Improving E-Commerce User Experience with Data-Driven Personalized Persuasion & Social Network Analysis
نویسنده
چکیده
Simply selling products online can no longer guarantee profits for e-businesses especially for new comers to the e-commerce industry, as the competition among companies is more intense. In order to keep existing customers and make new ones, e-businesses have to provide products and services that feel personal to their clients. This research proposes a framework for improving a user’s e-commerce experience by using personalized persuasion techniques and social network analysis. The proposed framework proposes the use of persuasion profiles in implementing a customer segmentation strategy. The framework also proposes the analysis of social networks to improve customers’ shopping experience.
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تاریخ انتشار 2016