Coverage is table stakes. What decides whether trade data earns its keep is how fast it gets you to a name, a number and a next step.
Named counterparties, declared values and quantities — not aggregated category totals you cannot act on.
No stitching together country-by-country subscriptions or reconciling incompatible formats.
Search the way customs classifies goods, from 2-digit chapter down to the national tariff line.
Enriched company details come with the plan rather than as a metered add-on.
Most markets updated monthly, so you are working from current movements rather than last year's.
Excel and CSV export on every plan; API and scheduled reports on Enterprise.
Prebuilt views for the questions traders actually ask: who buys this, who sells it, at what price.
Help from people who understand HS classification and customs process, not a generic ticket queue.
| What matters | Typical directory site | EximDataProvider |
|---|---|---|
| Source of listings | Self-registered company profiles | Customs and bill of lading filings |
| Proof of trading | None | Shipment history with dates and volumes |
| Price visibility | None | Declared unit values |
| Coverage | Fragmented by country | 200+ countries in one search |
| Freshness | Whenever a company updates itself | Monthly customs releases |
The fastest way to judge trade data is against a product you already know well. Request a free demo and check our records against what you know to be true.
A directory can list a company that has never shipped a single container. A shipment record cannot exist without a real, declared movement of goods — that is the difference a free demo will show you immediately.
Most trade data providers describe themselves in the same terms, so the useful comparison is not on adjectives but on the handful of properties that change what you can do. Whether counterparty names are available in your markets. Whether the classification goes to the national line. How company name variants are resolved. What happens to a historical series across an HS revision. And whether missing fields are left blank or quietly filled.
| Property | Why it changes your work |
|---|---|
| Counterparty coverage by market | Decides whether you can build a buyer list at all |
| Classification depth | Duty and preference attach to the national line, not to six digits |
| Entity resolution method | Determines whether supplier counts and volumes mean anything |
| HS edition handling | Decides whether a multi-year series is continuous or silently broken |
| Treatment of blanks | An estimated field is indistinguishable from a real one downstream |
| Stated lag per market | Determines whether a recent gap is a decline or a reporting artefact |
The practical cost of fragmented coverage is not the licence fees; it is the reconciliation. Different providers use different classification depths, different period conventions, different entity resolution and different treatments of missing data. Assembling a view across three of them consumes analyst time indefinitely and produces figures nobody quite trusts. A single consistent treatment across markets is worth more than the sum of its coverage.
Named markets and named fields, rather than a headline country count.
Per market, because it varies and it changes how you read a recent gap.
The method, and the variants folded into a profile.
Services, domestic trade, margin and intent are outside it.
Run any provider against a market or a counterparty you understand well. What matters is not whether the numbers match your expectation, but whether the differences can be explained.
The cost of stitching together several regional providers is rarely the licence fees. It is that each uses a different classification depth, a different period convention, a different approach to company name matching and a different treatment of missing fields. Assembling a cross-market view from them consumes analyst time indefinitely and produces numbers that nobody in the room quite trusts, which is the worst possible outcome for a dataset whose entire value is that it is more reliable than opinion.
Run any provider against a market or a counterparty you already understand well. You are not looking for the numbers to match your expectation — they often should not. You are looking for whether every difference can be explained: a definitional basis, a period boundary, a classification choice, an entity resolution decision. A provider who can explain the differences is one whose numbers you can build on. One who cannot is selling you a black box.
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.