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Measurement & Market

What is a counterfactual baseline?

A counterfactual baseline is an estimate of what would have happened without the change being measured — what sales would have been if the price increase, promotion, or menu change had never shipped. It is the honest denominator for impact measurement, replacing the misleading defaults: last year's number, the week before, or the system average, all of which bundle the change's effect together with seasonality, weather, and market trend.

Baselines are built from the patterns in a store's own history — trend, seasonality, day-of-week structure — often disciplined by control stores or market data that reveal what similar locations did over the same window. The measured impact is then the gap between actual results and that expectation, not the gap between actual results and an arbitrary comparison period.

The difference is not academic. A price increase followed by a 2% traffic decline looks damaging against last month — and looks like a win if the market around the brand declined 4% over the same weeks. Same data, opposite conclusion; the baseline is what decides which is true.

Why it matters

Every impact claim smuggles in a comparison. Making the counterfactual explicit is what turns 'sales went up after we did X' into evidence that X worked — and it is the machinery behind honest measurement of pricing, promotions, and launches alike.

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