Building the Product

How do I know when something we shipped is actually working versus just launched?

A starting point

Launching is an event, working is a signal, and founders confuse the two constantly. Before you ship a feature, write down the one number you expect it to move (activation, retention on that flow, repeat use) and a rough threshold, then check it a week later without flinching from a bad result. As a starting point: if you cannot name the metric a feature should move, you are shipping on vibes, and half of what you ship should probably be quietly removed later.

Go deeper

Hand-picked from around the web, each with a note on why it earns your time.

3 resources 3 link-checked

Read

📄 Article
✓ Link checked Freemium Intermediate

Why we picked it When people sign up and vanish, the first fork is: did they never hit the moment where the product clicked (activation), or did they hit it and still leave (a deeper product or fit gap)? This piece gives you a concrete way to find that moment for your own product, brainstorm candidate aha actions, then check with data whether they actually cause retention rather than just correlate with it. That test is what tells you which problem you are staring at, so it is a starting point for the diagnosis, not the whole answer.

How to determine your activation metric

From Lenny's Newsletter by Lenny Rachitsky

  • A good activation metric is causal for retention, not just correlated, so run regression and then experiments before you trust it.
  • Find the specific early action that separates users who stick from users who churn, that is your aha moment made concrete.
  • If people activate and still leave, the problem is likely core product or fit, not onboarding, and you fix a different thing.
Open lennysnewsletter.com
📖 Book
✓ Link checked Paid Intermediate

Why we picked it The book behind the "One Metric That Matters" discipline, which is exactly the mindset you need to judge whether a ship worked instead of drowning in vanity numbers. It ties the right metric to your business type and stage, so you know which signal to watch after a launch. Read it as the reference that makes the rest of this list make sense.

Lean Analytics: Use Data to Build a Better Startup Faster

From O'Reilly / Lean Series by Alistair Croll and Benjamin Yoskovitz 440 pages

  • Pick the One Metric That Matters for your stage and business model, and let it settle the "did it work" argument.
  • Vanity metrics feel good but do not tell you a shipped thing is working: draw a line to real behaviour.
  • Match the metric to where you are (empathy, stickiness, virality, revenue, scale), because the right signal changes as you grow.
Open leananalyticsbook.com
📄 Article
✓ Link checked Free Beginner

Why we picked it The biggest tracking mistake in an MVP is measuring everything and learning nothing. This Amplitude piece walks you through picking one metric that maps to real customer value and finding the early aha moment that predicts whether people stick around, which tells you the few events actually worth tracking. Treat it as a starting point for focus, not a rule: a small product is still learning what matters, so revisit your metric as you go.

Every Product Needs a North Star Metric: Here's How to Find Yours

From Amplitude by Julia Sholtz

  • A good North Star Metric is a leading indicator of value delivered, not a lagging number like monthly revenue.
  • Find the early aha action that predicts retention (the classic example is Facebook users adding seven friends in ten days) and instrument that first.
  • Choosing one metric and a few inputs keeps your tracking small and honest instead of a dashboard nobody reads.
Open amplitude.com

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