EFFECTS OF PERSONALIZED RECOMMENDATIONS VERSUS AGGREGATE RATINGS ON POST-CONSUMPTION PREFERENCE RESPONSES

Online retailers use product ratings to signal quality and help consumers identify products for purchase. These ratings commonly take the form of either non-personalized, aggregate product ratings (i.e., the average rating a product received from a number of consumers suchas "the average rating is 4.5/5basedon100 reviews"),or personalizedpredicted preference ratings for a product (i.e., recommender-system-generated predictions for a consumer's rating of a product such as "we think you'drate thisproduct4.5/5").Ratings in eitherformat canprovide decisionaidtothe consumer, but the twoformats convey different types of product qualityinformation and operate withdifferent psychologicalmechanisms. Prior researchhas indicatedthat eachrecommendation type cansignificantly affect consumer's post-experience preference ratings, constitutingajudgmentalbias, but has not comparedthe effects of these twocommonproduct-ratingformats. Usingalaboratory experiment, we showthat aggregate ratings andpersonalizedrecommendationscreate similarbiases onpost-experience preference ratings when shownseparately. Showntogether, there is nocumulativeincrease inthe effect. Instead, personalized recommendations tendtodominate. Our findings canhelpretailers determine how touse these different types of product ratings to most effectively serve their customers. Additionally, these results helptoeducate the consumer on how product-rating displays influence their stated preferences