A counterfactual baseline estimates what would have happened without a campaign. Because that world cannot be observed directly, teams estimate it with controls, geo experiments, or time-series models.
The demo shades the gap between actual results and an estimated baseline. It avoids labeling every observed sale as an advertising effect.
If the baseline is wrong, the lift estimate is wrong. Check seasonality, pricing changes, and other promotions as potential confounders.
When to use
Use it before treating a before-and-after sales gap as causal impact.