Send us the product or HS code you trade and we will return a sample of live customs records for it — real importers, real exporters, real declared values.
Actual customs records for your HS code in your target market — not a screenshot of someone else's product.
The most active counterparties trading your product, ranked by shipment volume.
Declared unit values across suppliers so you can see the spread.
A short session showing how to run the searches yourself.
Email us with the details below and we will respond within one business day.
| Tell us | Why we need it |
|---|---|
| Your product or HS code | So we pull the right tariff lines |
| Target country or countries | So we search the right customs dataset |
| Whether you are buying or selling | So we return buyers or suppliers accordingly |
| Your company and email | So we can send the report |
A demonstration on someone else’s product tells you the interface works. A demonstration on your own tariff line, in your own target market, tells you whether the data answers your question — which is the only thing you actually need to know. That is why the useful version starts with you naming the HS code or describing the product, and the market you care about, rather than with a scripted tour.
| Bring | Why it matters |
|---|---|
| An HS code, or a product description | Everything filters from the classification |
| One or two target markets | Coverage depth varies by jurisdiction and this sets expectations |
| A company name, if you have one | Counterparty verification is the fastest credibility test |
| Your typical order size | Tells us whether the counterparties surfaced are relevant |
| The decision this feeds | A buyer list, a price benchmark and a market study need different views |
Real records rather than a mock-up: consignments with dates, declared quantities and values, counterparties where the jurisdiction publishes them, and the ports involved. You should also expect to be told what is not there — which fields the source does not publish for that market, and how recent the latest complete period is. A demonstration that shows only strengths is not a demonstration, it is a pitch.
The most recent one or two are always filling in, and you should be told so.
Every jurisdiction publishes a different field set.
Name variants folded into one profile is a judgement you should be able to inspect.
A view you cannot get out of the tool is worth less than it looks.
Ask to see a market or a counterparty you understand well. Being able to explain any discrepancy is what turns a demonstration into a decision.
A useful sample takes four inputs and returns a concrete artefact. Give us the tariff line or a plain description of the goods, one or two markets, whether you are buying or selling, and roughly what scale you work at. What comes back is a set of real records for that line in those markets: consignments with dates, declared quantities and values, counterparties where the jurisdiction publishes them, and the ports involved — plus an explicit note on what is missing and how recent the latest complete period is.
That last part matters more than it sounds. Every trade dataset has gaps, and a sample that presents only the fields that happen to be full is not a sample, it is a selection. Seeing the blanks is how you find out whether the data supports the decision you actually need to make.
Software demonstrations are designed to show a product at its best, and every trade data platform can be made to look convincing on a well-chosen tariff line in a well-covered market. The only thing that tells you whether a dataset is useful to you is running it against your own product, in your own market, and looking at what comes back — including the gaps. That is the version we would rather do, and it takes less of your time than a tour.
If the records answer your question, the next step is scoping: which markets, at what depth, how much history, and how the data needs to be delivered. If they do not, we will tell you what would be needed and whether it exists anywhere, because pointing someone at a source we do not sell is a better outcome than selling them one that does not fit. Either way there is no obligation attached to a sample.
Trade data rewards a short, boring discipline far more than it rewards technique. Four steps cover most of it, and skipping any one of them is where the confident wrong conclusions come from. Fix the classification first, because every filter, every duty figure and every price comparison downstream is keyed to the tariff line and inherits any error in it. Then read at least three years, so that seasonality and trend can be told apart rather than conflated. Then exclude the most recent one or two periods, which are still filling in as late filings arrive. Then separate value from volume, because a value movement can be price, quantity or a change of mix inside the line, and those point in different directions.
| Step | What it prevents | Cost of skipping it |
|---|---|---|
| Confirm the tariff line | Filtering the wrong product | Every downstream figure is wrong by an unknown amount |
| Read three years | Mistaking a season for a trend | Strategy built on a cyclical high or low |
| Drop the incomplete tail | Reading reporting lag as decline | Writing off buyers who never stopped buying |
| Separate value from volume | Reading price as demand | Investing against a movement that was not demand |
| Check the counterparty | Acting on an unverified name | Credit or capacity committed to a company with no history |
| Record the period and source | Unrepeatable analysis | Figures nobody can reconcile three months later |
The material here is one layer of a set that is meant to be used together. The country pages establish the shape of a market from official reported figures. The HS chapter pages take a single classification down to product level. The industry hubs group the chapters that make up a real industry and sum them, because almost no industry is one chapter. The India location pages read the national record as places, using the clearance point as a geographic signal. And the trade role pages take one job at a time — building an importer list, checking an exporter, reading a lane — and set out the signals that matter for it.
Reported totals, partner markets and chapter breakdown for 99 markets.
Learn more ›All 98 chapters, each with the markets that trade it.
Learn more ›Thirty-eight industries, each summed across the chapters it spans.
Learn more ›Seventy-nine trading places, their gateways and their clusters.
Learn more ›The same record read as a buyer list, a supplier check or a lane analysis.
Learn more ›Classification, documentation, pricing, sourcing and compliance in practice.
Learn more ›Customs records cover goods that physically crossed a border and were declared to an authority. They do not cover services. They do not cover domestic trade, so a business selling mainly inside its own market will look far smaller here than it is. They carry no margin, no contract terms, no payment behaviour and no intent. Coverage of counterparty names varies by jurisdiction and is not universal, data arrives on a lag, and published periods are revised as corrections come in.
None of that reduces what the record is good for, and stating it plainly is what makes the rest credible. Used within its limits, customs data is one of the very few commercial sources where the underlying event actually happened, was documented at the time, and was documented under legal obligation rather than for promotional purposes. That is a rare property, and it is worth not overselling.
Before relying on any trade dataset — ours or anyone else's — ask which markets are covered at which depth, what the lag is in each, how company names were matched, and what happens to a historical series across an HS revision. The answers tell you more than any headline figure.