that has bought from one origin at a tight price for a decade is a different exercise from approaching one that switches origins every year, and the two deserve different messages and different amounts of effort.
Referencing the specific product, the volume band and the current origin demonstrates that the approach is considered rather than broadcast. It also self-corrects: where you have misread the record, the recipient tells you, which is more useful than silence. Timing matters as much as content — outreach landing when budgets are set converts differently from outreach landing at random, and the buying calendar is visible in the seasonal shape of the data at no cost.
Two minutes of shipment history prevents most wasted introductions, and it prevents the much more expensive mistake of committing capacity or credit to a buyer nobody checked.
Everything above is a framework, and a framework is only worth what it survives contact with. The useful discipline is to test each assumption against what consignments actually did, because customs data is one of the few commercial sources where the underlying event — goods crossing a border — physically happened and was documented under legal obligation at the time.
Fix the tariff line before anything else. Every filter, every duty figure and every comparison downstream depends on it.
Learn more ›A single period is a snapshot. Three years separate a trend from seasonality, and let you discount the incomplete recent periods.
Learn more ›Frequency and consistency beat size. A steady mid-scale counterparty is usually a better prospect than an occasional large one.
Learn more ›Declared unit values tell you the range you are entering before you quote into it.
Learn more ›Two failure modes account for most wrong conclusions drawn from trade data, and both are easy to avoid once named. The first is reading the incomplete tail of a series as a decline — authorities publish on a lag and revise afterwards, so the last one or two periods will fill in after you look. The second is reading a value movement as a demand movement, when declared value can move because volume moved, because unit price moved, or because the product mix inside a tariff line changed.
Customs data covers goods that crossed a border. It does not cover services, domestic trade, margin, contract terms or intent. Treat it as a dated, quantified observation to corroborate — not as a conclusion that arrives finished.
The difference between teams that get value out of trade data and teams that ran one interesting project is almost never analytical sophistication. It is whether the work became a routine. A saved query reviewed weekly, a short written note against each counterparty you assessed, and a standing habit of checking the period stamp before quoting a figure will out-perform an elaborate one-off study within a quarter, because markets move and a study does not.
The second habit worth building is writing down not just what you concluded but why and when. Records get revised, prices move, and counterparties change behaviour. Six months later nobody remembers whether a supplier was rejected on volume, on price band or on timing, and without that note the assessment simply gets repeated from scratch. A one-line rationale is what converts a list into institutional knowledge, and it costs seconds at the point where the thinking has already been done.
Finally, be explicit with colleagues about the confidence attached to any figure you circulate. A declared value from a complete period, controlled for origin and unit, is strong evidence. The same figure pulled from an incomplete recent period, averaged across a whole chapter, is barely evidence at all — and the two look identical once they are in a slide. Saying which one you have is what keeps trade data credible inside an organisation over time.
Few enough to personalise each approach. A researched list contacted with one generic message stops being a researched list within a week.
Usually not first. The largest are most likely to be locked into established arrangements. Steady mid-scale buyers using several suppliers convert considerably better.
Check the most recent complete period, not the most recent period available — the newest one or two are still filling in and an apparent stop is often reporting lag.
Coverage of counterparty names varies by jurisdiction. Where names are not published, the record still sizes demand, shows origin mix and price band, which is enough to decide whether the market is worth pursuing by other means.
Markets refresh on their customs authority's own release cycle — monthly for most, 45 to 60 days for a few. The most recent one or two periods are always still filling in, so exclude them when you are reading a trend rather than treating the gap as a decline.
Yes. Give us the HS code or a product description and the market you care about, and we will return a sample of live customs records filed against it.
Keep reading
The next questions this one usually raises are covered in How to build a buyer list that converts, Seasonality in trade data and Negotiating with unit price data. Each picks up where this article stops, and together they cover the sequence a consignment actually goes through — classification and duty before anything moves, documentation and payment while it moves, and verification of the counterparty before any of it is committed to. Reading them in that order is usually more useful than reading them by topic.
A long list is easy.
Learn more ›Almost every traded product has a buying calendar.
Learn more ›A declared unit value is not a quotation, but it is the most credible number you can put on a table that you did not get from the other side.
Learn more ›Request a free demo and we will pull live importer records for your HS code.