Synthetic Data for Ecommerce

Describe your store in a sentence, for example handmade ceramics with 3,000 customers and revenue rising from $40,000 to $110,000 over a year, and Misata Studio builds the whole store: customers, a product catalog written for what you sell, orders with a real lifecycle, line items, payments, returns and reviews. Order totals come from their line items, each month's revenue lands on your figure, and a certificate lists every number you asked for and whether it was met.

Updated 2026-09-24.

You would write

An online store with 3,000 customers selling handmade ceramics. Revenue rises from $40,000 in January 2025 to $110,000 in December 2025 with an 8% return rate.

Studio builds this on one of its tested archetypes: the mechanics below are fixed and verified, and what the business sells, the names and the wording are written for yours.

Start from this

What Studio builds

customersNames, emails, cities and phone numbers that agree with the country
productsA catalog written for what your store sells, with prices at believable levels
ordersPlaced, paid, shipped, delivered or cancelled, with a timestamp for each step taken
order_itemsThe lines of each order; the order total is their sum
paymentsOne per paid order, for exactly the order's total
returns and reviewsEach points at the item it concerns; review text agrees with its rating

What holds, and how you know

These are checked on the finished data, not assumed. Each dataset comes with a certificate listing what you asked for and whether it was met. How we verify.

  • An order's total equals the sum of its line items, and its payment equals the order
  • Monthly revenue lands on the curve you state, to the cent
  • A return rate you state is exact, and every return points at an item that was ordered, dated after the order
  • Seasons, holidays and weekly rhythm follow the store's region
  • Every foreign key points at a row that exists, checked on the finished data
  • Every count, total, rate, share and date window you state is applied exactly, or listed as not applied
  • A certificate lists each requirement and whether the data meets it
Free sample dataset

A ready-made storefront dataset to download and open right away.

See the sample

Have a schema, specialised rules or a large volume and would rather hand it off? Ask us to build it for you.

Frequently asked

Do I need real ecommerce data to generate this?
No. Misata Studio builds the dataset from a description, a schema you draw, or a structure you import (SQL DDL, DBML or a CSV header). No real records are uploaded, copied or learned from, so there is nothing to anonymise.
Is the generated ecommerce data privacy safe?
Yes. Nothing is learned from real records, so no real person, customer or account can appear in the output. A model writes names, places and wording, and Studio may research public facts on the web (you can turn research off). It never asks for your data.
Can I control the numbers, like rates and totals?
Yes. State a total, a monthly curve, a share or a rate in plain words, or draw the curve, and Studio applies it exactly. The certificate lists each figure and whether it was met. If a figure cannot be met, Studio says so instead of changing it.
Can I use my own schema?
Yes. Paste SQL DDL or DBML, import a CSV structure, or draw the tables on the canvas. A schema you give is followed exactly, and any difference is reported.
Which formats can I export?
CSV, Excel, Parquet, JSON Lines, SQL for Postgres, MySQL, SQL Server, Oracle, BigQuery and Snowflake, SQLite, DuckDB, dbt seeds, Prisma, DBML, TypeScript, JSON Schema, a data dictionary and more.
Will the products fit my store?
Yes. The catalog, categories and prices are written for the business you describe, so a ceramics shop sells mugs and planters, not phones.