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Concept
Marketing mix modeling
Summary
Marketing mix modeling (MMM) is statistical analysis such as multivariate regressions on sales and marketing time series data to estimate the impact of various marketing tactics (marketing mix) on sales and then forecast the impact of future sets of tactics. It is often used to optimize advertising mix and promotional tactics with respect to sales revenue or profit.
The techniques were developed by econometricians and were first applied to consumer packaged goods, since manufacturers of those goods had access to accurate data on sales and marketing support. 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. In recent times MMM has found acceptance as a trustworthy marketing tool among the major consumer marketing companies.
The term marketing mix was developed by Neil Borden who first started using the phrase in 1949. “An executive is a mixer of ingredients, who sometimes follows a recipe as he goes along, sometimes adapts a recipe to the ingredients immediately available, and sometimes experiments with or invents ingredients no one else has tried."
According to Borden, "When building a marketing program to fit the needs of his firm, the marketing manager has to weigh the behavioral forces and then juggle marketing elements in his mix with a keen eye on the resources with which he has to work."
E. Jerome McCarthy, was the first person to suggest the four P's of marketing – price, promotion, product and place (distribution) – which constitute the most common variables used in constructing a marketing mix. According to McCarthy the marketers essentially have these four variables which they can use while crafting a marketing strategy and writing a marketing plan. In the long term, all four of the mix variables can be changed, but in the short term it is difficult to modify the product or the distribution channel.
Official source
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