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ECUXH: A Set of User eXperience Heuristics for e-Commerce

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Social Computing and Social Media: Experience Design and Social Network Analysis (HCII 2021)

Abstract

Currently, e-Commerce users have different objectives and contexts of use, so it is essential to consider each of these cases when designing appropriate websites, so that the User eXperience (UX) would be as pleasant as possible. UX extends the usability concept. UX refers to user’s perceptions and responses that result from the use and/or anticipated use of a system, product, or service. Heuristic evaluation is an inspection method that allows evaluating the usability of interfaces. A set of heuristics can be general, like Nielsen’s heuristics, or specific to the area of application of the interactive software system under evaluation. Due to the specific characteristics of e-Commerce websites, general usability heuristics are not suitable, especially when evaluating UX aspects beyond usability. Specific sets of heuristics have been proposed to evaluate e-Commerce websites, but they mainly focus on usability. This article presents a set of heuristics that address not only usability, but also other UX factors. The new set of heuristics was developed, validated, and refined in three iterations, based on the methodology established by Quiñones et al. (2018). This methodology establishes 8 steps that allow obtaining a set of heuristics for a specific domain. The results obtained in the experimental validation indicate that the ECUXH set is a useful and more efficient tool than generic heuristics, when evaluating e-Commerce websites. As future work, we pretend to develop a set of retail-oriented Customer eXperince (CX) heuristics, based on ECUXH.

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Acknowledgements

The authors would like to thank the School of Informatics Engineering of the Pontificia Universidad Católica de Valparaíso (PUCV), Chile, and the Agencia Nacional de Investigación y Desarrollo (ANID).

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Bascur, C., Rusu, C., Quiñones, D. (2021). ECUXH: A Set of User eXperience Heuristics for e-Commerce. In: Meiselwitz, G. (eds) Social Computing and Social Media: Experience Design and Social Network Analysis . HCII 2021. Lecture Notes in Computer Science(), vol 12774. Springer, Cham. https://doi.org/10.1007/978-3-030-77626-8_27

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  • DOI: https://doi.org/10.1007/978-3-030-77626-8_27

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