Pawel Huryn
120 lines
4.3 KiB
Markdown
120 lines
4.3 KiB
Markdown
---
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description: Design a product metrics dashboard with North Star metric, input metrics, health metrics, and alert thresholds
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argument-hint: "<product or feature area>"
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---
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# /setup-metrics -- Product Metrics Dashboard Design
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Design a comprehensive metrics framework for your product or feature — from selecting the right North Star to defining alert thresholds that catch problems early.
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## Invocation
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```
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/setup-metrics SaaS project management tool
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/setup-metrics New checkout flow we just launched
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/setup-metrics # asks what you're measuring
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```
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## Workflow
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### Step 1: Understand What to Measure
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Ask the user:
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- What product or feature area are you setting up metrics for?
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- What stage is it in? (pre-launch, recently launched, mature)
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- What are the current business goals or OKRs?
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- Do you have existing metrics? What's missing or broken?
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- What analytics tools are you using? (helps tailor implementation advice)
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### Step 2: Define the Metrics Framework
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Apply the **metrics-dashboard** skill:
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**North Star Metric:**
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- Identify the single metric that best captures the value your product delivers to users
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- Validate against criteria: measures value delivery, is a leading indicator, is actionable
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- Define the metric precisely (formula, data source, time window)
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**Input Metrics (3-5):**
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- Identify the levers that drive the North Star
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- Each input metric should be directly actionable by a team
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- Map the causal chain: Input → North Star → Business Outcome
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**Health Metrics (3-5):**
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- Metrics that should stay stable — if they degrade, something is wrong
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- Examples: error rates, latency, support ticket volume, NPS, churn rate
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- Define "healthy" ranges and degradation thresholds
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**Counter-Metrics (1-2):**
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- Metrics that could indicate you're optimizing the wrong way
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- Example: if North Star is "daily active users", counter-metric is "session quality" to prevent empty engagement
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### Step 3: Design Alert Thresholds
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For each metric:
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| Metric | Green | Yellow | Red | Check Frequency |
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|--------|-------|--------|-----|----------------|
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| [metric] | [healthy range] | [warning] | [critical] | [daily/weekly] |
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- **Yellow**: Investigate — something may be off
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- **Red**: Act immediately — page someone or escalate
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### Step 4: Create Dashboard Spec
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```
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## Metrics Dashboard: [Product/Feature]
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**North Star**: [metric name]
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**Definition**: [precise formula]
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**Current value**: [if known]
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**Target**: [goal]
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### Input Metrics
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| Metric | Definition | Owner | Target | Current |
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|--------|-----------|-------|--------|---------|
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### Health Metrics
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| Metric | Healthy Range | Yellow Threshold | Red Threshold |
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|--------|-------------|-----------------|---------------|
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### Counter-Metrics
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| Metric | Why It Matters | Watch For |
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|--------|---------------|-----------|
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### Metrics Tree
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North Star: [metric]
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├── Input: [metric 1] → driven by [team/action]
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├── Input: [metric 2] → driven by [team/action]
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├── Input: [metric 3] → driven by [team/action]
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└── Counter: [metric] → watch for [degradation signal]
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### Implementation Notes
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- Data sources: [where each metric comes from]
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- Refresh frequency: [real-time / hourly / daily]
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- Tool recommendations: [based on user's stack]
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### Review Cadence
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- **Daily**: Glance at North Star and health metrics
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- **Weekly**: Review input metrics trends, discuss in team standup
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- **Monthly**: Deep dive — are inputs driving the North Star as expected?
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- **Quarterly**: Reassess the metrics framework itself
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```
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Save as a markdown file to the user's workspace.
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### Step 5: Offer Next Steps
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- "Want me to **write SQL queries** to compute these metrics?"
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- "Should I **create OKRs** based on this metrics framework?"
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- "Want me to **build a cohort analysis** to set realistic baselines?"
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- "Should I **set up a weekly metrics review template**?"
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## Notes
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- A good North Star is rare — most teams pick vanity metrics. Push for a metric that captures *user value delivered*, not just engagement
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- Input metrics should be MECE (mutually exclusive, collectively exhaustive) in explaining the North Star
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- If the product is pre-launch, define metrics now but note that baselines will need calibration after launch
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- Counter-metrics prevent Goodhart's Law — when a metric becomes a target, it ceases to be a good metric
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- Recommend starting with fewer metrics, well-instrumented, over a sprawling dashboard nobody checks
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