Can AI replace DataFast?

KINDA · weekend project

price $9/moyou'd save $108/yrbuild time weekend for the dashboard, multi-day to trust the numberscategory 📊 analyticsreplaced by 0 peoplebuild unverified

The pageview half of DataFast is the same weekend build as Plausible or Umami. The revenue half is where it stops being a weekend. Attribution is only worth anything if the anonymous visitor who found your launch post on a phone is still recognisably the customer who pays from a laptop three weeks later, and that stitching is exactly what an agent will hand you a naive version of. A localStorage id plus an email match at signup does get you a channel table that is directionally right for a single-domain solo product, which is genuinely worth having. It also quietly under-counts every cross-device path, every privacy browser that clears storage between visits, and every customer who pays with a different address than they signed up with. You can build the dashboard in a weekend. Trusting it enough to move ad spend is the part that keeps costing you weekends.

the prompt

Build me a revenue attribution dashboard for one site, to replace DataFast. Requirements:

- Node + Express + better-sqlite3, one process behind Caddy on my own VPS.
  Server-rendered pages, no frontend framework, no build step.
- A tracker snippet under 2 KB: navigator.sendBeacon sends path, referrer and
  any utm_* params, keyed to a first-party visitor id in localStorage. No
  third-party cookies.
- Attribution is the whole point. Per visitor store first-touch and last-touch
  channel, from utm_source/utm_medium/utm_campaign, else by parsing the
  referrer host into google / x / reddit / hn / direct. Never overwrite
  first-touch.
- An /identify endpoint I call after signup with the user's email, which binds
  the anonymous visitor id to a customer row.
- A Stripe webhook for checkout.session.completed, invoice.paid and
  customer.subscription.deleted: verify the signature, match on email, write
  revenue against that visitor. Webhook secret and API key from .env.
- Dashboard on localhost behind one bearer token from .env: a channel table
  with visitors, signups, customers, MRR and revenue per visitor over 7/30/90
  days. Tables and one inline SVG bar chart, nothing else.
- Drop known bots against a user-agent blocklist before anything is counted. No
  accounts, no telemetry, one SQLite file I can copy off the box.
- Out of scope: cross-device identity stitching, multi-touch models, the live
  visitor feed, purchase-likelihood scoring, team seats and an MCP server. One
  domain, single-touch, single-device.
- README: the script tag, the /identify call, `stripe listen` for testing
  webhooks locally, and an honest paragraph on where the numbers lie · a
  phone-to-laptop journey counts as two visitors, cleared localStorage counts
  as a new one, and a customer who pays from a different address never matches
  at all.

$ open in your agent (prompt prefilled, you press enter) or copy it raw

why people still pay

An attribution number you do not trust is worse than no number, because you spend against it. Paying keeps someone else maintaining the bot filters, the Stripe and Shopify connectors and the retention window while you sell, and at $9 a month that is cheaper than the weekend each quarter you would spend keeping your own version honest.

what you lose

xidentity stitching across devices, browsers and cleared storage

xbot and AI-crawler filtering that stays current without you

xone-click installs for Shopify, Webflow, WordPress and 20 other platforms

xthe live visitor feed and purchase-likelihood scoring

xthe hosted MCP server and CLI for querying the data in plain English

prior art · use these instead of building, if you'd ratherPostHogOpen source and self-hostable, with revenue analytics and channel attribution already built↗PlausibleOpen source analytics with goals and revenue goals; the Stripe join is still yours to write↗UmamiLightweight self-hosted analytics with UTM tracking and no revenue side at all↗