Product Analytics Ownership
• Partner with Product Managers and Engineering leaders to understand customer workflows, product experiences, user behaviors, and business objectives, using data to drive product strategy and decision-making.
• Develop a deep understanding of customer workflows, product experiences, and user behaviors to identify opportunities for improved adoption, engagement, retention, and value realization.
• Define success metrics and measurement plans for product launches, features, and strategic initiatives.
• Develop and refine KPIs and measurement frameworks that align teams around product and business performance.
• Partner with Product and Engineering teams to define event tracking requirements and ensure product telemetry supports meaningful measurement and analysis.
• Quantify opportunity size and help Product teams prioritize investments based on expected customer value, business impact, and strategic objectives.
• Support product teams throughout the product lifecycle, from opportunity identification and prioritization through launch and post-release evaluation.
Analytics Execution & Insight Generation
• Conduct deep-dive analyses to identify trends, opportunities, risks, and root causes.
• Translate complex business questions into actionable insights and recommendations.
• Design, analyze, and communicate results from experiments, feature launches, and product initiatives, evaluating customer and business impact.
• Identify and quantify opportunities to improve product experiences, customer engagement, retention, and business outcomes through data-driven analysis.
• Evaluate tradeoffs between competing product investments and provide analytical recommendations that support roadmap prioritization.
Stakeholder Partnership & Data Storytelling
• Act as a trusted analytics partner to Product, Engineering, and Leadership teams.
• Present analytical findings and recommendations through clear narratives and effective visualizations.
• Influence prioritization and strategic decisions through evidence-based insights.
• Communicate complex analytical concepts to both technical and non-technical audiences.
Analytics Excellence & Innovation
• Partner with Data Engineering and Analytics teams to improve data quality, instrumentation, and accessibility.
• Leverage modern analytics and AI-powered tools to accelerate analysis and improve team efficiency.
• Contribute to scalable analytics best practices, governance, and continuous improvement across the organization.