How Do Product Attributes and Reviews Moderate the Impact of Recommender Systems Through Purchase Stages? [Dokyun Lee & Kartik Hosanagar]

An interesting study on the impact of recommender systems in e-Commerce. While, on average, views, conversion|views, and final conversion rates varied by 15.3%, 21.6%, and 7.5%, respectively, the numbers strongly depended on the product attributes. The study is based on an A/B test (recommendations vs. no recommendations) with 184,375 users.

We find that the lift on product views is greater for utilitarian products compared with hedonic products as well as for experience products compared with search products. In contrast, the lift on conversion|views rate is greater for hedonic products compared with utilitarian products. Furthermore, the lift on views rate is greater for products with higher average review ratings, which suggests that a recommender acts as a complement to review ratings, whereas the opposite is true for conversion|views, where recommender and review ratings are substitutes. Additionally, a recommender’s awareness lift is greater than its saliency impact.

https://doi.org/10.1287/mnsc.2019.3546

A short summary/review of the paper can be found here https://phys.org/news/2020-05-effects-e-commerce-vary-product-attributes.html. The full paper is available here https://doi.org/10.1287/mnsc.2019.3546.

The study found that using recommenders increased both the volume of consumers’ views of products and consumers’ likelihood of buying a product. A recommender’s positive impact on product views was greater for utilitarian products (e.g., a hammer) than it was for hedonic products (e.g., perfume), and greater for products with characteristics that can only be discerned by use (e.g., wine, movies) than for products for which consumers can easily judge the quality by reading descriptions (e.g., computers, phones).

https://phys.org/news/2020-05-effects-e-commerce-vary-product-attributes.html.