Marketing mix modelling: assess effects and limits.
Assess whether your data supports meaningful modelling. Consider budget questions, external factors and uncertainty before making decisions.
Which budget decision should the model support?
modelling examines relationships between marketing activity, other factors and a business outcome over time. Its usefulness depends on data, assumptions and evaluation. We start with a specific budget question and assess whether the available material supports a viable approach.
Uncertainty belongs in the decision
A model can support scenarios, but cannot guarantee an optimal budget allocation. Seasonality, pricing, distribution and simultaneous activity can affect estimates. Assumptions, uncertainty ranges and alternative explanations must remain visible.
Assess feasibility first
An agreed review examines the outcome, time series, granularity and relevant factors. You receive an assessment of data gaps and a proposal for method and validation. Whether modelling proceeds, and with which specialist roles, is decided on this basis.
How we deliver
Agree the task
Define a budget question and a suitable outcome.
Review the data
Review history, variation, completeness and relevant factors.
Evaluate an approach
Justify the method, assumptions and possible validation.
Interpret findings
Assess usefulness, uncertainty and decision limits.
Define the next step
Document findings, limitations and ownership. Agree implementation and operation separately.
Questions before starting
Sources and technical context
- Google Meridian: MMM and causal inference
Methodological assumptions and limits of causal claims in MMM.
Start with a concrete question
Tell us the decision and the available data. Together we assess a useful first step.
Discuss MMM feasibility