Digital Analytics
Collect, measure, analyse, and interpret data from digital channels (websites, apps, social media, email, and ads) to understand user behaviour and campaign performance, and to improve outcomes such as engagement, conversion, retention, and service adoption.
Proficiency Level
Level 1 (Follow)
- Understand common digital metrics (such as sessions, users, Click-through Rate CTR conversions) and basic tracking concepts.
- Use existing dashboards/reports to retrieve data and share simple observations.
- Follow SOP for tagging/UTM usage and flags obvious data issues (missing data, broken links).
Level 2 (Assist)
- Perform routine reports and explores data by channel/campaign/audience; explains basic trends.
- Apply consistent tagging (UTMs), validates tracking basics, and troubleshoots common reporting discrepancies.
- Produce actionable insights for day-to-day optimisation (content, ads, landing pages).
Level 3 (Apply)
- Design measurement plans (KPIs, events, funnels) aligned to business objectives and user journeys.
- Perform deeper analysis (cohort, funnel drop-off, segmentation) and turns findings into clear recommendations.
- Manage data quality and consistency across tools (web/app analytics, CRM exports) with documented assumptions.
Level 4 (Ensure)
- Establish analytics standards and governance (naming conventions, KPI definitions, QA gates, dashboard frameworks).
- Lead experimentation and optimisation (A/B testing design, hypothesis tracking, impact measurement).
- Integrate multi-source data (ads + web/app + CRM) to provide full-funnel performance insights and coach teams.
Level 5 (Strategise)
- Define enterprise digital measurement strategy (north-star metrics, multi-touch attribution approach, reporting operating model).
- Drive analytics maturity (automation, advanced modelling, decision systems) and ensures compliance/privacy readiness.
- Influence strategy using insights at scale (investment allocation, product/UX direction, growth roadmap).