![]() The team posts all of the transcribed data to a large whiteboard, which enables the Post-Its to be manipulated.The team commits all of the qualitative data points to Post-It notes, of which there can be dozens.It’s a best practice for affinity diagramming to be done in complete silence – that way, equal weight is given to both the louder and the quieter voices on a design team. A researcher would have a difficult time making a general design recommendation based on an observation that “One participant attempted to filter her search results when asked to complete the task of using the search function to find more information about a local business.” But if that observation was compared against similar findings in other contextual inquiry observations, and the findings were aggregated and grouped thematically during an affinity diagramming session, the decision to add additional search functionality would be substantiated. Say a researcher is testing a customizable geolocation app that allows users to search for nearby mobile businesses. The quote from Extractable about what they term “fuzzy data” reveals a crucial benefit of affinity diagramming: it allows researchers and designers to take indistinct information and make it concrete and actionable. The term ‘fuzzy data’ can have multiple meanings to different people and industries, but in the context of UX Design, it is all the known information related to a project that is nebulous and not yet actionable.” “At the start of the design process, it can be difficult for designers to conceive design direction from fuzzy data and requirements. ![]() During the process of analyzing a given task, researchers might guide the interaction back to important user actions that fall within the scope of the product the team is creating or features of the existing product they are trying to improve.Ĭontextual inquiry gives researchers what Extractable calls “fuzzy data”: A user researcher watches users complete a task, asking clarifying questions to probe deeper into their thought process, recording observations about behavior. Finding Value in Fuzzy DataĬontextual inquiry can take the form of an interview conducted in the user’s natural environment (workspace, home, etc.). The primary focus, as in all aspects of user UX design, should be on the end users – the people who the implications of the data will ultimately affect. In order to create human-centered designs that foster meaningful user experiences, the process of classifying data needs to take place in such a way that the focus remains on understanding its implications and applying it appropriately. Organizing user research data is essential. However, once investigation begins – once the hypothesis begins to be tested – evidence validates or invalidates it, allowing the supposition to evolve into something more sensitive to the personal stories of the user base. The method creates a relationship between data and its implications for UX.įorming a hypothesis about how to alleviate user pain points is a logical starting point, but a hypothesis runs the risk of removing the focus of the design process from the end user it’s based on an assumption rather than an intimate understanding of user needs, desires, and behaviors.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |