North Star Metric Tree (Input Metric Cascade)

North Star Metric Tree (Input Metric Cascade)

North Star Metric Tree (Input Metric Cascade)

Use it when you need to break a single north star metric into actionable input metrics to align your team and drive focused growth.

Category

Growth & Metrics

Growth & Metrics

Originator

Brian Balfour

Brian Balfour

Time to implement

1 week

1 week

Difficulty

Intermediate

Intermediate

Popular in

Data & analytics

Data & analytics

Growth

Growth

What is it?

The North Star Metric Tree, also known as the Input Metric Cascade, is a hierarchical model that translates your one "true north" growth metric into a layered set of input and output metrics.

At its core, the framework solves the biggest blind spot in growth strategy: teams obsess over a single high-level metric without clear ownership or levers to pull. You start by defining your North Star – the one metric that best captures customer value (e.g., Weekly Active Users, Net Revenue Retention). From there, you map downstream output metrics that directly move that needle and upstream input metrics that teams can own and experiment on.

This alignment transforms vague KPI targets into a roadmap of tests and investments, ensuring every engineer, marketer, and product manager knows exactly how their work contributes to sustainable momentum.

Why it matters?

When you collapse your entire growth engine into a single North Star without context, you kill focus and stall cross-team collaboration. The Metric Tree forces clarity: every input is a testable hypothesis, every output is a shared goal, and your North Star becomes a living compass. This structure turbocharges retention, pinpoints acquisition levers, and turns random experiments into a coherent growth roadmap.

How it works

Growth co-pilot turns your toughest product questions into clear, data-backed recommendations you can act on immediately.

1

Define Your North Star Metric

Pinpoint the one metric that best reflects core product value and aligns with long-term company goals. Keep it simple and customer-centric.

2

Identify Output Metrics

List 3–5 metrics that have a direct, causal impact on your North Star. For example, if your North Star is DAU, outputs might include "New Sign-ups" and "Feature X Engagement."

3

Break Into Input Metrics

For each output, drill down to 2–3 leading indicators you can test on a daily or weekly cadence. Think activation rates, email opens, or trial conversions.

4

Validate Causality

Use historical data and A/B tests to confirm that movements in each input reliably shift its parent output and, ultimately, the North Star.

5

Assign Ownership and Cadence

Tie every metric to a cross-functional owner and set regular review cycles. This creates clear accountability and accelerates decision-making.

6

Iterate and Optimize

Continuously refine metrics based on test learnings. Drop underperforming inputs, add new levers, and celebrate small wins to fuel momentum.

Frequently asked questions

Growth co-pilot turns your toughest product questions into clear, data-backed recommendations you can act on immediately.

What's the difference between a North Star metric and an input metric?

Your North Star captures overall customer value (e.g., Monthly Recurring Revenue), while input metrics are the daily or weekly levers (e.g., trial-to-paid conversion) that drive that value up or down.

What's the difference between a North Star metric and an input metric?

Your North Star captures overall customer value (e.g., Monthly Recurring Revenue), while input metrics are the daily or weekly levers (e.g., trial-to-paid conversion) that drive that value up or down.

How many levels should my metric tree have?

Aim for three layers: North Star at the top, 3–5 outputs in the middle, and 2–3 inputs per output. Any deeper and you risk complexity; any shallower and you lose actionable granularity.

How many levels should my metric tree have?

Aim for three layers: North Star at the top, 3–5 outputs in the middle, and 2–3 inputs per output. Any deeper and you risk complexity; any shallower and you lose actionable granularity.

Can I retrofit this model onto an existing product?

Absolutely. Start with your current North Star, audit your data to identify real drivers, and rebuild the cascade. Expect pushback, use quick wins to prove the tree's value and win buy-in.

Can I retrofit this model onto an existing product?

Absolutely. Start with your current North Star, audit your data to identify real drivers, and rebuild the cascade. Expect pushback, use quick wins to prove the tree's value and win buy-in.

How do I pick the right input metrics?

Prioritize predictive indicators you can test weekly, own end-to-end, and tie directly to user behavior. If it doesn't map back to your North Star through a clear causal path, ditch it.

How do I pick the right input metrics?

Prioritize predictive indicators you can test weekly, own end-to-end, and tie directly to user behavior. If it doesn't map back to your North Star through a clear causal path, ditch it.

How often should I revisit the Metric Tree?

Treat it as a living document. Schedule a deep dive each quarter and blitz small updates monthly. The goal is agility: adjust levers fast when data shows a misalignment.

How often should I revisit the Metric Tree?

Treat it as a living document. Schedule a deep dive each quarter and blitz small updates monthly. The goal is agility: adjust levers fast when data shows a misalignment.

You've mapped your North Star Metric Tree, now use the CrackGrowth Scorecard to diagnose which input metrics are underperforming and generate data-driven experiments that move the needle.