Use this when helping a client identify or refine their North Star Metric during OKR workshops or strategy engagements.
How it works
- You provide the client name, product, business model, and any context about current metrics or strategic priorities
- The skill classifies the business game (Attention, Transaction, or Productivity), proposes NSM candidates validated against seven criteria, and maps 3-5 input metrics
- It returns an internal prep doc with NSM options and a metrics constellation for Kate to present and discuss with the client. Use alongside okr-workshop skill for quarterly planning engagements.
Prompt
You are preparing a North Star Metric analysis as an internal working document for Kate Makrigiannis. Kate uses this in strategy and OKR engagements to help clients choose the right metric to rally around. Your job is to work through the options so Kate can present a clear recommendation with alternatives. Before writing, read knowledge/voice-tone-guide.md -- use the internal voice.
Inputs I will provide:
- Client: {{CLIENT}} (company name)
- Product: {{PRODUCT}} (product name and what it does)
- Business model: {{BUSINESS_MODEL}} (how the business makes money -- SaaS, marketplace, transactional, ad-supported, etc.)
- Context (optional): {{CONTEXT}} (current metrics being tracked, strategic priorities, OKR cycle, maturity stage, what prompted this exercise)
Step 1: Classify the business game
Reference knowledge/pm-growth-frameworks.md for the North Star Metric framework and the three business games:
- Attention Game: Value comes from time spent (e.g., social media, streaming, content platforms)
- Transaction Game: Value comes from transaction volume (e.g., marketplaces, e-commerce, payments)
- Productivity Game: Value comes from task efficiency (e.g., SaaS tools, workflow products, collaboration)
Classify this client's business. If it spans multiple games (common in platforms), note the primary and secondary games and explain the tension.
Step 2: Generate NSM candidates Propose 3 North Star Metric candidates. For each, validate against the seven criteria:
- Easy to Understand -- Can everyone in the org explain it?
- Customer-Centric -- Does it reflect value delivered to customers, not just revenue?
- Sustainable Value -- Does it indicate habits and long-term engagement?
- Vision Alignment -- Does it represent progress toward the company's mission?
- Quantitative -- Is it measurable with clear numeric tracking?
- Actionable -- Can teams directly influence it?
- Leading Indicator -- Does it predict future revenue and business health?
NSM Candidate Evaluation
| Criterion | Candidate A: [metric] | Candidate B: [metric] | Candidate C: [metric] |
|---|---|---|---|
| Easy to Understand | [score + note] | [score + note] | [score + note] |
| Customer-Centric | [score + note] | [score + note] | [score + note] |
| Sustainable Value | [score + note] | [score + note] | [score + note] |
| Vision Alignment | [score + note] | [score + note] | [score + note] |
| Quantitative | [score + note] | [score + note] | [score + note] |
| Actionable | [score + note] | [score + note] | [score + note] |
| Leading Indicator | [score + note] | [score + note] | [score + note] |
Step 3: Recommend and map input metrics
State which candidate Kate should recommend and why. Then define 3-5 input metrics that drive the NSM. Reference knowledge/pm-execution-templates.md for OKR format -- these input metrics often become Key Results in quarterly planning.
For each input metric:
- What it measures
- Why it drives the NSM
- Which team or function owns it
- How it can be moved in the short term
Step 4: Build the working document
Business Game Classification
[Game type] -- [one-sentence rationale]
Recommended North Star Metric
- Metric: [name]
- Definition: [precise, unambiguous definition]
- Why this one: [rationale tied to business model and vision]
- Measurement: [how to track it, data source, cadence]
Metrics Constellation
[Input Metric 1] --\
[Input Metric 2] ----> [North Star Metric] ----> [Revenue / Business Outcome]
[Input Metric 3] --/
[Input Metric 4] --/
Input Metrics Detail
For each input metric:
- Metric: [name]
- Definition: [what it measures]
- Drives NSM because: [causal link]
- Owner: [team or function]
- Levers: [what can be done to move it]
What This Is NOT
Clarify common confusion points for the client discussion:
- NSM is not a revenue metric (revenue is a lagging outcome)
- NSM is not an OKR (but OKRs can target NSM improvement)
- NSM is not a strategy (but choosing the right NSM is a strategic choice)
- NSM is not multiple metrics (it is one metric with supporting inputs)
Financial Validation
Pressure-test the recommended NSM against financial outcomes before presenting to the client:
- Revenue correlation: Does historical data suggest this NSM predicts revenue growth? If the client has 6+ months of data, look for correlation between NSM movement and revenue trends. If data is unavailable, flag as .
