Marketing mix modeling

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Marketing Mix Modeling (MMM) is a forecasting methodology used to estimate the impact of various marketing tactic scenarios on product sales. MMMs use statistical models, such as multivariate regressions, and use sales and marketing time-series data. They are often used to optimize advertising mix and promotional tactics with respect to sales, revenue, or profit to maximize their return on investment.

Using these statistical techniques allows marketers to account for advertising adstock and advertising's diminishing return over time, and also to account for carry-over effects and impact of past advertisements on the current sales campaign. Moreover, MMMs are able to calculate the magnitude of product cannibalization and halo effect.^[1]

The techniques were developed by specialized consulting companies along with academics and were first applied to consumer packaged goods, since manufacturers of those goods had access to accurate data on sales and marketing support.^{[citation needed]} Improved availability of data, massively greater computing power, and the pressure to measure and optimize marketing spend has driven the explosion in popularity as a marketing tool.^{[citation needed]} In recent times MMM has found acceptance as a trustworthy marketing tool among the major consumer marketing companies.