My argument here is simple – despite the common argument that ”everything is tracked”, marketers face a big data fallacy when assessing their ability to predict consumer behavior.
The reason is simple :
”On any given occasion, everything from personal factors such as how well a person has slept the night before, current mood, hunger, and previous choices, to environmental variables such as the weather, the presence of other people, background music, and even ceiling height can influence how a customer responds. Algorithms can use only a handful of variables, which means a lot of weight is inevitably placed on those variables, and often the contextual information that really matters, such as the person’s current physical and emotional condition or the physical environment in which the individual is tweeting, Facebooking, or buying online, isn’t considered.”
Therefore, what is known is simply not enough to accurately predict an individual consumer’s behavior. On average, however, given the limitation of computable variables, marketing algorithms can enhance marketing performance. But data will never make marketing ”perfect” – just simply because there’s not enough of it.
: Dholakia (2015) https://hbr.org/2015/06/the-perils-of-algorithm-based-marketing