Reallocating a marketing budget with explicit rules.

SUPPORTED DECISIONAuthorise a transfer only if the prudent expected gain stays positive after costs and if the minimums of the source channel are protected.

Evidence status

What was reproduced, and what it does not prove.

The fixture and the Python run verify that minimum and maximum shares are respected, the robust marginal calculation and the rescaling of the educational allocator's constraints. They prove neither the persistence of a signal nor the gain of a market reallocation.

  1. Technical specification of the budget allocator, specification in French (opens in a new tab)

    v1, 31 August 2026 · CC BY 4.0 · specification in French · Method document written by marketing-mix.net. The figures are illustrative: they are not market measurements.

Key distinctions

Three conditions before calculating.

01

A signal is not yet a decision

A fall can come from noise, from a conversion delay, from a stockout or from a change of measurement. The rule sets a reference, a window and a threshold before any move.

02

The mobile tranche is bounded

Commitments, minimum presence, learning in progress and capacity determine the share genuinely movable. The total budget of a channel is never assumed fungible.

03

Reversal is prepared

The review date, the stopping signal and the restoration reserve are defined before execution. A rule with no documented exit is not reversible.

Method

Writing a reallocation rule in four decisions

  1. 01Qualify the trigger

    Choose a measure aligned with the decision — marginal contribution, incremental cost, saturation, capacity or availability; set the minimum period, the reference and the uncertainty.

  2. 02Compute the prudent tranche

    Compare the contribution lost at the source with the one expected at the destination; retain a prudent bound, then deduct the transition costs and the continuity minimums.

  3. 03Test the constraints

    Check coverage, learning volume, stock, service, calendar and correlations. A blocking constraint forbids the move even if the central gain is positive.

  4. 04Log the revision

    Record amount, assumptions, owner, effective date, observation window and the conditions to continue, stop or restore.

DECISION TOOL

The register of reallocation rules

Every move connects an observed signal to a window, a tranche, a guardrail and a review decision.

RuleSignalWindowThresholdTrancheGuardrailReviewDecision
R01Marginal return4 weeks+0.30€40kStable reachD+14Shift
R02Net prudent gain6 weeks> €0€40kObserved rangeD+42Extend
R03Availability7 days< 95%€0Restore if out of stockD+7Block
R04Net prudent gain6 weeks< €0−€40kReserve availableD+42Restore
CSVDownload the reallocation register↓
ILLUSTRATIVE EXAMPLE · SIMULATED DATA

Moving €80k in two steps rather than €200k at once

01 · SITUATION

Illustrative example: channel A has a prudent marginal return of 0.10 and channel B of 0.62. A has €500k but must keep a floor of €420k. The transition cost is estimated at €6k.

02 · CALCULATION

The maximum tranche is 500,000 − 420,000 = €80,000. The gross prudent gain is 80,000 × (0.62 − 0.10) = €41,600. After €6,000 of transition, the prudent expected gain is €35,600.

03 · DECISION

The rule authorises €40k immediately and then €40k after review. It blocks any further transfer as long as B's response and A's coverage have not been re-estimated.

Acceptance conditions

What must be true to act.

  1. 01

    The trigger uses an incremental or marginal measure adapted to the horizon.

  2. 02

    The amount respects minimums, maximums, commitments and observed ranges.

  3. 03

    The gain stays positive under a prudent assumption after transition costs.

  4. 04

    A review date, a stopping threshold and a condition for reverting are written before execution.

Limits

What this analysis does not prove.

  • A rule does not correct a biased measurement nor a poorly identified response curve.
  • Interactions between channels can invalidate a calculation based on separate effects.
  • Brand effects and long delays can require dedicated floors.
  • Changes that are too frequent disturb learning and prevent evaluation.

References

Works cited.

  1. Google Meridian, ROI, marginal ROI and response curves, official documentation, 2026 (opens in a new tab)
  2. Google Meridian, interpreting the visualisations and bounding extrapolation, 2026 (opens in a new tab)
  3. Meta Robyn, MMM analysis guide and budget allocation (opens in a new tab)