Both experimental and observational methods for causal modeling generally can be viewed as “counterfactual” analysis: they attempt to understand what would be the difference between the situations — which cannot both happen — where the “treatment” event (e.g., showing an advertisement to a particular individual) were to happen, and were not to happen.
