Media Mix Modelling and machine-learning forecasting for mid-market and enterprise marketing budgets. Channel contribution, response curves, scenarios, and forecasts with confidence intervals.
Once a marketing budget crosses seven figures, the cost of guessing compounds. Last-click attribution can't see offline channels, can't survive privacy changes, and can't tell you what would have happened anyway. Yet most budgets are still allocated on exactly that evidence.
Forecasting & Media Mix Modelling is our premium advisory engagement for marketing and finance leaders who need allocation decisions they can defend, with statistical rigour, in language a CFO accepts.
MMM needs 12 to 24 months of spend and outcome history across multiple channels. It's built for organisations investing AUD 100k or more per month in paid media.
If you're earlier than that, start with a Marketing Effectiveness Audit; its channel mix assessment is the lightweight version of this work, and it builds the data foundation a future model needs.
We audit spend and outcome history across channels and confirm the model is feasible before you commit to the full build.
Data preparation, feature engineering, fitting, and out-of-sample validation. Every assumption documented.
We sit with marketing and finance and run the reallocation questions live: shift 20% out of a saturated channel, halve brand spend, double a growth market.
Markets move and models drift. Ongoing advisory keeps the model current and the reallocation decisions coming.
Each channel's true incremental contribution, response curves, and saturation points, separated from baseline revenue.
Machine-learning forecasts built on your own data with confidence intervals, not single-point promises.
Budget reallocation modelled before you commit real dollars, presented in language finance accepts. Not a 90-slide appendix.
Tell us about your channels and spend history, and we'll confirm whether a model is feasible before you commit.
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