When a consumer visits an e-commerce website nowadays, it is nearly impossible to ignore reccomendations that have been provided by the site. These reccomendations suggest other items that the consumer may be interested in, based on shopping history and stored data. Normally populated by a sophisticated alogarythm, these recommendations intend to predict what the consumer may be interested in purchasing, and entice the consumer to purchase these products from their website.
However, since product reccomendations are becoming more widespread, consumers are noticing and reacting when these recommendations don’t meet their interests or needs. According to the Choicestream “2009 Personalization Survey,” 59% of consumers reported that they received poor personal recommendations in 2009.
Consumers that were surveyed reported high satisfaction with the reccomendations from entertainment sites such as iTunes and Netflix, and were least satisfied from reccomendations from e-commerce sites in the toy, office supply and shoe companies.
Source: eMarketer, February 4, 2009
