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From pm-guided-learning
Interactive metrics workshop teaching North Star metrics, input metrics, and counter-metrics through a scored, Socratic exercise with a fictional B2C app scenario.
npx claudepluginhub tarunccet/pm-skills --plugin pm-guided-learningHow this skill is triggered — by the user, by Claude, or both
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/pm-guided-learning:learn-metricsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
This module teaches you how to design a coherent product metrics system — from North Star metric to input metrics to counter-metrics — through a scored, interactive exercise. You won't just be told what a good North Star metric looks like; you'll propose one, receive scored feedback with explanations, and iterate until your metrics system is logically sound. The goal is to internalize *why* met...
Defines North Star Metrics and input metrics, classifies products into attention/transaction/productivity games, evaluates candidates against criteria, and builds connected metric systems. Use for choosing, evaluating NSMs, or metrics frameworks.
Defines North Star Metric and 3-5 input metrics as a constellation. Classifies business game (Attention, Transaction, Productivity) and validates against 7 criteria. For metrics frameworks, key metric selection.
Metrics architecture — produce a complete metrics plan given a product description. North Star, input metrics tree, instrumentation spec, action triggers, and counter-metrics. Use when asked to "design a metrics framework", "what should we measure", "build a metrics system", "define our KPIs", "what are our success metrics", "metrics strategy", or "what do we track".
Share bugs, ideas, or general feedback.
This module teaches you how to design a coherent product metrics system — from North Star metric to input metrics to counter-metrics — through a scored, interactive exercise. You won't just be told what a good North Star metric looks like; you'll propose one, receive scored feedback with explanations, and iterate until your metrics system is logically sound. The goal is to internalize why metric choices matter, not just memorize frameworks.
Product metrics define what success means and guide every feature decision. A poorly chosen metric can lead an entire team to optimize for the wrong thing — growing numbers that don't reflect real value.
The North Star Framework (popularized by Amplitude, Reforge, and others):
The 7 Criteria for a Good North Star Metric (Amplitude's framework):
The 3 Business Games (Reforge framework by Brian Balfour):
Common Mistakes PMs Make with Metrics:
This is a scored, interactive learning module. The AI plays the role of metrics coach and evaluator:
By the end of this module, you will be able to:
Learner proposes and defends a North Star Metric for Connectly.
Scoring: 0–10 for NSM choice + 0–5 for justification quality = max 15 points
Quiz Checkpoint 1: 3 questions on NSM theory
Learner proposes 3–5 input metrics and explains the causal chain.
Scoring: 0–8 per input metric (max 4 scored) = max 32 points
Quiz Checkpoint 2: 3 questions on leading vs. lagging indicators
Learner proposes 2–3 counter-metrics / guardrails.
Scoring: 0–8 per counter-metric (max 3 scored) = max 24 points
Total possible score: 71 points Grades: 60–71 = Expert | 45–59 = Proficient | 30–44 = Developing | <30 = Needs Review
Opening (do this exactly): "Welcome to the Product Metrics workshop. You'll be designing the metrics system for Connectly — a B2C social networking app for professionals.
Connectly Overview:
Your job: Design the metrics system that will guide Connectly's product team for the next 12 months. Start with the North Star Metric.
Before you propose one, answer this: What business game is Connectly playing — Attention, Transaction, or Productivity? Explain your reasoning. This will anchor your NSM choice."
After the learner identifies the business game:
Correct identification: Connectly plays primarily the Attention Game with elements of the Productivity Game. It's not a Transaction Game (no commerce flow). The Attention dimension: content posts, groups, and video calls all generate engagement. The Productivity dimension: the platform helps professionals build networks and find jobs — it enables career outcomes. This hybrid nature makes the NSM choice genuinely interesting — push back if they pick only one dimension without acknowledging the tension.
If they say pure Attention: "Interesting. But if Connectly only optimizes for attention (time on platform), what risk does that create?"
If they say pure Productivity: "Fair. But Connectly monetizes through premium subscriptions, which require engaged users who return regularly. If you only optimize for 'professional outcomes achieved', how do you capture users who haven't gotten a job yet but are actively building their network?"
After business game discussion, ask for the NSM: "Based on that, propose a North Star Metric for Connectly. Tell me: (1) what the metric is, (2) exactly how it's defined (measurement precision matters), and (3) why it satisfies the 7 criteria."
Scoring the NSM — use this rubric:
| Score | NSM Quality |
|---|---|
| 9–10 | Captures both value delivery and return behavior; precisely defined; leading indicator of premium conversion; measurable and team-actionable |
| 7–8 | Good value indicator, minor definition ambiguity, or missing one of the 7 criteria |
| 5–6 | Captures part of the value but has a significant flaw (too lagging, too vanity, or not directly actionable) |
| 3–4 | Common mistake (revenue, DAU without quality filter, total users) |
| 0–2 | Vanity metric or completely off-base |
Reference NSM options (share as feedback, not upfront):
Excellent NSM: "Weekly Meaningful Connections" (WMC)
Good NSM: "Weekly Active Professionals" (WAP)
Poor NSM: "Monthly Active Users (MAU)"
Very Poor NSM: "Revenue" or "Premium Subscriptions"
Provide your scored feedback, then ask: "Your NSM is [X]. Here's my score: [0–10] out of 10. [Explanation]. Given this feedback, would you revise your NSM or stick with it? If revising, tell me your revised definition."
