The 2026 measurement consensus is triangulation: calibrate the MMM with an incrementality test. On simulated data with a known answer, the recommended recipe moved a badly biased ROI estimate about two thirds of the way to the experiment’s answer and then stopped, leaving it 77% above the truth. The prior lost to the likelihood, because a misspecified MMM is confidently wrong. Here is the diagnostic to run before you calibrate anything.

Put spend on the right-hand side of a fixed effects regression and the coefficient looks like marginal return. On simulated data with randomly assigned dose, it overstates the true marginal return by 31%. Here is why, and how the new contdid package fixes it.