Analytics and monitoring decision

Baremetrics

A capable engineer can build a useful subset (ingestion, MRR/cohort computation, segmentation and dashboards) in a week and maintain it cheaply, but Baremetrics' paid value comes from add-ons (dunning, enrichment), broad integrations, and polish that are expensive to fully replicate.

Visit website
You pay

$49/mo

$588/yr

Read off the official pricing page.

You’d pay instead

$50one-off30 h to build

$0/mo8 h/mo upkeep

On cash alone, building overtakes the subscription at 1 seat.

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. All Baremetrics alternatives, with the arithmetic →

What a replacement has to do

  • Ingest billing events, normalize into a time-series/ledger, compute subscription metrics (MRR, ARR, churn, cohorts), and visualize/filter those metrics by segments

What it still won’t have

  • Payment Recovery (dunning + automated recovery flows)
  • Cancellation Insights product with in-app popups and automated post-cancel emails
  • Built-in Clearbit data enrichment
  • Benchmarks / aggregated industry comparisons
  • Wide, maintained set of one-click integrations and dedicated support

What remains hard

  • Brand trust+900 companies using Baremetrics for growth
Read the build prompt

First-year cost

Keep paying

Paying is—cheaper in year one.

On cash alone, building overtakes the subscription at 1 seat.

Paid seatsseats

Money you would actually spend

Keep paying
—

Subscription price × seats × 12

Build it
—

AI build —APIs + hosting —

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

Not run yet
Build a minimal subscription-analytics service using Node.js (Express) + Postgres + a React dashboard. In scope: webhook ingestion for Stripe, a normalized ledger schema, nightly ETL jobs computing MRR/ARR/churn and cohort tables, a SQL-driven segmentation engine, REST API endpoints for dashboard data, and a React UI with historical charts and side-by-side segment comparisons. Out of scope: automated payment recovery/dunning flows, paid data enrichment (Clearbit), industry benchmark aggregation, and multi-provider one-click installers. Include auth, per-account config, retries/error handling for webhooks and ETL jobs, tests for ingestion and metric computations, and basic deployment scripts (Docker + single-node managed Postgres).
How we checked5 sources · 2/3 runs agreed · evidence score 63

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
  • Evidence score63

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.

Integrity checks

What held up, and what did not.

✓ Price read off the page! 2 of 3 runs agreed; the verdict is the majority✓ Citations limited to fetched pages! 1 moat quoted from the page