Algorithms told me to buy it To what extent do Amazon’s recommendations influence the choice of its customers?

Inspired by the growth of e-retail sector in the 21st century, the aim of this thesis was to explore how effective are Amazon’s recommendations in persuading customers and influencing their purchase choices. The questionnaire survey with Likert scales was performed on Amazon’s users in order to compare the influences of Amazon’s recommendations with other notable influences on purchase choice as well as to measure if the persuasion coping mechanisms affect the likelihood of being influenced by them. Findings indicate that Amazon’s recommendations have higher influence on purchase decisions when compared to the marketing communication, and lesser when compared to word of mouth and price-quality ratio of the product as perceived by costumers. This suggests that despite the trend of algorithmic appreciation among users of online platforms, they still put more trust in online reviews, friends’ advices and their own judgment regarding the value of products than in recommender algorithms on Amazon’s website. However, research also shows that Amazon’s recommendations are more successful in influencing the purchase choice of those who are more likely to elaborate the recommendations that they get from Amazon. Also, those who tend to appreciate the recommendations due to their service of user personalization are also more influenced by them. It can be therefore concluded that since those who critically assess recommendations find that there is a reason to trust them. Amazon’s marketers could therefore work more on campaigning to emphasize the advantages of recommendations and their personalizing aspects in order to rival the other influences on purchase choice.