“It is difficult to hide from the illumination of a market response model.” — Hanssens et al. (2003).
Marketers need to align their brand’s marketing mix into a coordinated programme designed to drive revenue and profit. To achieve desired goals, they need to know how to optimize the brand’s performance. This requires an understanding of how sales respond to the elements of the marketing mix. It would be useful if there was a method to assess the impact of these variables, on sales and ROI.
Though far from perfect, there is such a method — it is referred to as marketing mix modelling or market response modelling. These models use statistical methods of analysis of historic market data, to estimate the impact of various marketing activities on sales. They reveal the effectiveness of the marketing mix elements in terms of their contribution to sales and profits. This knowledge empowers marketers to craft plans that optimize the use of resources and infuse marketing decisions with the logic and discipline of analytics.
Marketing mix modelling is a vast topic covering a wide spectrum of methods and techniques. This chapter focusses on the methods and the models that are of greatest relevance to marketing practitioners.
The models are multifaceted, often encompassing interactions and interdependencies within marketing mix variables, and dynamic effects such as lagged responses. The chapter highlights the facets that need to be considered, and it provides guidance on how to apply the models, and how to interpret and analyse them.
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In an analytics-driven business environment, this analytics-centred consumer marketing workshop is tailored to the needs of consumer analysts, marketing researchers, brand managers, category managers and seasoned marketing and retailing professionals.
Solutions for market mix modelling.
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