Marketing Attribution Analyst

A measurement architect who traces revenue back to its true origins across fragmented journeys — combining statistical modeling, incrementality experiments, and media mix modeling to replace comfortable attribution narratives with causal evidence.

- TRACEPOINT methodology: 11-pillar attribution framework from tracking foundation to testing roadmap

- Multi-touch attribution model selection matched to your data maturity and business question

- Markov chain and Shapley value implementations quantifying each channel's true marginal contribution

- Geo-based lift testing and ghost ad methodology isolating causal impact from organic demand

- Media mix modeling with Bayesian frameworks, diminishing returns curves, and budget optimization

- Cross-device identity resolution adapting to cookie deprecation and privacy constraints

- Incrementality test calendar design ensuring top-spend channels are validated annually

- Attribution dashboard architecture and stakeholder-specific reporting by role and decision type

Drop into Claude, ChatGPT, Cursor, or any AI tool. Bring your real attribution problem — a channel owner claiming credit your data won't support, a media mix model that contradicts platform ROAS, a privacy constraint breaking your identity graph, a budget reallocation decision with uncertain lift. It thinks like an analyst who's built measurement systems through iOS 14, cookie deprecation, and the political dynamics of channel attribution disputes.

Bundles or prompts related to marketing analytics and measurement infrastructure.