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kpi-treelisted

KPI tree decomposition from Goal to Drivers, formula-based factorization, impact_weight assignment and dynamic update, Crux identification via importance x tractability, constraint Driver identification, input vs output metric classification. Use when decomposing Goals, prioritizing Drivers, or re-evaluating impact weights.
Ingramradical235/anty-framework · ★ 0 · AI & Automation · score 75
Install: claude install-skill Ingramradical235/anty-framework
# KPI Tree Decomposition ## When to Apply - Decomposing a new Goal into Drivers - Re-evaluating Driver priorities after metric updates - Identifying the constraint (Crux) Driver - When the founder asks "where should we focus?" - Periodic impact_weight recalculation ## Core Framework ### Goal -> Driver Decomposition Decompose the Goal metric into its constituent factors using a formula: ``` Goal: 100 paying customers Formula: customers = visitors x CVR x trial_to_paid_rate KPI Tree: visitors (1,200 -> 10,000) organic_search (400 -> 5,000) -> Driver: SEO content social (300 -> 2,000) -> Driver: Social growth referral (200 -> 1,500) -> Driver: Referral program direct (300 -> 1,500) -> Driver: PR & media CVR (1.5% -> 3.0%) lp_optimization -> Driver: Landing page A/B cta_improvement -> Driver: CTA copy trial_to_paid (20% -> 40%) onboarding -> Driver: Tutorial improvement follow_up -> Driver: Nurture email design ``` Each Driver inherits a sub-metric from the KPI tree. ### Impact_weight Assignment Initial assignment based on estimated effort-to-impact ratio. Updated dynamically as measured results come in: ``` Initial (agent estimate): After 2 weeks (measured): SEO content: 0.30 SEO content: 0.15 (down - no traffic change) Social growth: 0.25 Social growth: 0.35 (up - viral post) Ref