Causal measurement for ads
This pillar focuses on causal inference and experimentation strategies for advertising. It highlights uplift modeling, geo experiments, and measurement pitfalls that surface at scale.
Recommended reading order
- Start with foundational measurement posts.
- Dive into experimentation design and guardrails.
- End with case studies on improving incrementality.
Start here
- Auction and pacing simulations for ads lift — Counterfactual simulations that stress pacing, budgets, and auction dynamics before running expensive experiments.
- Geo experiments for ads lift without slowing delivery — Designing geo experiments with CUPED adjustments, overlap checks, and playbooks teams can actually run.
Posts in this pillar
- Auction and pacing simulations for ads lift — Counterfactual simulations that stress pacing, budgets, and auction dynamics before running expensive experiments.
- Geo experiments for ads lift without slowing delivery — Designing geo experiments with CUPED adjustments, overlap checks, and playbooks teams can actually run.
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