Know Which Channels Drive Revenue And Where To Invest Next

Marketing budgets are under more scrutiny than ever, and the question every marketing leader faces is the same: which channels are actually driving results, and where should the next dollar go? Media Mix Modelling (MMM) answers that question with statistical rigour, giving you a clear, data-backed view of how each channel contributes to your business outcomes.

Unlike attribution models that rely on cookies and click-path data, MMM works with aggregated historical data to measure the true incremental impact of each marketing channel. This makes it resilient to privacy changes, ad blocker adoption, and the decline of third-party cookies. It is the most robust method available for understanding the relationship between your marketing investment and revenue.

MMM uses statistical regression analysis on your historical marketing spend and business outcome data to isolate the contribution of each channel. By accounting for external factors like seasonality, economic conditions, and competitive activity, the model separates genuine marketing-driven lift from background noise.

The result is a set of response curves for each channel that show how incremental spend translates to incremental revenue. These curves reveal diminishing returns, identify channels with headroom for growth, and highlight areas of over-investment. This is not guesswork or rule-of-thumb allocation. It is a quantitative framework grounded in your own data.

We build models using your marketing spend data, revenue or conversion data, and any available external variables. The modelling process includes data preparation, feature engineering, model fitting, validation, and scenario simulation. We present the findings in a clear, actionable format designed for marketing and finance stakeholders.

Understand how much revenue each marketing channel is responsible for, from paid search and social to TV, out-of-home, and organic.

Model "what if" scenarios to see how reallocating budget across channels would impact total revenue. Identify the optimal mix before committing real dollars.

See where additional spend in a channel stops delivering proportional returns, so you can redirect budget to higher-impact areas.

Separate the revenue you would earn without marketing (baseline) from the revenue driven by your campaigns (incremental lift). This clarity is essential for accurate ROI measurement.

Account for factors outside your control, so you measure true marketing effectiveness rather than attributing seasonal demand to campaign performance.

MMM is best suited for organisations that invest across multiple marketing channels and have at least 12 to 24 months of historical spend and outcome data. It is particularly valuable when:

You need to justify or defend marketing budgets to finance or leadership with quantitative evidence.

Attribution models are incomplete or unreliable due to privacy regulations, cross-device behaviour, or offline channels.

You are planning a significant budget reallocation and want to model the impact before committing.

You want to understand the interplay between brand and performance channels, including how upper-funnel activity influences lower-funnel conversions.

If you are earlier in your data maturity journey or have limited historical data, we can advise on the best path forward, whether that is starting with a simpler channel assessment or building the data foundation needed for a full MMM engagement.