What this laboratory teaches
The laboratory applies fixed illustrative response curves to three channel budgets. It demonstrates why additional spend can produce diminishing modeled response and why reallocating a fixed budget can change the central estimate and uncertainty range.
It is intentionally transparent: the curves are examples, not parameters learned from your company’s history.
Formula and worked example
The illustrative response curve behind the laboratory.
Ceiling × (1 − e^(−spend ÷ half-saturation)) Spend produces a diminishing illustrative response as it approaches the fixed example ceiling.
Baseline outcome + sum of channel contributions The channel examples are added to a user-entered baseline; none of these values are learned from observed company data.
Central outcome ± max(15% of outcome, 80% of incremental contribution) A teaching boundary added around the example—not a statistical confidence or credible interval.
These fixed equations explain the interface. They do not estimate causality, forecast an outcome, or recommend a budget.
The three channel contributions are added to the baseline outcome. The illustrative range uses the larger of 15% of the modeled outcome or 80% of the incremental contribution on either side of the central value.
With the default weekly inputs—$60,000 paid search, $40,000 paid social, $30,000 video and display, and a 1,000-order baseline—the fixed example curves produce a central modeled outcome of about 1,103 orders. That is a demonstration of the math, not evidence about any real channel.
What it cannot tell you
The output is not a forecast, causal estimate, attribution result, or budget recommendation. It does not use observed outcomes, media history, controls, experiments, geography, seasonality, priors, or a fitted statistical model.
Use it to understand a modeling concept—not to approve a budget.
The next real step
Complete the MMM data-readiness worksheet and define the decision, outcome, row grain, historical window, media inputs, controls, and validation plan. Continue through the Build a Marketing Mix Model hub when the data contract is ready to review.