Marketing mix modeling estimates how advertising and other factors relate to business outcomes over time. The decision is usually where to spend the next part of a budget. That requires an estimate of incremental response, alongside uncertainty about what would have happened without the advertising.
Google’s September 2025 Meridian update reflects continued investment in open-source marketing measurement. Access to a model is useful; the quality of a budget decision still depends on the data, assumptions and evidence behind its estimates.
Define the outcome and comparison
Choose a consistent outcome such as orders, qualified opportunities or net sales. Document returns, reporting delays and changes in tracking. A discontinuity in the measurement system should not quietly become a change in advertising effectiveness.
Include plausible non-media influences, such as price changes, distribution, promotions and seasonality. An omitted event that coincides with a campaign can distort the model’s interpretation. The model cannot recover information that the business never recorded.
Distinguish average return from marginal return
Average return summarizes performance over an observed spending range. Marginal return asks what an additional amount of spending might produce at the current level. Those quantities can differ when a channel approaches saturation.
For an illustrative comparison, a channel with strong historical returns may offer limited additional reach. Another channel may have lower average returns but more room to grow. Examine response curves and uncertainty before treating either estimate as a spending instruction.
Use experiments as additional evidence
Where feasible, compare model estimates with well-designed geographic or audience experiments. Check that the experiment’s outcome, time period and treatment match the quantity being estimated. An experiment on one audience does not automatically validate every channel or market.
Keep the experimental result distinguishable from the model’s assumptions. Our guide to marketing mix modeling gives the wider framework for evaluating these contributions.
Change budgets in controlled steps
Keep proposed spending changes within a defensible range of the observed data. Extreme reallocations can rely on extrapolation that has little support. Document the expected outcome, uncertainty and conditions that would trigger a review.
Evaluate the downstream sales process too. More leads may not mean more accepted opportunities; use lead-quality measures to understand the handoff. A measurement plan should separate acquisition effects from changes in sales follow-up.
Start with a decision you can review
Select a budget question, a consistent reporting window and an owner for the assumptions. Talk to NextBrain AI about the data preparation and analytical workflow needed to assess the decision.