Abstract
Although purchasing online has become increasingly popular, finding suitable products in Web shop environments still requires significant effort from users. This study proposes a method for re-ranking products on a Web shop’s search engine to better match individual user preferences using semantic descriptions in user profiles. Through a live experiment, we demonstrate that the proposed re-ranking method incorporating segment-based customer preferences increases the commercial efficiency of Web shop’s search engine, increases the average rank of product clicks and the add-to-basket rate, while decreases the click-through rate. Interestingly and contrary to what holds for Web search, the empirical evidence collected in this study indicates that the average rank of clicks used to measure the quality of Web search may not be a reliable indicator for the product search result ranking quality for product search engines in Web shop environments.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
