PROGRAM | Data Platforms | 2022 -> 2025
Marketing Analytics & Incremental Lift Optimization
Decision-grade measurement and targeting models aligned to incrementality, not vanity metrics.
PythonPredictive modelingTargetingExperimentation mindsetProduction integration
- Incremental Return on Ad Spend (iROAS) analytics for budget decisions.
- CLTV, propensity, and look-alike models for targeting efficiency.
- Insight -> recommendation workflows for partners and stakeholders.
Context
- Optimization without measurement discipline produces expensive hallucinations.
- Incrementality is the anchor: what changed because we acted?
What we built
- Analytics frameworks for acquisition/retention/product decision loops.
- Targeting models (CLTV/propensity/look-alike) designed for operational use.
- Reporting artifacts that connect model outputs to actions and expected lift.
Engineering choices
- Model interfaces designed for stable production integration.
- Guardrails to prevent silent degradation (data drift and monitoring mindset).
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