Improving Task Performance in User Experience Writing : a validation of two methods in digital and in-person user contexts

University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

Abstract: User Experience (UX) Writing is part of the product’s overall user experience design. It can be a part of a product content strategy as much as the visual design. The base for any UX centered profession is the understanding of usability — the practice of making products or services easy to use for the intended target group. The difference between the UX designer and UX writer is that the writer contributes with an in-depth understanding that textual content contributes to an overall better user experience along with the product brand. This study includes two UX writing usability evaluation methods for a defined functional service application. By performing the UX writing methods through an online form as well as in an in-person user interview, the validity of transforming an established method into an online tool was investigated. The liabilities of both contexts were evaluated and future developments are suggested. To accomplish this, a literature review was conducted and an online tool was developed. This was used to gather data from 20 users, 10 in the online context and 10 in the in-person context. The datasets were then compared for validation, which in turn served as a foundation for further discussing the possibilities of using an online tool in this situation. The conclusion is multifaceted. The in-person user tests require resources in terms of time for the UX writer, finances in terms of compensation for the users and result in a smaller data set. Digital user tests also require time and resources, but can generate a much larger data set, seeing as it provides a data set of the same quality level as the in-person user tests. Considering the advantages of an online tool, it can provide a valid replacement for in-person user tests, if one considers that the assets outweigh the minor liabilities. However, the potential of a future collaborative dataset and all the further developments suggested in this paper are what is truly worthwhile investigating further.

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