How we recommend your North Star Metric

No black box. The frameworks we draw from, the 14 metrics we consider, the math behind the recommendation, and what this tool deliberately doesn't do.

What is a North Star Metric?

The single number that best captures the core value your product delivers to customers — and that predicts long-term sustainable growth. An effective NSM has four traits: represents customer value, is a leading indicator (not lagging), your team can directly move it, and is expressible in plain language.

The four frameworks we draw from

Sean Ellis (2010, Mixpanel): Established the "one number to align around" doctrine. We adopt the premise — the brief commits to one recommendation, not three.
Cutler & Johns (2018, Amplitude): Distinguished value events from revenue outcomes; introduced the inputs structure. We adopt the driver-tree pattern and the value-event literacy pressure test.
Brian Balfour (2020, Reforge): Argued for a constellation — acquisition + retention + monetization, not one number. We adopt the diagnostic penalties for vanity and counter-metric blindness.
Lenny Rachitsky (2023): Grounded North Star Metric theory in what real companies actually pick — six empirical categories. We adopt his categorization for our 14-metric bank (five of his six; User Experience deliberately excluded).

The 7 context questions

We narrow from 14 candidates to 1 across seven dimensions:

Archetype — SaaS / marketplace / usage-platform / consumer-sub / media (all 4 frameworks)
Sales motion — B2B self-serve / sales-led / hybrid / B2C (Lenny + Balfour)
Monetization unit — seats / teams / usage / transactions / time (Amplitude + Lenny + Balfour)
Free-tier mechanic — freemium / trial / paid-only (Lenny)
Revenue stage — 8 tiers from pre-revenue to $1M+ (Lenny)
ACV band — under $1K / $1K–10K / $10K–50K / $50K+ (Balfour Model-Market Fit)
Usage cadence — daily / weekly / monthly / event-driven (Balfour + Amplitude)

The 14 metrics we consider

Eight are native to our engine (driver trees auto-derived from the metric library's equations). Six are external — flagged honestly because they sit outside our subscription engine but are genuinely the right answer for some shapes: GMV (marketplaces), Consumption Volume (usage platforms), WAU + Engagement Time (engagement-driven products), LTV:CAC Ratio (needs CAC from marketing layer), Paid Active Teams (engagement-quality data lives in product analytics).

The scoring formula

score = base + acv_bonus + cadence_bonus + monetization_match + hypothesis_bonus − pressure_penalties

Base (0–4): Stage × Archetype × Sales motion fit
ACV bonus (0–3): Adjusts for deal size — high ACV → CLV; low ACV → MRR Movement / LTV:CAC
Cadence bonus (0–2): Daily cadence rewards engagement metrics
Monetization match (0–2): +2 when an NSM literally counts what the customer pays for
Hypothesis bonus (0 or +2): Your guess gets a thumb on the scale if it's eligible
Pressure penalties (0 to −6): Diagnostic answers can demote a hypothesis

Tie-break: hypothesis-match → base weight.

The 4 pressure-test questions

Counter-metric uncertainty (max −1) — "If you doubled this metric tomorrow, what's the first bad thing that could happen?"
Vanity-metric exposure (max −2) — "Tell us about a month you hit your metric target but the company felt worse."
Value-event literacy (max −1) — "Is your metric something your customers DO, or something that HAPPENS as a result?"
Operational alignment (max −2) — "When the team gathers around your metric, you're usually..."

What this tool isn't

A substitute for cohort analysis. A replacement for strategy debate. A permanent answer (reassess every 12–18 months). A replacement for your finance dashboard.

Sources

Sean Ellis on the North Star Metric (Mixpanel, 2010)
Amplitude — The North Star Framework (Cutler & Johns, 2018)
Amplitude — What makes a good vs. bad NSM (2019)
Brian Balfour — Don't Let Your North Star Metric Deceive You (2020)
Reforge — How to Choose & Measure NSMs (2021)
Lenny Rachitsky — Choosing Your North Star Metric (2023)