North Star Metric Decomposition AI Prompt

Decompose the North Star Metric into its input metrics and build a measurement tree.

North Star Metric: {{nsm}} (e.g. 'Weekly Active Engaged Users' or 'Messages Sent per Month')
Product context: {{product_description}}

1. Level 1 decomposition:
   Break the NSM into 2-3 multiplicative or additive components.
   Example: Weekly Active Engaged Users = Weekly Active Users x Engagement Rate
   Example: Revenue = Users x Conversion Rate x Average Order Value

2. Level 2 decomposition:
   Break each Level 1 component further.
   Example: Weekly Active Users = New Users + Retained Users + Resurrected Users
   Example: Engagement Rate = % Users Completing Core Action

3. Level 3 decomposition (where meaningful):
   Continue decomposing into actionable leaf metrics that specific teams own.

4. For each leaf metric:
   - Current value
   - Owner: which team or squad controls this metric?
   - Lever: what specific action moves this metric?
   - Effort to improve by 10%: Low / Medium / High

5. Sensitivity analysis:
   - If each leaf metric improves by 10%, which has the largest impact on the NSM?
   - This identifies the highest-leverage improvement opportunity

6. Metric tree dashboard spec:
   - Top level: NSM with trend
   - Second level: Level 1 components with trend
   - Third level: Level 2 components with owner labeled
   - Color coding: green = above target, yellow = near target, red = below target

Return: metric tree (all three levels), owner assignment, sensitivity analysis, and dashboard specification.