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Web Analytics Audit & Data Quality
Supporting Case Study — Assessing the data foundation for strategic decisions.
Corporate Group | Wholesale & Skilled Trades (Anonymised)
Context
As part of a strategy and workshop project, I reviewed the website’s web analytics foundations.
The aim was to answer a fundamental question:Are the available data reliable and consistent enough to support strategic decisions?
Approach & Scope
I systematically reviewed the data structure in Google Analytics 4, covering:• Core GA4 setup and tracking stability
• Device and user breakdown
• Main entry points (landing pages)
• Engagement and time spent on the site
• Differences between website sections
The focus was on understanding how data was collected and what it revealed about user behaviour, rather than producing KPI reports.
Technical foundations of GA4 data collection: device, browser and platform breakdown.
User Behaviour & Entry Points
The analysis revealed a clear pattern:• Users engage deeply with content
• Engagement levels and time spent on the site are consistent
• Many visits begin on general overview pages
• Users reach the decision-making or conversion stage relatively late in their journey
GA4 — Engagement and landing pages. Strong content engagement, but no clearly defined route into the next stage of the journey.
Differences Between Website Sections
Different sections of the website, including information, careers and services, showed similar usage patterns. Users were active and interested, but there were few clear pathways to defined next steps.
This suggested a structural issue in the digital experience rather than a tracking problem.
GA4 — Comparison of website sections. Similar usage patterns across different areas.
Data Quality Assessmentt
What the data could reliably support:• Analysing user behaviour
• Identifying the most actively used content and sections
• Assessing technical system stability
What the data could not yet support:
• Clear evaluation of marketing performance against KPIs
• Conversion analysis
• Comparison of different marketing activities
The key limitation was the lack of clearly defined entry points into the digital process.
Conclusion
The web analytics system was technically stable, logically consistent and straightforward to interpret. It provided a reliable data foundation for strategic decisions.Key Takeaway
Reliable web analytics data provides a foundation for strategy, but does not guarantee success. Meaningful evaluation of KPIs and performance also requires clearly defined entry points into the user journey.My Approach
This supporting case study illustrates the analytical work behind my strategic approach: first validate the data, then use the findings to inform strategy.