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🚢 ImportYeti Scraper — US Customs Importer & Supplier Data

👁 Apify Actor
👁 Python

🤖 Structured supply-chain intelligence in seconds. Pull every public datapoint from ImportYeti — importer addresses, country-of-origin breakdowns, monthly shipment history, top HS codes, trademarks and tags — straight into a JSON / CSV / Excel dataset.

✨ Why this scraper

• ⚡️ Fast — concurrent extraction, 5 records / second under default settings
• 📦 Complete — every visible field from each company/supplier page in one flat record
• 🏷️ Both sides of the trade — US importer "companies" and their foreign "supplier" counterparts
• 🌍 Country-of-origin rollups — pre-aggregated per country & continent
• 📈 Monthly history — shipments, weight (kg) and TEU broken down per month
• 🔁 Incremental mode — since: parameter skips records older than your last run
• 🛡️ Cloudflare-resilient — browser-fingerprint impersonation + your own residential/mobile proxy (via env var)
• 🧾 3 export formats — JSON, CSV, Excel

🚀 Quick start

1. Click Try for free
2. Type a search term (a company name, brand, product, or keyword) — or paste a list of /company/<slug> / /supplier/<slug> URLs
3. Hit Start and grab a coffee
4. Download the result as JSON, CSV, or Excel from the Storage tab

🛠️ Input

🔌 Proxy: set via the PROXY_URL (or HTTPS_PROXY / HTTP_PROXY) environment variable on the actor — every request is routed through it. A residential / mobile proxy is recommended (ImportYeti is behind Cloudflare and blocks datacenter IPs). Format: http://user:pass@host:port.

💸 Saving proxy traffic

Residential/mobile proxies bill by the gigabyte, and detail pages are the cost driver. The actor minimises bytes for you, and you can trade depth for cost:

Tip for recurring monitoring: run fetchDetails: false to list what's changed cheaply, then re-run fetchDetails: true with startUrls for just the records you care about.

📤 Sample output

{
"url":"https://www.importyeti.com/company/apple",
"id":"company/apple",
"scraped_at":"2026-05-10T20:00:10Z",
"type":"company",
"title":"Apple",
"address":"568 Aldi Blvd, Mount Juliet, Tn 37122, Us",
"country_code":"US",
"phone_number":"XXX-XXX-X000",
"website":"apple.com",
"other_names_count":2,
"other_addresses_count":89,
"most_recent_shipment":"01/21/2026",
"total_sea_shipments":2449,
"total_shipping_cost":101746.81,
"shipping_cost_coverage":2.69,
"avg_teu_per_month":0.39,
"avg_teu_per_shipment":0.77,
"database_updated":"05/06/2026",
"multi_address":true,
"dataset":"us",
"uflpa":false,
"location":{
"state":"Tennessee",
"county":"Wilson County",
"city":"Mount Juliet",
"district":"Mount Juliet"
},
"tags":[
{"tag":"puter","shipments":617},
{"tag":"computer","shipments":617},
{"tag":"lithium","shipments":388}
],
"trademarks":[{"name":"Apple","trademarks_count":1620}],
"imports_per_country":[
{"country":"China","continent":"Asia","shipments":2292},
{"country":"Hong Kong","continent":"Asia","shipments":62},
{"country":"Vietnam","continent":"Asia","shipments":37},
{"country":"Germany","continent":"Europe","shipments":11}
],
"top_hs_codes":["8504.40","8517.62","8471.30","8544.42","8473.30"],
"shipments_time_series":[
{"period":"01/01/2024","shipments":32,"weight":89421,"teu":84},
{"period":"01/02/2024","shipments":41,"weight":117850,"teu":102}
]
}

💼 Use cases

💡 Tips & tricks

• Free-text queries match titles, addresses and aliases — "apple" returns 27 hits across companies and suppliers, not just Apple Inc.
• For company-only datasets, set entityType: "company". Suppliers are foreign manufacturers and have a different shape (no trademarks, often no website).
• The since filter uses the most recent shipment date on each record — perfect for nightly incremental runs.
• Want comparable competitors? Run one query per company name, then merge — each result carries a tags array you can use for affinity clustering.
• Large runs (10k+ records) benefit from concurrency: 10 and unlimited maxItems: 0.

❓ FAQ

Q: What data is in each record? A: Every field shown in the sample above — importer name, primary and alternate addresses, phone, website, total sea-shipment count, country-of-origin breakdown, top HS codes, monthly time series, trademarks and keyword tags.

Q: How fresh is the data? A: ImportYeti's database update timestamp travels with each record in the database_updated field, so you always know how recent the underlying customs data is.

Q: Can I get individual shipment-level records? A: This actor returns the public aggregated view (count + breakdowns + monthly history). Individual bill-of-lading records aren't part of the public page surface.

Q: Will this work for non-US companies? A: Yes — the dataset itself is US sea imports, so US-side companies are importers and foreign-side companies are suppliers. Both show up.

Q: How are records de-duplicated? A: By the canonical id field (company/<slug> or supplier/<slug>) — the same company appearing on multiple search pages or via multiple startUrls is pushed once.

Q: What happens if a search slug doesn't have a real page? A: ImportYeti's search occasionally surfaces orphan slugs. The actor detects and silently skips them — they don't count against your run.

📊 Output

Three checkmarks live in the Storage tab — the dataset is exportable as JSON, CSV, and Excel out of the box. Use the Open in Apify Console link for an interactive table view with filtering and sort.

🛟 Found a bug or want a field that's missing? Open an issue from the actor page — we ship fixes fast.