Why analytics keeps slipping
Most small teams do care about data: sign-ups, activation, where people drop off. The blocker isn’t interest. It’s that every event means finding the right line of code, adding a call, opening a PR, and waiting for deploy. When you’re small, that work keeps losing to shipping. So “we’ll add analytics next quarter” never lands.
Tagging before instrumentation
Developers usually jump straight to instrumentation. They reach for an SDK, write track() calls, and wire things up. The problem is that instrumentation assumes you’ve already done the step that usually gets skipped: data tagging. Tagging is deciding what to track, what to call it, and where in the code it belongs. Without that, you’re either guessing at placement and names or you’re stuck in “we should track something here” without a clear plan. Instrumentation is the part everyone talks about. Tagging is the vital step before it. Once you treat tagging as its own step, the right tool is the one that does that step for you, then gets out of the way.
What actually helps
You don’t need a data warehouse. You need a short list of events that map to questions you care about (e.g. sign-up, first value, upgrade) and a single place they land (Firebase, GA4, etc.). Good enough means clear event names, a few useful params, and enough coverage to see funnel and key actions. No magic. Just “track this so you can answer that.” That’s the outcome of good tagging; instrumentation is what happens after.
How Maslo fits in
Maslo is built for solo devs and tiny teams. It does the tagging step: it reads your repo, infers what to track and where, and hands you a minimal plan with concrete insertion points and the actual code. Nothing gets sent to the cloud; analysis runs on your machine. You run the CLI, open the dashboard, and you see recommendations in plain language (“Track X so you can answer Y”) with event names, params, and the exact file and line. One click generates a patch (e.g. a track() call). You get a diff; you commit when you’re ready. So tagging is handled; instrumentation becomes a review and a merge. No new workflow to learn. Maslo plugs in as the layer that was missing: the step before you write the first track().
How we’re different
Some tools autocapture everything and you filter later. Quick to start, messy for privacy and governance. Others are built for big teams with dedicated data folks. Maslo is code-first and minimal. Analysis is local; recommendations are tied to real code (routes, components, handlers); you always see a diff before anything lands. We’re not replacing analytics or BI. We’re filling the tagging gap so that when you turn on Firebase or GA4, the events you need are already there.
What we suggest
Recommendations depend on your codebase, but typical ones include sign-up and login (with method), onboarding or first-value moments, activation actions (e.g. first export or share), upgrade or plan changes, and important API calls. Each suggestion in the dashboard points to the exact insertion point and gives you a one-click insert and a reviewable diff.
Give it a shot
If you’ve been meaning to add analytics someday, run this in your repo:
npx maslo-tags
You’ll get an indexed view of the codebase, a short list of recommendations with real insertion points, and the ability to add Firebase-style events with a click and review the change. No CDP, no pipelines. Just a minimal plan and code ready to deploy.
Where we’re at
Right now we focus on Firebase/GA4-style events. We don’t do Segment pipelines or warehouses. Framework support is early (Next, Remix, React SPAs, Node APIs are most likely to work). If your stack is different, we’d love to hear from you so we can prioritize.