Module
Module 2 of 6Lesson 1 of 2~18 min

North Star, input metrics and guardrails

Picking a North Star that reflects the value customers get keeps a team from steering by revenue alone. This lesson shows how to connect it to concrete levers split across teams, and how to protect each lever against the side effects it can trigger. Every project on the roadmap then ties back to a number everyone understands.

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

Lesson objective

By the end of this lesson, you will be able to propose a product's North Star, break it down into a tree of three to five input metrics a team can act on, and choose the guardrail metrics that prevent it from being improved at customers' expense.

Topics covered

  • North Star metric
  • metrics tree
  • input metrics
  • guardrail metrics

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 (this lesson)
  2. From decisions to metrics, and a definition of activation

What you will learn in the course

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.
  • Design an implementable tracking plan (events, properties, naming convention, identity and accounts, emitting source, owners).
  • QA and monitor event collection to get reliable data, and know what to do when it is not.
  • Collect usage data in line with the GDPR and the CNIL rules (consent, audience measurement exemption, minimisation, retention period).
  • Analyse a conversion funnel, activation and cohort retention, and interpret the resulting curves correctly.
  • Choose a product analytics tool (PostHog, Amplitude, Mixpanel, GA4, data warehouse) based on needs, constraints and cost.
  • Turn an analysis into a reasoned decision (dashboard, decision memo) while avoiding interpretation traps (vanity, Simpson, correlation, small counts).

Related courses