Recommending branded products from social media

Abstract

E-commerce companies are increasingly encouraging their users to connect to social media venues such as Facebook and Pinterest. The main strategic goal of such social connections is to boost user interaction and adoption on social media. However only a few efforts have been focused so far on leveraging users' social profiles to personalize the e-commerce experience and to recommend products of interest. In this paper, we start exploring this topic by investigating if a user's social media profile can be used to predict and recommend what type of products and what brands the social user is more likely to buy. More specifically, we study the correlation between the brands liked by the user on social media sites and those purchased on an e-commerce site. We then leverage these correlations in a brand prediction system, showing that social media can be effectively used to recommend branded products when user-user collaborative filtering techniques are used.