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Trade and customs data

DataSupplier·13 min read

Trade and customs data reveals what moves between economies, a powerful signal for supply chains, markets and policy. This guide covers sourcing it.

Why trade data matters

Import-export flows show demand, dependency and disruption across products and partners. Trade data underpins supply-chain strategy, market sizing and economic analysis.

The data landscape

  • Trade flows: volumes and values by product and partner.
  • Classifications: HS codes and product taxonomies.
  • Tariffs and rules: duties and trade measures.
  • Shipment-level: bills of lading where available.

Common use cases

Supply-chain dependency and risk, market and competitor analysis, sourcing and tariff planning, and economic research.

Sourcing considerations

Official statistics (Eurostat, UN Comtrade) provide aggregated flows; shipment-level data from some jurisdictions adds granularity but with coverage limits. HS-code harmonisation and revisions need care.

Delivery and governance

Most use cases use batches. Provenance and classification documentation matter. Shipment-level data may carry commercial sensitivities.

In a managed model

A managed partner can combine aggregated and shipment-level trade data, harmonise classifications, and deliver analysis-ready datasets.

Aggregated vs shipment-level

Trade data comes in two broad forms: official aggregated statistics (Eurostat Comext, UN Comtrade) showing flows by product and partner, and shipment-level data (bills of lading where available) offering granular detail with coverage limits. The two answer different questions, macro dependency versus specific consignments, and HS-code harmonisation and periodic reclassifications need care when combining or comparing over time.

Uses and provenance

Trade data supports supply-chain dependency analysis, market sizing, sourcing and tariff planning, and economic research. Classification consistency and documented provenance matter, and shipment-level data can carry commercial sensitivities, so confirm licensing before relying on it.

Key takeaways
  • Trade data reveals demand, dependency and disruption.
  • Combine aggregated flows, classifications, tariffs and shipment-level data.
  • Official statistics aggregate; shipment-level adds granularity with limits.
  • Harmonise HS codes and handle revisions.

Sources & further reading

  • Eurostat (Comext) and UN Comtrade: trade statistics.
  • WTO and WCO: tariffs and HS classification.
  • National customs authorities.
  • Commercial shipment-data providers.
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Logistics & supply-chain data: shipments, ports and freight rates →Supply-chain risk & disruption data →