GenerateRealData logoGenerateRealData
Home › Use cases › User Journeys & Behaviour
User journeys & behavioural patterns

User journeys that drop off like real ones.

Simulate how people actually move through your product: sessions, searches, carts and checkouts, with realistic drop-off at every step and timestamps that add up.

Free trial for every new account. No credit card.

A checkout funnel, event by event: example spreadsheet in a Mac window (checkout_funnel_events.xlsx)
The example

A checkout funnel, event by event

What to look for in the screenshot above. These are the details that usually break in hand-made or random test data.

What you get

01

Weighted transitions

Define steps and the chance of moving between them; every session follows its own path.

02

Time that adds up

Each step's duration matches the gap to the next event, so session length is real.

03

Linked to your users

Sessions belong to real user rows, so you can segment by device, country or plan.

04

Ready for analytics

Load into your warehouse or BI tool to test funnels, cohorts and attribution.

How it works

From idea to dataset in three steps

1

Describe or upload

Describe your data in plain English, or upload your SQL schema for PostgreSQL, MySQL / MariaDB, SQL Server and SQLite.

2

Review the plan

Check the tables, columns and rules the AI proposes, and adjust anything you like.

3

Generate and download

Choose how many rows you need and download a ready-to-run SQL script, CSV, Excel (one sheet per table) or JSON.

Questions

Can I set my own funnel steps?

Yes. Describe the steps and how likely each transition is, or let the AI propose a realistic funnel.

Can journeys differ by device?

Yes. Add rules per segment, such as lower checkout completion on mobile.

Is this useful for testing tracking code?

Yes. It gives your analytics pipeline realistic event streams to process and validate.

Build your own version of this example

Describe your tables or upload your schema. The free trial needs no credit card.

Start free
More use cases
Multi-Table Relational Data Test Data from SQL Schema AI-Written Text Fields Data Quality & Anomalies ML Training Data Load & Performance Testing Demand Forecasting Geospatial & GPS Tracking Fraud & Transaction Data All capabilities