randarium
Datasets

Fake Order Dataset Generator

Create reproducible fake orders with products, amounts, dates, and statuses for demos and import testing.

Also known as: mock orders · dummy sales data

seeded · synthetic data

Output

No output yet — set your options and hit .
About this tool, tips & examples

What it does

The Fake Order Dataset Generator creates clearly synthetic e-commerce orders — products, quantities, amounts, order dates, and statuses — up to 10,000 rows per run, bounded by a start and end date so the order timeline matches your scenario. Seeded output regenerates identically anywhere, and exports as CSV, JSON, NDJSON, or TSV.

Common use cases

  • Storefront and admin demos — order lists, detail pages, and refund flows with realistic-looking history.
  • ETL and import testing — reproducible order files for pipeline validation, dedupe logic, and incremental-load tests.
  • Analytics examples — revenue-over-time, status funnels, and average-order-value charts with sensible inputs.
  • Load testing — bulk order batches for pagination, search, and aggregation performance.

Settings

  • Rows — 1 to 10,000 orders per run.
  • Start / End date — the window order dates are drawn from; align it with your reporting period.
  • Seed — the same seed and settings regenerate the identical dataset — stable fixtures for tests and demos.

Privacy note

Orders are generated locally in your browser and never uploaded. Every order is fictional — synthetic customers buying synthetic products — and must not be presented as real sales data.

FAQ

Can I generate a specific quarter of orders? Yes — set the start and end dates to the quarter and every order date falls inside it, which keeps time-bucketed charts meaningful.

Are amounts and statuses distributed realistically? They’re plausible for demos and testing — varied statuses and sensible amounts — rather than calibrated to any real store’s economics.

How do I get matching customers or products? Pair with the Fake User and Fake Product dataset generators, or use the Synthetic Dataset tool’s order template when you want schema control (field selection, renames, null rates) in one place.