The structured, SKU-level record of Southeast Asian ecommerce.

One row is one SKU in one month, with the whole category tree attached.

Real rows from the live dataset — not a mock. Nine of 32 fields shown; every row also carries local-currency pricing, stock, merchant location and the full three-level category tree.

No signup, no email — the sample is a real export of one category-month. Take the CSV to open it in a spreadsheet; take the Parquet if it is going into a warehouse, where it loads faster and lands with its column types already correct.

Reusable structured intelligence for the decisions a category or brand team makes every month.

Each row is already scraped, cleaned and labelled — the work an on-demand fetch does not do for you.

Every market and marketplace we can sell you, with the gaps left visible.

Read from the export catalog — the same source that prices and delivers your export, so what you see here is exactly what is buyable. Coverage is not uniform: only Indonesia has all five marketplaces, and history depth varies by market and category.

Latest refresh covers through August 2026. The catalog endpoint returns the same ranges per category — see the quickstart. A dash means we do not sell that combination, not that the marketplace is missing from the region.

You see the exact price before anything is charged.

Prepaid credits, billed per row actually returned. Failed and empty queries cost nothing, and a dry-run estimate is always free — so the size of a pull is never a surprise.

Estimate, then export. Two calls.

Bearer auth, one key across both APIs. The estimate returns the exact row count and price and charges nothing, so nobody commits budget to a number they have not seen.

curl -X POST "https://api.magpieiq.com/data/v1/exports" \
  -H "Authorization: Bearer mgk_live_..." -H "Content-Type: application/json" \
  -d '{"country":"ID","category_3":["Facial Serum"],
       "date_from":"2026-01","date_to":"2026-05","estimate":true}'

# same call without estimate:true — returns a job id to poll,
# then signed download links for each category and month.
curl -X POST "https://api.magpieiq.com/data/v1/exports" \
  -H "Authorization: Bearer mgk_live_..." -H "Content-Type: application/json" \
  -d '{"country":"ID","category_3":["Facial Serum"],
       "date_from":"2026-01","date_to":"2026-05","format":"parquet"}'

Scraping jobs follow the same shape against the Scraping API. Every endpoint and parameter is in the reference, and production pipelines — S3, Airflow, warehouse loads — are in the recipes.