Econometrics is the application of mathematical and statistical techniques to economics in the study of problems, the analysis of data, and the development and testing of theories and models.
Thus, it aims to give empirical content to economic relations and probably gives you already a hint how useful the unification of economics, mathematics, and statistics can be for making marketing decisions. In fact, adding empirical content to economic theories paves the way for proper forecasting and evaluation.
Since the amount of data seems to increase at the speed of light and we are starting to talk about exabytes, zettabytes and yottabytes, each a thousand times larger than the previous, we have actually no other choice than to seriously consider embracing marketing combined with econometrics, as it is capable of depicting the different levels and factors that best explain a result.
However, econometric studies needs at least three years of weekly marketing data for providing detailed results. In addition to a sufficiently long time span, the data being measured needs to vary over time to be able to compare the inputs to the output side of the equation. Thus, companies preparing to use econometrics to determine the optimal marketing mix should ensure that data is weekly and varies over the study period.
Besides, just figuring out what's working and what's not can be a major headache, too. Especially since the economy and outside factors play an important role for the findings. Econometrics can calculate an equation built from historical data and determine e.g. what's driving sales. On one side of the equation is the goal or the dependent variable, on the other side the independent variables that includes the marketing spend for traditional and new media, sponsorship, direct marketing, etc. Independent variables include competitor activities and some variables with no monetary value, such as social media and public relations.
As an art and a science, econometrics examines the inputs (independent variables) each week and the outputs (dependent variables) during the same week and following weeks for longer-term effects. By analyzing input and outputs every week over a three-year period, the numerous marketing levels occurring over time provide a sufficient variance for a comprehensive analysis. The subsequent equation of calculated results mimics actual outcomes and predicts future market response of activities. The conclusion of the analysis can then be used to establish a marketing budget and optimally allocate that budget across marketing activities, products, customer segments and regions.
By Daniela La Marca