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revenue-analytics

Revenue analytics architecture - ARR / NRR / GRR decomposition, cohort retention, expansion drivers, segment economics, and CAC payback diagnostics. Use when: revenue analytics, ARR waterfall, NRR analysis, GRR, expansion analysis, cohort revenue retention, CAC payback, magic number, segment economics, revenue diagnostics.

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Atualizado há 4 meses

Ver no GitHub ↗ Licença: MIT

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Ler descrição completa

Revenue Analytics (LADDER Framework)

Design a revenue analytics layer that answers where revenue is being created, where it's leaking, and which lever to pull next - not a dashboard of vanity totals. LADDER decomposes ARR, attributes it, diagnoses drivers, and turns analysis into named actions.

Core Principle

Revenue analytics fails when it stops at the totals. Reporting ARR up-and-to-the-right tells you nothing actionable. LADDER decomposes revenue into the components a leadership

[Description truncada. Veja o README completo no GitHub.]

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