- Lead analytics across marketing acquisition, product-led growth, lifecycle growth, and channel performance, spanning paid, organic, lifecycle, partnership, affiliate, referral, and in-product channels.
- Own analysis of the full growth funnel, including acquisition, activation, onboarding, conversion, retention, monetization, expansion, and long-term customer value.
- Develop and improve attribution, campaign measurement, and marketing efficiency frameworks to help the business understand what is driving sign-ups, revenue, CAC, ROAS, LTV, and payback.
- Lead experimentation analytics across the growth funnel, including A/B tests, incrementality tests, onboarding experiments, landing page tests, lifecycle experiments, pricing/packaging tests, and in-product conversion tests.
- Design and evaluate experiments end to end, including hypothesis development, metric selection, test sizing, statistical interpretation, readouts, and rollout recommendations.
- Build dashboards, reporting frameworks, and analytical models that give teams clear visibility into performance across campaigns, channels, segments, cohorts, funnels, and experiments.
- Analyze customer journeys using campaign data, UTM parameters, product usage data, conversion events, lifecycle touchpoints, and marketing schemas to improve tracking quality and uncover growth opportunities.
- Develop or support advanced analyses such as LTV modeling, customer segmentation, propensity modeling, churn analysis, product-qualified lead scoring, and upsell/cross-sell opportunity analysis.
- Partner with Data Engineering and Analytics Engineering to improve data quality, event instrumentation, marketing/product data models, and self-service reporting infrastructure.
- Communicate insights, tradeoffs, experiment results, and recommendations clearly to Marketing, Growth, Product, Finance, and executive stakeholders.
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