Representativeness Heuristic

Representativeness Heuristic

Representativeness Heuristic is a cognitive bias explored by Kahneman and Tversky in their article Subjective Probability: A Judgment of Representativeness (1972). It demonstrates that people tend to “force” statistical arrangements to match with their beliefs when making judgements about the probability of an event under uncertainty. Representativeness Heuristic also explains the way in which we place objects in to a certain category simply based on a limited number of similarities: even if something doesn’t fit exactly into a known category, we will judge it to be the same if we can draw enough parallels. This shortcut leads us to judge the probability of something or the category it fits into in a biased manner by comparing it to a similar thing rather than using objective statistics or knowledge.

For example, if an individual sees three blackbirds fly past in succession, they will expect the fourth bird to go past to be black too, and even assume that maybe there are only black birds in that particular area. They are making biased assumptions based on a mental shortcut that relies on generalisation rather than statistical probability. Mathematically speaking, without knowing any statistics related to the ornithological distribution in the area, the fourth bird to pass is just as likely to be any other colour as it is to be black again.

You can use this principle in web marketing in several ways. In order to make your product appear as attractive as possible to your customers, you can highlight the similarities of this product to another that you know your customer likes (perhaps something they’ve previously bought). You can also make use of this principle to ensure that the products and services you are offering match up with their expectations based on representative models.

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