Analytics and monitoring decision
DataFast
A competent developer can reproduce the core revenue-attribution workflow (tracking, join payments, compute attribution, simple dashboard) in a self-hosted project; the vendor's value is primarily hosting, integrations, polish and scale rather than proprietary data or an insurmountable moat.
Visit website↗Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need — the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship.
What a replacement has to do
- Collect page and event telemetry, ingest payment events, join visitor sessions to payments, compute attribution per visit/customer, surface revenue-by-channel metrics and journeys in a simple dashboard.
What it still won’t have
- Hosted ingestion, scaling, and uptime guarantees
- Built-in integrations (Stripe, Shopify, LemonSqueezy) out of the box
- Polished mobile apps, CLI, MCP server, and prebuilt AI agent integrations
- Managed data retention, backups, and compliance packaging
What remains hard
- Product polish and ongoing maintenance
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 1 seat.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a self-hosted minimal revenue-attribution analytics service using Node.js (Express) + PostgreSQL (or ClickHouse) + React. In scope: a lightweight JS tracking script that preserves visitor/session IDs and supports cross-domain URL params; a secured HTTP ingestion endpoint to accept page events and payment webhooks (Stripe example); a schema and ETL to join visitor sessions to payments; an attribution SQL module implementing first-touch and last-touch models; a React dashboard showing revenue-per-channel, revenue-per-visitor, simple funnel and a per-visitor journey view; a JSON API to export matched visitor->payment journeys. Out of scope: mobile apps, advanced bot-detection, managed multi-tenant billing, and LLM/agent integrations. Include input validation, error handling, basic tests for ingestion and attribution logic, and deployment scripts (Docker + docker-compose).
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 3 cited sources+3
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Evidence score67
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time — so the same evidence always produces the same number.
How scoring works →Cited sources · 3
Every page the run actually retrieved.
- official productDataFast | Find out which marketing channels drive your revenue
- official docsTrack visitors across different domains — DataFast Documentation
- open sourcedubinc/dub
Integrity checks
What held up, and what did not.
