Towards a Pattern Language for improving UX work in Software Startups

Choma, Joelma; Sharp, Helen; Barroca, Leonor; De Souza, Cleidson; Machado, Leticia and Zaina, Luciana (2022). Towards a Pattern Language for improving UX work in Software Startups. In: PLoP (Pattern Languages of Programs) Conference 2022, 17-24 Oct 2022, Online, (In Press).



Software startups are endeavors focused on building innovative products by seeking to achieve a high growth rate. However, there are a large number of startups that fail in their venture. Software startup failures are often associated with a high degree of market uncertainty, limited resources, time pressure, or simply a bad product idea. User experience practices can help startups achieve successful and sustainable business creation, promoting genuine interest from users, and opportunities for meaningful feedback. To encourage startup professionals to incorporate UX into their practices as earlier as possible, we present in this paper five patterns entitled: UX work value, Shared UX mindset, UX work driven by user data, Knowledge of real users, and Record of UX work. These patterns are part of a larger set of patterns that have been identified through empirical studies that we have carried out in four software startups. In our pattern mining process, we followed an inductive approach using elements of Constructivist Ground Theory by investigating emerging issues concerning UX work in software startups

Viewing alternatives

Item Actions