What is Marketing Mix Modeling?

Marketing mix modeling (MMM), also called media mix modeling, is a statistical method that analyzes time series data (chronological data) from sales and marketing. The goal of this analysis is to calculate the impact of various marketing efforts on sales and then predict the results of future strategies.

Think of it as a way of understanding the effectiveness of different marketing activities and how they each influence your sales. By analyzing your historical data, such as sales, the model quantifies the impact of your marketing channels. This is done mathematically by identifying patterns and trends in the relationship between marketing efforts and sales outcomes. To do this accurately, the model takes into account other market dynamics that affect sales, such as seasonality and channel saturation. 

flow diagram with icons showing how media mix modeling works

The success of each marketing channel can be understood by evaluating how much it contributes to incremental sales (e.g. sales that wouldn’t have happened if not for your marketing efforts). MMM breaks this down into three main components:

Effectiveness: This is about measuring sales brought in by each effort in a marketing channel. For example, if you post a new ad or increase spending, how much does that increase sales?

Efficiency: This focuses on comparing the sales generated to the cost involved in the effort. It’s about maximizing sales while minimizing the cost. In simpler terms, it’s ensuring that for every dollar spent on marketing, you realize the greatest impact on sales. 

Return on Investment (ROI): This is the big-picture metric. It considers both the sales made and the costs incurred to give you an overall understanding of the value gained from your marketing efforts.

How to get started?

Creating a marketing mix model involves training a model using historical data from sales, conversions, and ad spend derived from marketing efforts. This process is not just a science but also an art, striking a balance between automated modeling tools processing large data sets, and the detailed work of experienced data scientists. Multiple iterations are created to develop the most accurate model.

Why use MMM?

MMM outputs can then be used to analyze the impact of marketing efforts on sales and conversions. For example, it allows marketing managers to see which elements contribute most to total sales, and the incremental gain in sales that can be obtained by increasing the use of a particular marketing channel. Importantly, it can also help in optimizing the marketing budget by identifying the most and least efficient marketing activities. 

Finally, the model can be used to simulate various marketing scenarios in a ‘what-if’ analysis, which can help marketing managers make informed decisions about future strategies and investments. 

Introducing Always-on Incremental Measurement (AIM): AIM is a cutting-edge MMM platform designed specifically to address the challenges faced by UA marketers. AIM’s unique approach leverages advanced machine learning that continuously adapts to new market information. The result? Precise insights that your UA buying team can take action on.

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