• Guide and optimize spend so it scales efficiently under contribution margin guardrails • Define CAC ceilings tied to 12- and 24-month contribution margin • Model diminishing returns and marginal efficiency curves to inform budget allocation • Translate attribution constraints and measurement uncertainty into practical, decision-ready frameworks • Interpret insights from MMM, incrementality tests, lift studies, or MTA frameworks and translate them into practical budget and investment decisions • Identify which channels, audiences, creatives, and offers drive the highest-quality cohorts • Support structured validation of new channels before meaningful scale • Deliver clear monthly recommendations on where to scale, hold, or cut • Build and maintain 12- and 24-month contribution margin tracking by acquisition cohort • Develop survival curve diagnostics and retention performance visibility across key milestones • Operationalize retention-adjusted CAC and payback thinking into acquisition decisions • Identify acquisition sources that degrade churn, payback, LTV, or margin • Evaluate pricing, discounts, and offers against downstream margin impact • Create cohort-based forecasting views that improve decision quality without turning this role into FP&A • Own tracking health across ad platforms, GA4, server-side events, ecommerce, and subscription systems • Standardize UTMs, taxonomy, and core metric definitions so performance reporting is trusted • Partner with Finance to align revenue, refunds, COGS, and contribution margin inputs • Build automated dashboards and reduce manual reporting • Create a clear source of truth for acquisition efficiency and long-term cohort performance • Analyze tests and performance shifts across pricing, trial structure, billing cadence, onboarding, churn interventions, win-back, and upsell • Provide decision criteria rooted in long-term contribution margin, not isolated metric lifts • Deliver clear narratives on what changed, why it changed, and what to do next