Home
Open-source subscription analytics — compute and visualize MRR, ARR, LTV, retention, churn, and more from your billing data.
Wiki¶
A compounding knowledge base — entity and concept pages maintained by an LLM agent as new sources arrive, rather than documents re-read on every question.
- How It Works — the three-layer pattern: raw sources, wiki, schema
- Catalog — every page with a one-line summary
- Log — chronological record of ingests, queries, and lint passes
Start with the catalog. Highlights: Metric Transparency (the project's core thesis), MRR, and the competitor pages for ChartMogul and Baremetrics.
Architecture¶
Implementation plan for the analytics engine.
- Overview — event-driven system design with Kafka
- Events — internal event schema and Kafka topics
- Database — PostgreSQL schema, ER diagram, and rationale
- Connectors — webhook translators for Stripe, Lago, Kill Bill
- Metrics — metric plugin system with self-managed tables
- API — FastAPI endpoints
- Development - Local development
- Deployment — Docker Compose on Hetzner, path to Kubernetes
- Testing — Stripe Test Clocks, seed scripts, webhook forwarding
Research¶
Background research and competitive analysis that informed the product direction.
Market & Models¶
- Market Overview — subscription economy sizing, trends, and key metrics
- Business Models — subscription model types and where they fit
Pricing & Billing¶
- Pricing & Billing Strategies — pricing models, billing mechanics, and optimization
- Billing Engines — comparing Stripe Billing, Lago, and Kill Bill
Competitive Landscape¶
- Analytics Tools — ChartMogul, Baremetrics, ProfitWell, and SaaSGrid
- Competitive Matrix — side-by-side feature comparison and gap analysis
Product¶
- Product Positioning — where this project fits and why it should exist