Case studies

Proof without exposing confidential data.

These examples are anonymized and outcome-focused. They show the type of work I can own without naming internal systems, clients, markets or sensitive metrics.

Dashboard governance

Analytics dashboard governance and KPI framework improvement

Problem: Stakeholders relied on dashboards, but KPI definitions, filters, naming conventions and ownership were scattered across conversations and tools.

My roleStructured requirements, documented KPI logic, coordinated dashboard QA and aligned stakeholders around sign-off criteria.

ConstraintsExisting dashboards had to keep running while governance improved; confidential business logic had to stay internal.

ActionsCreated a dashboard inventory, clarified metric definitions, mapped source fields, defined QA checks and documented monthly review steps.

Tools/systemsDatorama / Salesforce Marketing Cloud Intelligence, Excel/CSV exports, Asana, stakeholder documentation, marketing platform data.

Outcome proxyClearer reporting ownership, fewer repeated definition questions and a maintainable path for dashboard updates.

What this showsI can turn reporting ambiguity into governance, QA and stakeholder-ready delivery.

eCommerce reporting

Retailer reporting and data quality investigation

Problem: Sales and media reporting did not line up cleanly across retailer exports, campaign naming, dashboard mappings and calculated metrics.

My roleInvestigated the discrepancy path, framed likely causes, coordinated follow-ups and documented QA evidence.

ConstraintsData arrived through exports and platform reports with different grains, timing and field naming conventions.

ActionsChecked missing dates, duplicate rows, null KPIs, country/brand mapping, source labels, campaign names and formula assumptions.

Tools/systemsExcel, CSV/XLS exports, retailer reporting, media platform data, dashboard QA notes and stakeholder updates.

Outcome proxyIssues were separated into data problems, naming problems and dashboard logic questions, making next actions clearer.

What this showsI can investigate reporting trust issues without jumping to unsupported conclusions.

Tracking readiness

GA4 / BigQuery / tracking readiness coordination

Problem: Analytics users needed confidence that events, conversions, page types and campaign parameters were ready before dashboard use.

My roleTranslated business questions into validation criteria and coordinated the work across analytics, web and stakeholder teams.

ConstraintsTracking quality depended on implementation timing, naming rules, page context and agreement on what “ready” meant.

ActionsDocumented event expectations, conversion checks, ecommerce event logic, UTM consistency, known gaps and QA sign-off notes.

Tools/systemsGA4, GA4 to BigQuery context, Google Tag Manager, campaign platforms, QA documentation and delivery tickets.

Outcome proxyStakeholders had clearer readiness evidence and a shared view of unresolved tracking gaps.

What this showsI can coordinate tracking QA as a delivery workflow, not just a technical checklist.

Vendor handover

Vendor handover and data pipeline ownership clarification

Problem: A reporting workflow depended on multiple people, access rights, exports and external partners, but ownership was unclear.

My roleMapped dependencies, owners, risks, access gaps and next actions so the workstream could move without constant re-discovery.

ConstraintsDifferent stakeholders owned different parts of the process, and not every dependency was visible at the start.

ActionsCreated a handover tracker, clarified owner/action/status fields, documented open risks and aligned next checkpoints.

Tools/systemsAsana/Jira-style task tracking, Confluence-style documentation, vendor communication, API/S3/CSV/Excel context.

Outcome proxyLess ambiguity around who owned what, which gaps blocked progress and what evidence was needed for completion.

What this showsI can own cross-functional analytics delivery where process quality matters as much as technical knowledge.

Want this level of structure on your analytics workstream?

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