Privacy-Safe Measurement Analyst
Design and implement marketing measurement strategies that maintain analytical rigor while respecting user privacy, using geo-experiments, marketing mix modeling, and privacy-enhancing technologies.
SupaScore
84Best for
- ▸Design geo-experiment frameworks for incrementality testing without user-level tracking
- ▸Build marketing mix models using aggregate spend and outcome data for attribution
- ▸Implement Google Privacy Sandbox APIs for cookieless conversion measurement
- ▸Migrate from third-party cookie attribution to server-side Conversions API tracking
- ▸Calculate lift from matched market tests using difference-in-differences methodology
What you'll get
- ●Detailed geo-experiment design with market matching criteria, test duration calculations, and difference-in-differences statistical framework
- ●Marketing mix model architecture with data requirements, model validation approaches, and expected attribution accuracy ranges
- ●Privacy Sandbox implementation roadmap with API specifications, measurement use case mapping, and fallback strategies for low-consent scenarios
Not designed for ↓
- ×Legal compliance advice on GDPR consent requirements or privacy regulations
- ×Building first-party data collection infrastructure or customer data platforms
- ×Creative advertising strategy or campaign messaging optimization
- ×General web analytics setup without privacy considerations
Current measurement stack details, privacy constraints (browser/platform restrictions, consent rates), business objectives, and available data sources for analysis.
Structured measurement strategy with specific methodologies (MMM, geo-experiments), implementation roadmap, expected accuracy trade-offs, and statistical frameworks for execution.
Evidence Policy
Enabled: this skill cites sources and distinguishes evidence from opinion.
Research Foundation: 8 sources (4 official docs, 1 books, 2 industry frameworks, 1 paper)
This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.
Version History
Initial release
Prerequisites
Use these skills first for best results.
Works well with
Need more depth?
Specialist skills that go deeper in areas this skill touches.
Common Workflows
Privacy-First Attribution Migration
Audit current attribution setup, design privacy-compliant measurement strategy, and implement robust testing framework for validation
Activate this skill in Claude Code
Sign up for free to access the full system prompt via REST API or MCP.
Start Free to Activate This Skill© 2026 Kill The Dragon GmbH. This skill and its system prompt are protected by copyright. Unauthorised redistribution is prohibited. Terms of Service · Legal Notice