Case amazon: ratings and reviews as part of recommendations

We studied user behavior in a recommender-rich environment, Amazon online store, to see what role the algorithm-based and user-generated recommendations play in finding items of interest. We used applied ethnography, on-location interviewing and observation, to get an accurate picture of user activity. We were especially interested in the role of customer ratings and reviews and what kind of strategies users had developed for such an environment. Our results underline the need to develop recommender systems as a whole. The way the recommendations are shown affects which items get picked, and for improving the interface, it is necessary to study the whole in addition to studying the parts in isolation.