The primary function of all marketing mix models is to quantify the sales contribution of marketing activities, with a view to calculating Return on Investment (ROI). To accomplish this, all such models employ econometric techniques to decompose product sales into base and incremental volume. Models that focus solely on incremental volume often recommend a marketing budget allocation skewed towards promotional activity: short-run sales respond well to promotions, yet are less responsive to media activity – particularly for established brands. This, however, ignores the long-run view: that is, the potential brand-building properties of successful media campaigns on the one hand and the brand-eroding properties of heavy price discounts on the other. Acknowledging and quantifying these features is crucial to a complete ROI evaluation and a more strategic budget allocation.

This article puts forward a unique approach to resolving this issue. Measuring the long-run impact of marketing investments essentially amounts to quantifying their impact on the trend component of the sales series: that is, on the evolution in base sales over time. However, this is not possible in conventional models since base sales are essentially fixed by construction. To deal with this problem, the marketing mix model needs to be re-structured as an Unobserved Component Model (UCM) to accommodate both short-run and long-run variation in the data. The former is used to calculate ROI on marketing investments in the usual way. The latter measures the evolution of brand preferences over time. This generates an evolving baseline which, when combined with marketing investments and consumer tracking information, allows a quantification of long-run ROI.

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