As Head of Analytics & Experimentation, you will lead the analytics, conversion rate optimization (CRO), and experimentation strategy for a fast-growing direct-to-consumer (DTC) e-commerce business in the health and wellness industry. You will establish a trusted source of truth for customer and revenue performance, transforming data from multiple sales and marketing channels into actionable business insights. Working closely with senior leadership, you will build a structured, cross-functional testing program that prioritizes opportunities based on potential revenue impact and customer journey performance. You will define measurement standards, improve reporting capabilities, and ensure that business decisions are supported by reliable data and rigorous analysis. This high-visibility, autonomous role offers the opportunity to build and scale analytics and experimentation practices from the ground up. Your work will directly influence growth, customer retention, revenue optimization, and the effectiveness of digital experiences across the entire customer journey.
Analytics strategy and measurement: Own the core customer and revenue metrics, including conversion rates, retention, customer lifetime value (LTV), and revenue performance. Establish consistent definitions, maintain a centralized metrics catalog, and ensure teams work from a reliable source of truth.
Data quality and governance: Serve as the final quality checkpoint for data used in business decisions. Validate data accuracy, investigate inconsistencies, and establish standards that promote trustworthy, consistent reporting across departments.
Business intelligence and reporting: Translate strategic business questions into clear analytical requirements, SQL queries, and data models. Develop and maintain dashboards and reporting solutions, beginning with a comprehensive customer journey dashboard.
Data infrastructure collaboration: Partner with data engineering teams to ensure the data platform captures the information required for meaningful analysis across e-commerce, subscriptions, marketing, and customer engagement channels.
Experimentation roadmap: Lead the cross-functional experimentation program, prioritizing tests according to revenue potential, website traffic, funnel drop-off, and expected business impact.
Testing standards and processes: Establish a consistent framework for proposing, designing, executing, and evaluating experiments. Build a shared intake process, define testing requirements, and implement a standardized KPI framework.
Customer journey optimization: Ensure the customer journey is instrumented with the appropriate KPIs and data points at every stage, identifying friction points and opportunities to improve conversion, retention, and customer experience.
Statistical analysis and test evaluation: Lead the analysis of experiment results, including statistical significance, incremental revenue, win rates, and other relevant performance indicators. Provide objective recommendations on which initiatives to scale, refine, or discontinue.
Test coordination and prioritization: Improve incoming test briefs by refining hypotheses, clarifying success criteria, and aligning stakeholders on expected outcomes. Resolve competing testing priorities when multiple teams want to experiment with the same pages, audiences, or customer touchpoints.
Knowledge management: Establish regular experimentation reviews and maintain a shared repository of test results, insights, and lessons learned to improve decision-making and prevent teams from repeating ineffective approaches.
Executive insights and recommendations: Translate complex analyses into clear, concise, evidence-based recommendations for the Director of Customer Journey & Revenue and executive leadership, explaining what is happening, why it matters, and what actions should follow.
Cross-functional partnership: Represent analytics and experimentation in planning discussions involving content, lifecycle marketing, CRM, design, and development teams, ensuring data informs decisions from the earliest stages of execution.
Hands-on execution: Contribute directly when needed by writing SQL queries, configuring experiments, building dashboards, validating data, and conducting in-depth analyses.
First 90-day priorities: Partner with leadership to instrument the full customer journey, introduce an initial metrics catalog, identify major performance gaps and revenue opportunities, and launch a structured testing prioritization process with the first experiments.
Continuous improvement: Refine analytics processes, measurement frameworks, and experimentation capabilities as the business evolves, ensuring that teams can make faster, more confident, and more effective growth decisions.