Despite the avalanche of figures and data generated by our surveys, it is very rare (and difficult) to prove a phenomenon and talk about causality in research and marketing. If we put aside the launch of new products (that did not at time zero and for which marketing efforts have a more direct impact), multiple reasons why we can not demonstrate such a marketing investment has boosted sales.
Indeed, there are three main requirements to be able to talk about causation. The first relates to the variation concomitant . In simple terms, this means that there is a strong association between an action and its result (a high budget and high sales for example). It is often Can we measure in research, but it is not causation and it is from the correlation. In everyday language, these two terms are often interchangeable, but causality is much more demanding.
We tend to think that this is the communications budget that influence sales. I could however argue that the opposite is true and that often the communication budget is derived from the sale (often a percentage of it). Causality therefore requires event A occurs before B . This requirement apparently trivial, is not so easy to follow. In the automotive industry, some manufacturers have budgets to advertising per vehicle sold. We sell more cars of brand X over its advertising budget increases!
But the third condition that makes so rare to demonstrate causality. Causality pure demand effect that there is no external variables q ui have influenced the outcome. Take the example of product placement in a film that supposedly multiplied the sales of a model car. Is this really the investment as as people who have influenced or rather the intense media coverage (viral or traditional media) associated with it that cause the phenomenon? To secure a survey result is meaningful (not to be confused with significant), we try to validate our results through different sources (observation, surveys and qualitative studies classics).
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