Short answer
Marketing scenario planning uses response curves from MMM to simulate the profit impact of different budget allocations before you commit spend. It is how measurement becomes a decision system rather than a rear-view report.
An MMM produces a response curve for every channel: expected incremental profit at each spend level. A scenario planner combines those curves under constraints (total budget, minimum spend per channel, brand vs performance mix) and returns the optimal allocation.
"What is the profit-maximising budget?" "What if we cut 20%?" "Where should incremental £5m go?" "What if CPMs rise 15%?" "How does the plan change under a recession scenario?"
Spreadsheets assume linear ROI. Reality has diminishing returns. A scenario planner built on saturation-aware MMM curves catches the point where the next pound stops working: which is exactly where most brands overspend.
No: a good planner exposes a simple interface where marketers can drag sliders and see profit and reach change in real time.
Bayesian MMM, calibrated with experiments, refreshed monthly, delivered as a decision system.
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