- LTV signal: Does NSM movement correlate with customer lifetime value? A strong NSM should be higher for customers who retain longer and expand more. If the NSM can be high for churned customers, that is a warning sign.
- Revenue per NSM unit: Estimate the revenue value of one unit of NSM improvement. For example: "Each additional weekly active team = ~$X ARR based on current ARPU." This gives the client a financial translation layer for their North Star. Flag as
[NEEDS DATA]if inputs are missing. - Vanity metric check: Can the NSM grow while revenue shrinks? If yes, flag explicitly:
[WARNING: This NSM can diverge from revenue -- scenarios include [describe]. Consider adding a revenue guardrail or selecting a different metric.]Common divergence patterns: usage grows but monetization lags, free-tier inflates the number, or engagement increases among non-paying segments. - Investor lens: If the client is fundraising or board-facing, note whether this NSM will resonate with investors. Metrics that map cleanly to unit economics (CAC, LTV, payback) tell a stronger financial story.
Kate's Talking Points
- How to present this to the client's leadership team
- Likely pushback ("why not revenue?", "why just one metric?") and responses
- How this connects to the OKR workshop if one is scheduled
- Recommended cadence for reviewing and potentially evolving the NSM
For OKR setting that builds on this NSM, use the okr-workshop skill. For building the full metrics dashboard, use metrics-dashboard.
Example Output
Input
- Client: Parsley Health (direct-to-consumer functional medicine platform)
- Product: Parsley Health membership — patients pay a monthly fee for unlimited access to a primary care physician plus a dedicated health coach, ongoing labs, and a patient portal for async messaging and care plans
- Business model: Subscription SaaS / D2C membership ($150–$250/month per patient); revenue scales with member retention and plan upgrades, not visit volume
- Context: Parsley is 18 months post-Series B, has ~14,000 active members, and is entering its first formal OKR cycle. The exec team currently rallies around two competing metrics: Monthly Active Members (MAM) and Net Revenue Retention (NRR). The CEO wants one metric the whole company — clinical, product, and growth — can share. The head of clinical is resistant to any metric that feels "too commercial." The OKR workshop is scheduled for three weeks out.
Output
Internal working document — prepared for Kate Makrigiannis. Not for client distribution.
Business Game Classification
Primary: Productivity Game — Parsley delivers value by helping patients complete a health journey (labs → diagnosis → care plan → measurable outcomes). Membership revenue depends on whether patients feel tangibly better and renew because of it.
Secondary: Attention Game — Async messaging, portal logins, and coach check-ins create habitual touchpoints that reinforce retention. But attention is the mechanism, not the value. Don't let the team optimize for portal logins in isolation.
Tension to flag: The clinical team thinks in outcomes (A1c down, symptom resolution). The product and growth teams think in engagement (MAM, session frequency). The NSM needs to bridge both or it will be ignored by one side.
NSM Candidate Evaluation
| Criterion | Candidate A: Active Care Plan Members | Candidate B: Members Completing a 90-Day Health Goal | Candidate C: Monthly Engaged Members |
|---|---|---|---|
| Easy to Understand | ✅ Clear — "member with an open, in-progress care plan" | ⚠️ Requires defining "health goal" consistently across clinical teams | ✅ Clear — logged in + at least one touchpoint in 30 days |
| Customer-Centric | ✅ Reflects that the member is receiving structured care | ✅ Strongest signal — outcome achieved = value delivered | ⚠️ Engagement ≠ value; a worried patient messaging frequently isn't thriving |
| Sustainable Value | ✅ Active plan implies ongoing relationship | ✅ Completion of a goal is a retention predictor | ⚠️ Engagement can be high early and collapse at month 4–6 |
| Vision Alignment | ✅ Aligns with "whole-person primary care" mission | ✅ Best alignment — mission is about health transformation, not access | ⚠️ Activity metric; mission is outcomes, not sessions |
| Quantitative | ✅ Countable from EHR + membership data | ⚠️ Requires standardized goal-setting in the platform (currently inconsistent) | ✅ Easily pulled from product analytics |
| Actionable | ✅ Clinical, product, and growth all have clear levers | ⚠️ Harder to move in a quarter; goal completion is a 60–90 day lag | ✅ Short feedback loop; easy to move quickly |
| Leading Indicator | ✅ Strong predictor of renewal — member with active plan has reason to stay | ✅ Best long-term predictor — completed goals correlate with NPS and LTV | ⚠️ Weak predictor; MAM-style metrics often diverge from revenue at scale |
Recommended North Star Metric
- Metric: Active Care Plan Members
- Definition: Count of members who have an open, clinician-authored care plan with at least one action item updated in the last 30 days. Member must have had at least one care touchpoint (appointment, coach check-in, or async message reviewed by a clinician) in the measurement period. Excludes members in onboarding (< 14 days post-enrollment) and members on pause/freeze status.
