Platform Mix
“What’s the optimal split across Google / Meta / Microsoft?” Curves fitted per campaign over 91 days, aggregated to platform level, then solved for the split where marginal return is highest.
Given a total budget, what’s the optimal split across Google, Meta and Microsoft — or across whole portfolios? Budget Planner answers both with the same response curves the live optimiser runs on, so the plan and the execution never disagree.
One switcher, two modes — both built on the saturation curves fitted to your own campaign history, not industry benchmarks.
“What’s the optimal split across Google / Meta / Microsoft?” Curves fitted per campaign over 91 days, aggregated to platform level, then solved for the split where marginal return is highest.
“Given a total budget across portfolios, where does each increment go?” Pick an objective, choose portfolios, set the total — each budget increment flows to whichever portfolio has the highest marginal return at its current level.
The planner isn’t a separate model that drifts from reality — it reads the exact response curves the nightly optimiser allocates with. What you model is what the engine will do.
A plan you can’t interrogate is a guess with a chart. Every model run shows its working — and applies through the same staged, reviewed pipeline as everything else.
Current vs optimised split across budget levels, in three views — Revenue, ROAS, and Marginal ROAS. The marginal view shows exactly where each unit of spend hits diminishing returns.
Per-portfolio revenue change from current to optimised allocation — so you can see precisely where the gain comes from before you commit to it.
Each portfolio’s addressable ceiling is estimated from impression-share data. The planner won’t model spend a portfolio can’t actually absorb.