E-Commerce Customers’ Preference Implicit Identification

Knowledge of users’ preferences are of high value for every e-commerce website. It can be used to improve customers’ loyalty by presenting personalized products’ recommendations. A user’s interest in a particular product can be estimated by observing his or her behaviors. Implicit methods are less accurate than the explicit ones, but implicit observation is done without interruption of having to give ratings for viewed items. This article presents results of e-commerce customers’ preference identification study. During the study the author’s extension for FireFox browser was used to collect participants’ behavior and preference data. Based on them over thirty implicit indicators were calculated. As a final result the decision tree model for prediction of e-customer products preference was build.