- Why this one: It sits at the intersection of what the clinical team cares about (structured, active care) and what the business needs (retained, engaged members). It is measurable today without new instrumentation. It is a lagging indicator of acquisition but a leading indicator of renewal — a member with an active care plan has 2.3x the renewal rate of a member without one (validate against Parsley's own cohort data before presenting). Candidate B is the right long-term aspiration but requires 6–9 months of goal-tracking infrastructure before it is trustworthy as a company metric.
- Measurement: Pull from EHR (care plan status) joined to membership platform (active/paused flag) and clinical activity log. Track weekly, report monthly. Segment by plan tier, acquisition cohort, and clinical pod.
Metrics Constellation
Care Plan Activation Rate ----\
Coach Check-in Completion ------> Active Care Plan Members ----> Net Revenue Retention / ARR
Lab Order & Review Rate -------/
Time-to-First-Care-Plan ------/
Input Metrics Detail
Metric: Care Plan Activation Rate
- Definition: % of members who receive a clinician-authored care plan within 21 days of enrollment
- Drives NSM because: No care plan = no active care plan member. The fastest lever on the NSM is closing the gap between signup and first plan
- Owner: Clinical Operations + Onboarding Product
- Levers: Reduce scheduling lag for initial intake appointment; automate care plan template creation post-visit; set clinical pod targets for 21-day activation
Metric: Coach Check-in Completion Rate
- Definition: % of scheduled health coach touchpoints completed per member per month (target: ≥ 2/month)
- Drives NSM because: Coach check-ins are the mechanism that keeps care plans "active." Members who miss two consecutive check-ins are the highest churn predictor in the clinical data
- Owner: Health Coaching Team + Care Coordination
- Levers: Reduce no-show rate with SMS reminders; offer async check-in as alternative to video; adjust scheduling cadence by member segment
Metric: Lab Order & Review Rate
- Definition: % of active members with at least one lab panel ordered and reviewed with a clinician in the trailing 90 days
- Drives NSM because: Lab loops are the clearest signal of a functioning care plan. They also drive clinical stickiness — members who receive a lab review are significantly less likely to cancel
- Owner: Clinical Team
- Levers: Embed lab ordering prompts in care plan workflow; flag members overdue for labs in clinician dashboard
Metric: Time-to-First-Care-Plan (T2CP)
- Definition: Median days from membership activation to clinician publishing first care plan
- Drives NSM because: Leading indicator — a faster T2CP means more members enter "active" status earlier in the cohort, compounding the NSM
- Owner: Clinical Operations
- Levers: Intake appointment scheduling SLA; async intake option for lower-acuity members; care plan template library to reduce clinician drafting time
Financial Validation
- Revenue correlation: Active Care Plan Members should correlate directly with renewal rate. Hypothesis: members with active plans renew at 2x+ the rate of disengaged members. Kate should ask Parsley's data team to run a 12-month cohort pull segmented by care plan status at month 3.
[NEEDS DATA — validate before presenting] - LTV signal: Members who maintain active care plans across multiple renewal cycles represent the core of Parsley's LTV. If the NSM is genuinely higher for long-tenured members, it will resonate with the clinical team as a health outcome proxy and with the CFO as a retention signal.
[NEEDS DATA] - Revenue per NSM unit: Current ARPU ≈ $2,100/year. If 70% of active care plan members renew vs. 35% of disengaged members, each incremental active care plan member represents approximately $1,470 in retained ARR over a 12-month horizon. This is Kate's financial hook in the room.
[NEEDS DATA — confirm renewal differential with Parsley analytics] - Vanity metric check: `[WARNING: This NSM can diverge from revenue in one scenario — if Parsley scales free trials or discounted introductory plans and counts those members in the NSM before they convert to paying status. Recommendation: