Analytics and monitoring decision
Usermaven
A capable engineer can build a usable subset (event collection, identity stitching, attribution, simple dashboards) over several weeks, but reproducing the full product (AI insights, polished ad/CRM syncs, white-label enterprise features, ad-blocker bypass and scale) is larger work and likely not worth reimplementing for teams that need those features now.
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 data, stitch sessions into users, compute multi-touch attribution, and present dashboards of funnels/journeys
What it still won’t have
- Maven AI — AI-powered automated insights and summaries
- Built-in ad-platform conversion sync and CRM connectors (HubSpot, Google Ads, Meta)
- White-label and enterprise features (private-cloud, SSO, audit logs)
- Ad-blocker bypass / plug-and-play server-side tracking polish
- Prebuilt dashboards, reports, and guided setup services
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 2 seats.
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 analytics stack in Node.js + Postgres (or ClickHouse) + React. Scope: implement a client tracking JS snippet, a server-side collector endpoint that persists events, a nightly job to run identity stitching (cookie id, optional CRM email import), a simple multi-touch attribution computation over a 365-day lookback, and a React dashboard with basic funnels, top channels by attributed revenue, and event search. Out of scope: white-labeling, managed CRM/ad-platform connectors, advanced AI insights. Include input validation, error handling, logs, automated tests for ingestion and attribution logic, and deployment Dockerfiles plus a small DigitalOcean/AWS cost estimate.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 5 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 · 5
Every page the run actually retrieved.
- official productUsermaven homepage (products/features)
- official pricingUsermaven pricing & plans
- official docsProduct analytics features
- open sourcePostHog/posthog
- open sourcematomo-org/matomo
Integrity checks
What held up, and what did not.
