---
license: cc-by-nc-4.0
task_categories:
- tabular-classification
- tabular-regression
language:
- en
tags:
- subscription
- invoices
- synthetic-data
- mindweave
- billing
- recurring-revenue
- saas
- cohorts
- stripe
- test-data
- mrr
- churn
- saas-metrics
- revops
- payments
pretty_name: Subscription Billing (Synthetic) (Free Sample)
size_categories:
- 1K<n<10K
configs:
- config_name: customers
  data_files: data/customers.csv
  default: true
- config_name: invoices
  data_files: data/invoices.csv
- config_name: payments
  data_files: data/payments.csv
- config_name: subscriptions
  data_files: data/subscriptions.csv
---

# Subscription Billing (Synthetic) (Free Sample)

> **This is a free sample** with 4,800 rows. The full dataset has **52,483 rows** across 6 tables.

SaaS subscription billing dataset covering customer acquisition, trial
conversion, invoicing, payments, plan changes, and churn over a two-year
growth period. Includes monthly recurring revenue expansion, mixed billing
cadences, dunning outcomes, and cohort-based retention patterns that match
realistic B2B SaaS finance and RevOps workflows.

The dataset encodes a pricing change in month 10 that temporarily increases
churn, while trial-to-paid conversion is held at 22 percent. Useful for
MRR analytics, churn modeling, payments reporting, subscription lifecycle
automation, dashboard demos, and finance data engineering tests.


## Sample tables

| Table | Sample Rows |
|-------|------------|
| customers | 500 |
| invoices | 2,000 |
| payments | 1,800 |
| subscriptions | 500 |
| **Total** | **4,800** |

## Full dataset

The complete dataset includes all tables with full row counts:

| Table | Full Rows |
|-------|----------|
| churns | 170 |
| customers | 5,000 |
| invoices | 21,250 |
| payments | 20,493 |
| plan_changes | 570 |
| subscriptions | 5,000 |
| **Total** | **52,483** |

**Formats included:** CSV, Parquet, SQLite

**[Get the full dataset on Gumroad](https://mindweavetech.gumroad.com)**

## About

Generated by [Mindweave Technologies](https://mindweave.tech) -- realistic synthetic datasets for developers, QA teams, and data engineers.

Every dataset features:
- Enforced foreign key relationships across all tables
- Realistic statistical distributions (not uniform random)
- Temporal patterns (seasonal, time-of-day, day-of-week)
- Injected anomalies for ML training and anomaly detection
- Deterministic generation (same seed = same output)

Browse all datasets: [https://mindweavetech.gumroad.com](https://mindweavetech.gumroad.com)