Incrementality testing or MMM — which is more accurate?

They're different tools: experiments give causal proof on the channels you test; MMM gives continuous, broad coverage. Many teams triangulate both.

Does The Ad Spend replace either?

No — it's the operational layer (change record + causal detection + action), not a channel-measurement model. It pairs with either.

How should I decide between Measured and Prescient AI?

Decide on rigor versus cadence. Measured's geo experiments give causal proof for the channels you test, on an experiment timeline. Prescient's daily MMM gives continuous coverage of the whole mix without formal tests. Teams that can afford both often triangulate.

Is there an alternative to Measured and Prescient AI?

For channel-level measurement, these two are the field. For operational causality — which settings change moved the metric, who made it, and what to do next — The Ad Spend works one layer down, on a permanent record of the account, and complements either measurement tool.

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Head-to-head · MMM & incrementality (measurement)

Measured vs. Prescient AI

Two ways to measure the media mix.

Measured vs. Prescient AI — feature comparison
Capability	Measured	Prescient AI
Core method	Geo incrementality experiments + Bayesian MMM	ML-based marketing-mix modeling
Proof style	Experiment-backed (test and measure)	Modeled (daily, pixel-free)
Speed	Experiment cycles	Daily updates
Budget guidance	Where to invest, test-validated	Daily campaign-level recommendations
Best for	Teams wanting experiment-proven incrementality	Teams wanting always-on modeled guidance

Choose

Measured

Pick Measured if you want experiment-backed proof a channel is incremental before you move budget — especially for hard-to-track media.

Choose

Prescient AI

Pick Prescient AI if you want always-on, daily MMM and budget recommendations without running formal experiments.

Frequently asked

Incrementality testing or MMM — which is more accurate?: They're different tools: experiments give causal proof on the channels you test; MMM gives continuous, broad coverage. Many teams triangulate both.
Does The Ad Spend replace either?: No — it's the operational layer (change record + causal detection + action), not a channel-measurement model. It pairs with either.
How should I decide between Measured and Prescient AI?: Decide on rigor versus cadence. Measured's geo experiments give causal proof for the channels you test, on an experiment timeline. Prescient's daily MMM gives continuous coverage of the whole mix without formal tests. Teams that can afford both often triangulate.
Is there an alternative to Measured and Prescient AI?: For channel-level measurement, these two are the field. For operational causality — which settings change moved the metric, who made it, and what to do next — The Ad Spend works one layer down, on a permanent record of the account, and complements either measurement tool.

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