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Module 2 of 6Lesson 2 of 2~16 min

From decisions to metrics, and a definition of activation

Starting from the decision at hand, rather than from the data you happen to have, changes what your team measures and how it reads the results. This lesson helps you set aside flattering numbers that guide no choice and write a definition of activation that the data can confirm or refute. Useful before any onboarding trade-off.

Take this lesson: your first course is freeSee the full syllabus

Lesson objective

By the end of this lesson, you will be able to start from a decision to be made to write the questions and metrics that inform it, tell an actionable metric from a vanity metric, and propose a definition of activation that can be checked against the data.

Questions this lesson answers

  • How do you tell an actionable metric apart from a vanity metric?
  • How do you define user or account activation for a product?
  • How do you go from a product decision to the metrics that inform it?

Topics covered

  • vanity metrics
  • actionable metrics
  • activation definition
  • decision question
  • aha moment

In the glossary

Full glossary

Where it fits

Choose what to measure

Out of everything I could measure, what actually helps the team decide?

Lessons in this module

  1. North Star, input metrics and guardrails
  2. From decisions to metrics, and a definition of activation (this lesson)

What you will learn in this module

This lesson is part of the course Instrument a product and use data to make decisions

  • Build a product's metrics tree (North Star, input metrics, guardrails) from the decisions to be made, and rule out vanity metrics.
  • Turn an analysis into a reasoned decision (dashboard, decision memo) while avoiding interpretation traps (vanity, Simpson, correlation, small counts).

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