Towards a Human-Centered E-Commerce Personalization Framework

Belk, Marios; Germanakos, Panagiotis; Andreou, Panayiotis C.; Samaras, George

doi:10.1109/wi-iat.2015.204

Cited by 3 publications

(1 citation statement)

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“…Making users aware of the purposes of data collection (especially those resulting from tracking online activity) has a direct impact on subjectively perceived UX [45]. Moreover, the importance of human cognitive factors (i.e., cognitive styles and working memory capacity), which can influence the perception of the quality of the personalization offered, cannot be overlooked [46]. The incorporation of emotional data based on user comments and opinions in the generation of recommendations on e-commerce platforms is also an interesting direction [47].…”

Section: Conceptmentioning

confidence: 99%

One Size Does Not Fit All: Multivariant User Interface Personalization in E-Commerce

Wasilewski,

Kolaczek

2024

IEEE Access

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One of the most visible manifestations of the changes brought about by the digitization of everyday life is undoubtedly the spread of electronic commerce. It is difficult to think of the digital economy without considering transactions through electronic channels. In turn, the user interface (UI) is the key to ecommerce, as it is usually the first and primary point of contact between business and consumer. A key trend in e-commerce is the personalization of communications, which can improve the user experience, increase customer satisfaction and deliver tangible business benefits. Today, it is technically possible to base this personalization on an analysis of user behavior using artificial intelligence and machine learning techniques. A common form of personalization in e-commerce is the use of product recommendation systems, but the user interface can be tailored much more extensively. The approach described and discussed in this paper is a multivariant user interface that allows the layout to be tailored to the characteristics, attributes, and behaviors of customer groups generated using machine learning techniques. The results of the research carried out make it possible to verify the practicality of the proposed solution and provide an opportunity to identify development directions that take into account the potential of artificial intelligence. The application of the concept described in the paper is broad, covering all aspects of e-commerce design that require compromises when serving a single UI variant, but allow flexibility and customization for different users when serving a multivariant UI.

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Section: Conceptmentioning

confidence: 99%