Develop and maintain dashboards and regular reporting that track key ecommerce metrics (revenue per visitor, conversion rate, AOV, retention, LTV).
Surface actionable insight and present findings to commercial and executive stakeholders.
Design measurement frameworks for A/B and cohort experiments, define success metrics, validate randomisation, and analyse experiment outcomes to quantify impact on revenue and conversion.
Recommend and support scaling of winning variants.
Perform deep-dive funnel diagnostics and cohort survival analysis to identify drop-off points, conversion drivers and revenue opportunities across the customer journey from landing through assessment, purchase and early post-purchase behaviour.
Own SQL-based analysis and build reproducible models to estimate unit economics, CLTV and contribution margins by channel, cohort and product.
Collaborate with Product, Design, Engineering and Commercial teams to translate insights into prioritised experiments and product changes.
Deliver concise, evidence-led recommendations and executive-ready reporting. Communicate trade-offs and confidence intervals clearly to non-technical stakeholders to drive faster decisions.
Ensure commercial recommendations balance revenue goals with clinical safety, regulatory constraints and long-term customer outcomes. Avoid optimisation that adversely affects customer trust or wellbeing.

Proven hands-on experience in ecommerce analytics, commercial insights or optimisation for consumer-facing subscription or repeat-purchase businesses.
Strong SQL skills with the ability to interrogate event-level data, build cohort/funnel analyses and deliver reproducible results.
Experience designing and analysing A/B and multivariate experiments with clear understanding of statistical power, false positives and ramp strategies.
Comfortable with product and funnel thinking: able to translate data into prioritised product and experiment roadmaps that move revenue per visitor and conversion.
Excellent written and verbal communication skills with experience presenting complex analysis to commercial and senior stakeholders.
Strong problem-solving mindset, attention to detail and a commitment to high-quality, reproducible analysis.

Commercial Insights Data Analyst

Key skills