North Star Metric Template
Value moment, north star definition, checklist and rejected candidates, input metric tree with decomposition, guardrails, review cadence, change log
Cómo usar: Use it when a product team needs one metric for customer value and the inputs that drive it. Fill the value moment and the definition first, then the input tree and guardrails. The main pitfall is choosing revenue or a vanity metric as the north star.
Vista previa
North Star Metric: [Product name]
A north star metric definition: the single metric that best captures the value customers get from the product, the tree of input metrics that drive it, the guardrail metrics that must not get worse, and how the metric is calculated, reviewed and changed. There is no formal standard; the template follows common product practice (the North Star Framework popularised by Amplitude's North Star Playbook) in original words. Define each metric precisely in a data/metric-definition document and link it here. Replace every
[bracketed]value and every row marked Example.
Document control
| Field | Value |
|---|---|
| Document ID | [NSM-PRODUCT-NN] |
| Product | [Product name] Example: Tallow Notes |
| Version | [0.1] |
| Status | [Draft / Approved / Under review / Retired] |
| Owner | [@head-of-product] |
| Data owner | [@analytics-lead] |
| Approvers / reviewers | [@leadership, @engineering-lead] |
| Linked strategy | [product/product-vision-strategy document ID] |
| Last updated | YYYY-MM-DD |
Revision history
| Version | Date | Author | Change |
|---|---|---|---|
| 0.1 | YYYY-MM-DD | [@owner] | First definition |
| [1.0] | YYYY-MM-DD | [@owner] | [Approved, baseline recorded] |
1. Value the product delivers
Core value moment: [When does a customer get the value they came for?]
Example: A Tallow Notes team gets value when knowledge written by one member is used or extended by another, so the team stops relying on one person's memory.
2. North star metric definition
| Field | Value |
|---|---|
| Name | [Metric name] |
| Plain-language definition | [What is counted and when it qualifies] |
| Unit | [Accounts, workspaces, users, transactions] |
| Time window | [Day / week / month, calendar or rolling] |
| Data source and owner | [Table or event, @owner] |
| Metric definition document | [Link to data/metric-definition] |
| Baseline | [Value, date] |
| Target | [Value, date] |
| Example: Name | Weekly collaborating workspaces (WCW) |
| Example: Definition | Workspaces in which at least two different members each edited at least one shared note during the calendar week (Monday to Sunday, UTC) |
| Example: Unit | Workspace |
| Example: Source | Event note_edited with workspace and member IDs, excluding internal and test workspaces |
| Example: Baseline | 4,200 in the week to 2026-09-27 |
| Example: Target | 6,000 by 2027-12-31 |
3. Checklist for a good north star
| Question | Answer for the chosen metric |
|---|---|
| Does it reflect value received by customers, not only value captured by the company? | [Yes / No, why] |
| Is it a leading indicator of revenue and retention? | [Evidence] |
| Can product teams influence it within a quarter through input metrics? | [Yes / No] |
| Is it understandable by everyone in the company in one sentence? | [Yes / No] |
| Is it hard to game without delivering value? | [How it could be gamed and the guardrail] |
| Can it be measured reliably and quickly (weekly)? | [Yes / No] |
| Candidate | Why rejected (Example) |
|---|---|
| Monthly active users | Counts single users who never collaborate, so it rewards the personal-notebook use the strategy moves away from |
| Notes created per week | Easy to inflate with empty or duplicate notes; does not show value to a team |
| Monthly recurring revenue | Lags value by months and teams cannot move it directly |
4. Metric tree: input metrics
| Input ID | Input metric | How it drives the north star | Owner team | Current (Example) | Target (Example) |
|---|---|---|---|---|---|
| I1 | [Metric] | [Mechanism] | [Team] | [Value] | [Value] |
| I1 (Example) | Newly activated workspaces per week | Adds workspaces to WCW for the first time | Growth | 480 | 650 |
| I2 (Example) | Week-over-week WCW retention | Keeps last week's collaborating workspaces | Core | 88% | 90% |
| I3 (Example) | Shared notes edited per collaborating workspace per week | Deeper use predicts retention (diagnostic for I2) | Core | 6.4 | 7.5 |
| I4 (Example) | Resurrected workspaces per week (collaborating again after at least one inactive week) | Returns lapsed workspaces | Lifecycle | 68 | 90 |
Worked decomposition (Example), week to 2026-09-27: the previous week had 4,150 collaborating workspaces. At 88% retention, 3,652 of them were retained (4,150 x 0.88 = 3,652). Adding 480 newly activated and 68 resurrected workspaces gives 3,652 + 480 + 68 = 4,200, which matches the north star value in section 2. When the north star moves, check which of the three components changed before celebrating or reacting.
5. Guardrail metrics
| ID | Guardrail | Limit | Why it matters | Action if breached |
|---|---|---|---|---|
| G1 | [Metric] | [Threshold] | [Risk] | [Response] |
| G1 (Example) | Sync failures per 1,000 edits | Not above 0.5 (current 0.4) | Collaboration value collapses if edits are lost | Freeze feature releases touching sync until back under limit |
| G2 (Example) | Invitation emails marked as spam per 1,000 sent | Not above 1.0 | Pushing invitations can harm trust and deliverability | Pause invitation experiments |
| G3 (Example) | Support tickets per 1,000 weekly active members | Not above 12 | Growth must not come from confusing flows | Review the change that moved it |
| G4 (Example) | Share of members who turn off notifications in week 1 | Not above 15% | Engagement pushed by notifications is not value | Review notification changes |
6. Targets and review cadence
| Review | Frequency | Participants | Output |
|---|---|---|---|
| Metric review | [Weekly] | [Product and analytics leads] | [Notes on movement by input] |
| Strategy check | [Quarterly] | [Leadership] | [Targets confirmed or changed] |
| Definition review | [Yearly] | [Head of product, analytics lead] | [Definition kept or changed, with reason] |
Definition change log:
| Date | Change | Reason | Effect on history |
|---|---|---|---|
| YYYY-MM-DD | [Change] | [Reason] | [Back-filled / series break noted] |
7. Common pitfalls
- Choosing a vanity metric (sign-ups, page views) that grows without value delivered.
- Choosing revenue or profit, which teams cannot move directly and which lags value.
- Having several north stars, which means none of them guides trade-offs.
- Setting input metrics that do not add up to the north star, so movement cannot be explained.
- Ignoring guardrails until customers complain.
- Treating correlation in the data as proof that an input causes the north star; test it with experiments (product/ab-test-plan).
Related templates and references
- data/metric-definition for the precise definition of each metric
- data/dashboard-specification for the north star dashboard
- product/product-vision-strategy, business/okr, business/kpi-scorecard, product/ab-test-plan
- Amplitude, North Star Playbook (John Cutler and co-authors), available from Amplitude: https://amplitude.com/books/north-star
Standard and licence note
Based on common product analytics practice. The North Star Framework is described in Amplitude's North Star Playbook, which is cited by name only; no text, checklist wording or figures are copied, and all wording here and the Tallow Notes example are original. Template licence: MIT.
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