We identify which channels are genuinely driving revenue, independent of channel-reported data, and exactly where to reallocate spend for stronger returns.
How does January Digital approach media mix modeling?
Every platform reports its own performance in the best possible light. MMM is the only tool that evaluates the full media mix independently, isolating each channel’s true incremental contribution to revenue without relying on pixels, last-click attribution, or what any platform says about itself.
We build Bayesian statistical models on 2+ years of historical spend and performance data, controlling for seasonality, promotions, and external factors. The output is not a channel ranking. It is a clear, defensible reallocation plan that tells you where you are over-invested and where you have room to scale.
How do you know which channels are actually driving revenue?
The honest answer is that most brands do not know, because the tools they use to measure performance were built by the platforms being measured. MMM removes that conflict. It evaluates the full mix holistically, using historical data to isolate each channel’s genuine contribution to revenue independent of what any single platform reports.
We also feed past incrementality test results into the model to anchor it to reality, which makes the output more accurate and more actionable than a model built on spend data alone.
What does the MMM process look like?
We collect 2+ years of spend and revenue data across all channels, build a Bayesian model that controls for seasonality, promotions, and external factors, and run a budget optimizer across thousands of scenarios. The deliverable is channel-level KPIs and a clear reallocation plan with projected outcomes at multiple spend levels, so leadership can make budget decisions with evidence rather than intuition.
Every model includes quantified uncertainty so you know how confident to be in each recommendation.
When does MMM make the most sense?
MMM tends to be most valuable when a brand is heading into budget planning season and needs a defensible allocation framework, when internal teams are debating channel investment from their own siloed data, or when significant spend is going into channels like TV, CTV, or OOH that have no click trail. If your ROAS looks strong but revenue growth does not feel like it matches, MMM is usually the right place to start.
What results has January Digital driven for clients through media mix modeling?
For Tanger, MMM-driven reallocation delivered an 18 to 25% reduction in incremental cost per traffic, with projected incremental traffic growth of 29 to 32% year over year. The model ran at 82% accuracy, giving leadership confident planning ranges rather than point estimates. For Carhartt, MMM informed a $391M+ revenue forecast across 11 channels at 18% MAPE for FY26 to 27.