Budget Advisor
Turn dated channel history into an evidence-aware budget decision. The advisor models only stable marginal patterns and preserves the rest at recent spend.
Decision canvas
Bring dated channel history
Use weekly or monthly spend with conversions or revenue. Your rows stay in this browser session.
Loads a local 16-week example with three modeled channels and one preserved channel.
No history loaded.
Paste channel history
History already loaded
Replace the current decision canvas?
Replacing history clears the current model, constraints, results, and local downloads.
Needs correction
Resolve the import findings
Only row number, semantic field, and controlled guidance are shown here.
Readiness
What the history can support
| Channel | Treatment | Evidence gates |
|---|
Allocation
Budget plan
Choose a budget and horizon to build the plan.
What supports this recommendation?
- Evidence quality
- Main driver
- Caveat
Inspect cleaned history
Review the normalized periods used by the model. Rejected cell values are not reproduced.
How the budget model works
Budget Advisor uses observational channel history to compare modeled marginal response while keeping unsupported channels in the plan.
- Evidence gates — A channel needs at least 12 complete periods, positive spend and outcome coverage, four distinct spend levels, and at least 20% robust spend variation before a curve is admitted.
- Modeled marginal response — Admitted channels use their observed diminishing-return relationship to compare the expected outcome from the next budget increment.
- Preserved channels — Channels that fail a gate are held at their median recent-four-period spend rate. They do not receive optimized incremental budget.
- Financial mapping — Contribution or profit columns require an explicit choice about whether marketing spend is already deducted.
This is observational decision support, not causal incrementality or a marketing mix model. Tracking changes, creative, audience, pricing, seasonality, and external conditions can break a historical relationship.
Budget optimization FAQ
What data do I need?
Bring weekly or monthly rows with period, channel, spend, and at least one outcome: conversions, revenue, or a financial contribution measure. A response curve needs at least 12 complete periods and meaningful spend variation; more rows alone do not guarantee admission.
What happens when a channel cannot be modeled?
The channel is preserved at its median recent-four-period spend rate. Its observed rows remain inspectable, but it cannot receive the optimized remainder until its evidence clears every gate.
How are revenue and profit handled?
Revenue is modeled separately from conversions. If you import contribution, gross profit, or profit, you must explicitly state whether marketing spend has already been deducted so the plan does not subtract cost twice.
How accurate are the recommendations?
The output describes patterns in the supplied history. It does not prove that spend caused the outcome, forecast a calibrated range, or make six months of data inherently reliable. Treat the plan as a testable allocation decision and monitor live performance.
Why use a diminishing-return curve?
A diminishing-return curve is fitted only when the observed channel history passes the stability gates. The advisor does not force a generic power law onto every channel; unsupported histories stay preserved instead.