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Product recommendations are already everywhere and are an almost fundamental part of the digital world. If we look at a book, a drop-down option will show what those who are also interested in it have read; if we look for clothes, we will see other pieces that match the fashion; or if we use design tools, we will start to receive options and additions to improve our work. Beyond the subject in question, recommendations are a key element in e-commerce. 

A group of specialists at the University of Pennsylvania investigated in terms of the subconscious how these recommendations work and how consumers process the data. What is most relevant is not what is recommended, but how and why the recommendation is made. Users take into account the context in which they receive the possibility of purchasing products.

The study sampled two different recommendation systems: one based on previous purchases and the other based on other consumers’ collaborative purchases. Users’ responses to the products were different, closely connected to their personalities and linked to the decision-making patterns they make in their lives. Consumers who make decisions for themselves and are used to being problem solvers preferred recommendations based on previous purchases. However, those more comfortable in terms of finding their needs opted for the process of having others choose products in advance. 

Product type also influences the effectiveness of the recommendation, in addition to personality. Consumers who want to feel that they make the decision need to recognize that the offer is related to their preferences, such as movies, travel or restaurants. An example of this type of user is those who correctly receive the percentage Netflix uses to recommend titles based on what was already watched or added to the playlist. The second group of consumers does not engage in that search, but rather expects the percentage shown to reflect how many purchases the products that were recommended to them have. 

Beyond looking for a definitive system to analyze and deliver recommendations, the reception of recommendations depends on the personality characteristics of consumers.


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