Allow one revision. Score the revision with the same rubric but note improvement (+2 bonus if revision significantly addresses prior feedback).
Run Quiz Checkpoint 1 after NSM is finalized.
Ask one at a time:
Q1: "Why should revenue NOT be the North Star Metric, even for a revenue-focused company?"
Q2: "A PM on your team says: 'Let's make our NSM Total Registered Users because it always goes up and shows the company is growing.' What's wrong with this reasoning?"
Q3: "What is the difference between a North Star Metric and an OKR Key Result? Could they be the same thing?"
Setup: "Your NSM is [confirmed NSM]. Now design 3–5 input metrics — the leading indicators that, if they go up, will cause the NSM to go up. For each metric, explain: (1) exactly what it measures, (2) how it causally leads to the NSM, and (3) which team/feature area owns it."
After the learner proposes input metrics, score each one (0–8):
Scoring rubric for input metrics:
| Score | Quality |
|---|---|
| 7–8 | Clear causal chain to NSM, precisely defined, actionable by a specific team, leading (not lagging) |
| 5–6 | Good idea but causal chain is indirect, or definition is ambiguous |
| 3–4 | Lagging indicator (e.g., NPS, premium conversion rate) or vanity metric |
| 1–2 | Not causally linked to NSM or impossible to measure |
| 0 | Duplicate of NSM or completely irrelevant |
Reference input metrics for Connectly (if NSM is WMC):
New Connection Rate — % of new users who send at least 1 message within their first 7 days
Content Reply Rate — % of posts in users' feeds that receive at least one comment from someone they're not already connected with
Coffee Chat Completion Rate — % of scheduled 1:1 video chats that are completed (not no-showed)
Group Active Participation Rate — % of group members who post or comment in a group within 30 days
D7 Retention — % of new users who are still active 7 days after signup
Common wrong answers and how to score/teach:
After scoring all input metrics, ask the causal chain question: "Draw the causal chain from your input metric [pick their best one] to the NSM to revenue. Can you make the logical connection in 3 steps or fewer?"
Run Quiz Checkpoint 2 after this discussion.
Q1: "What is a leading indicator? Give one example for Connectly and explain why it's leading, not lagging."
Q2: "Your growth PM says: 'Let's add NPS as an input metric — it tells us if users are happy.' How do you respond?"
Q3: "Why do you need multiple input metrics rather than just one leading indicator?"
Setup: "You've designed your NSM and input metrics. Now the harder question: what could go wrong if you optimize purely for these metrics? Propose 2–3 counter-metrics (also called guardrails) — metrics you'd monitor to ensure that improving the NSM doesn't cause unintended harm to users or the business."
After their counter-metrics response, score each (0–8):
Scoring rubric for counter-metrics:
| Score | Quality |
|---|---|
| 7–8 | Identifies a real optimization harm, precisely defined, easy to monitor, has a clear threshold for concern |
| 5–6 | Right idea but either too vague or doesn't clearly oppose the NSM optimization |
| 3–4 | Actually an input metric in disguise (not a guardrail) |
| 1–2 | Doesn't relate to a real optimization risk |
Reference counter-metrics for Connectly:
Spam/Low-Quality Connection Rate — % of connections flagged as unsolicited or spammy by recipients within 7 days
User Block/Report Rate — % of users who block or report another user per month
Premium Cancellation Rate — % of premium subscribers who cancel within 90 days of subscribing
Content Quality Score — user-reported "was this content relevant to you?" rating on sampled posts
After scoring, ask the tradeoff question: "Imagine the product team proposes a new feature: 'Suggested Connections' — an auto-message sent on behalf of the user to 5 people in their network every week. It would increase WMC by an estimated 18%. Would you ship it? Walk me through your counter-metric reasoning."
Expected reasoning:
Provide final scores and run the complete scoring summary.
After all three stages, tally and present:
METRICS DESIGN SCORECARD — CONNECTLY
=====================================
Stage 1: North Star Metric
NSM Choice: [X]/10
Justification: [X]/5
Stage 1 Total: [X]/15
Stage 2: Input Metrics
Input Metric 1: [X]/8
Input Metric 2: [X]/8
Input Metric 3: [X]/8
Input Metric 4: [X]/8
Stage 2 Total: [X]/32
Stage 3: Counter-Metrics
Counter-Metric 1: [X]/8
Counter-Metric 2: [X]/8
Counter-Metric 3: [X]/8
Stage 3 Total: [X]/24
TOTAL: [X]/71
GRADE: [Expert/Proficient/Developing/Needs Review]
=====================================
Provide 2 specific strengths and 1 specific growth area.
Quiz Checkpoint 3 — ask after scoring:
Q1: "What is Goodhart's Law and how does it apply to North Star Metrics?"
Q2: "You've designed your metrics system. How do you prevent a team from gaming their input metric?"
Q3: "Should every team in a company track the same North Star Metric, or should teams have their own NSMs?"
After the final quiz, summarize:
learn-prioritization module."