Measuring marketing impact without user tracking.
Geo Experiment Designer
Geo-lift tests, causal inference, marketing impact
Best for
- ▸Measuring incrementality of TV/OTT campaigns when user-level tracking isn't possible
- ▸Testing causal impact of price changes across geographic markets
- ▸Designing geo-lift tests for new product launches in retail chains
- ▸Validating true lift of brand awareness campaigns using regional experiments
What you'll get
- ▸Stratified randomization design with 40 matched DMA pairs, power analysis showing 80% power to detect 5% lift, and CausalImpact implementation plan
- ▸Synthetic control methodology using 3 treatment cities with weighted control from 25 donor markets, including pre-treatment validation tests
- ▸Complete experimental protocol with exclusion criteria, spillover mitigation strategies, and Bayesian analysis framework for measuring incremental revenue
Clear business question, available geographic units, pre-treatment outcome data, and specific KPI to measure with defined success criteria.
Complete experimental design with randomization strategy, sample size calculations, analysis plan, and statistical framework for measuring causal lift.
What's inside
“You are a Geo Experiment Design Scientist. You design, validate, and analyze geographic experiments to measure true causal incrementality when user-level randomization is impossible. - **Randomization-first thinking.** You refuse to claim causal effects from observational geographic comparisons and ...”
Covers
Not designed for ↓
- ×User-level A/B testing or individual customer randomization
- ×Attribution modeling for digital advertising channels
- ×Simple correlation analysis between marketing spend and sales
- ×Real-time campaign optimization or bidding algorithms
SupaScore
88.53▼
Evidence Policy
Standard: no explicit evidence policy.
Research Foundation: 8 sources (2 books, 3 paper, 1 official docs, 1 academic, 1 web)
This skill was developed through independent research and synthesis. SupaSkills is not affiliated with or endorsed by any cited author or organisation.
Version History
v6.0 wave-1 repair: re-distilled from masterfile/v2 (truncation incident 2026-06, delta-first rules)
v5.5 final distill
Pipeline v4: rebuilt with 3 helper skills
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
Marketing Incrementality Measurement
End-to-end workflow for measuring true marketing impact, from initial experimental design through geo-randomization to causal analysis and attribution modeling
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