Mobile App Terminology

Marketing mix modeling (MMM)

What is marketing or media mix modeling (MMM)?

Also referred to as media mix modeling, marketing mix modeling (MMM) is an analytical technique used to quantify the value that various marketing inputs have on sales. In other words, the goal of MMM is to determine how much each marketing input is contributing to the company’s overall bottom line. By quantifying MMM, this not only helps in sales forecasting, but also helps marketers determine the appropriate amount of budget to allocate to each marketing channel or campaign.

As you probably know, the 4Ps of the marketing mix include: Product, Price, Place, and Promotion. While these factors are four key considerations that marketers will make in order to run a profitable campaign, MMM takes this a step further and is designed to determine how much each factor actually contributed to sales. As the blog Hurree summarizes:

If carried out correctly, MMM has the potential to streamline your marketing mix through fact-based optimisation. Using statistical data removes the guesswork from marketing activity, increasing ROI through precisely allocated budgets and accurately accounting for seasonal and channel-specific factors.

Want to use marketing mixed modeling to increase ROI?

Learn how Singular can help!

What are the uses of marketing mix modeling?

By using MMM and understanding the value of each marketing input on sales, the main use case of using this statistical analysis technique is to increase the ROI of all marketing efforts. MMM often uses techniques such as linear or multivariate regression to forecast the impact of marketing tactics on sales. For example, by creating a marketing mix model, a marketer may be able to forecast the impact that adding additional budget to ad spend will have on future sales.

Marketing Evolution provides a useful example of what you can do with the insights from MMM:

The insights derived from media mix modeling allow marketers to refine their campaigns based on a variety of factors, ranging from consumer trends to external influencers, to ultimately create an ideal campaign that will drive engagement and sales.

In short, MMM provides marketers with the ability to streamline and optimize their marketing mix with data-driven analysis. Using various statistical techniques, this removes a lot of the guesswork that goes into managing a cross-channel marketing campaign. By taking this data-driven approach to marketing, the main use case for MMM is to increase the company’s overall ROI by allocating budgets more efficiently.

Want to use marketing mixed modeling to increase ROI?

Learn how Singular can help!

How Singular facilitates MMM?

As a leader in marketing analytics and attribution, Singular is uniquely positioned to help marketers with media mix modeling for mobile apps and user acquisition. Given that tracking through IDFA is a thing of the past, mobile marketers rely on third party mobile measurement partners (MMPs) like Singular to fill in the missing data. As highlighted in our blog posts on media mix modeling for mobile apps, the next generation of attribution will involve combining MMM techniques with other mobile attribution techniques to get a complete picture of a marketing campaign’s ROI:

Combining all that signal while simultaneously silencing the noise to generate insights for growth: that’s the next challenge. And MMM has a seat at that table as part of next-gen attribution. 

You need huge amounts of data to make media mix modeling or marketing mix modeling work. Singular provides that both on the campaign side and the attribution side.

In summary, by combining MMM with other mobile attribution techniques, marketers are able to accurately determine which channels and campaigns are driving the highest ROI. With this data in hand, marketers can also create accurate sales forecasts and better allocate their marketing budgets to achieve their desired results.


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