"algo-ad-budget"

Ad Budget Allocation Optimization

Overview

Budget allocation distributes a total advertising budget across campaigns to maximize overall returns. Uses the equal marginal returns principle: allocate until the marginal CPA (or marginal ROAS) is equalized across all campaigns. Handles diminishing returns and budget constraints.

When to Use

Trigger conditions:

• Distributing a fixed budget across multiple campaigns or channels
• Identifying diminishing returns and optimal spend levels per campaign
• Rebalancing budget after performance changes

When NOT to use:

• When optimizing bids within a single campaign (use bidding strategy)
• When there's only one campaign (nothing to allocate across)

Algorithm

IRON LAW: Equal Marginal Returns Principle
Optimal allocation makes the MARGINAL return of the last dollar
equal across ALL campaigns. If Campaign A's marginal CPA is $5
and Campaign B's is $15, shift budget from B to A until they equalize.
Total budget constraint: Σ budget_i = total_budget.

Phase 1: Input Validation

Collect per-campaign: historical spend, conversions, revenue at multiple spend levels. Need at least 3 data points per campaign to fit response curve. Gate: Sufficient historical data to estimate response curves.

Phase 2: Core Algorithm

1. Fit response curve per campaign: conversions = f(spend). Common models: log curve, power curve, or S-curve
2. Compute marginal return curve: f'(spend) for each campaign
3. Allocate: use Lagrangian optimization or iterative greedy — assign next marginal dollar to campaign with highest marginal return
4. Apply constraints: minimum spend floors, maximum caps, channel-specific rules

Phase 3: Verification

Check: total allocation = total budget, no campaign below floor or above cap, marginal returns approximately equal at boundaries. Gate: Allocation sums to budget, constraints satisfied.

Phase 4: Output

Return allocation table with expected performance projections.

Output Format