6 resources from Amplitude we point founders to, and the questions each answers.
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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.
Why we picked it
You cannot cut the right step until you know which step is the real cliff, and a funnel chart shows you exactly that. Amplitude lets you lay out your onboarding as a sequence of events and see the percentage who fall off at each one, so you fix the actual drop rather than the step that merely annoys you. The free tier is enough for an early-stage product to instrument this.
Why we picked it
This gives you the mental picture and the evidence in one place: a bucket full of holes barely fills no matter how fast you pour, which is exactly what a weak funnel plus weak retention feels like. It is backed by a benchmark study of 2,600 plus companies showing acquisition skill and retention skill do not correlate, so being good at one tells you nothing about the other. That is the honest diagnostic for deciding where your real leak is before you spend on either side.
Pouring more users in through acquisition does nothing if retention leaks them out, so measure the hole before you widen the tap.
Across 2,600 plus companies, how well you acquire and how well you keep users show no meaningful correlation, so treat them as separate problems.
Fast time to value in onboarding is the strongest predictor: 69 percent of top week-one activation performers were also top three-month retention performers.
Why we picked it
This playbook helps you name the single metric that represents the value your product delivers, plus the few inputs that move it. Choosing it is a strategy exercise, which forces you to decide what learning actually matters. Use it to pick the come-back or aha moment worth measuring.
Why we picked it
Watching sessions tells you the story; a cohort retention curve tells you the numbers, and this guide walks through building one so you can see whether it flattens or falls to zero. It shows why aggregate retention hides the truth and how grouping users by signup week exposes whether recent changes are helping. This is the how to behind the 'retention curve' language in your answer.
Why we picked it
A practical walkthrough of building only the button or menu item for a feature that does not exist yet, then measuring who clicks it, as the fastest way to see whether a struggle is real enough for people to reach for a solution. Good for testing one specific idea inside something you have already partly built.
