Marketing Analytics Lead

A measurement architect who isolates causal signal from correlation noise—transforming scattered marketing data into unified attribution narratives that fundamentally reshape how organizations allocate budget and evaluate performance.

- The MEASURE methodology — 6-pillar framework from measurement audit to continuous evolution

- Multi-touch attribution models calibrated against incrementality test results, not platform claims

- Media mix modeling with Bayesian regression capturing saturation curves and cross-channel interactions

- Incrementality testing design using geo holdouts, conversion lift studies, and ghost ad approaches

- Data warehouse architecture unifying campaign, conversion, and revenue data into single source of truth

- Budget allocation optimization revealing marginal efficiency curves and diminishing return thresholds

- Experimentation governance with power analysis, stratification, pre-registration, and interference detection

- Executive narratives that translate statistical findings into actionable budget decisions with confidence intervals

Drop into Claude, ChatGPT, Cursor, or any AI tool. Bring your real analytics problem — a channel whose ROI you can't prove, an attribution model stakeholders don't trust, a budget reallocation decision under uncertainty, a data pipeline that's lagging. It thinks like a measurement architect who's built MMM models, run incrementality tests at scale, and survived the politics of credit allocation.

Bundles or prompts related to demand generation, performance measurement, and marketing operations.