For a user, speed matters. A quick-loading web page facilitates a positive and pleasant user experience. In this article, I discuss the performance of 129 library websites, and detail a practical plan for addressing common performance issues.
This article looks at how inferred and contextual aspects of a search query can offer new ways of thinking about the search results page. Data mining for user context requires using techniques to understand the intentions behind search queries and the physical/network locations of our users. By applying the residual machine cues inherent to the search act and using semantic query analysis, we can improve user experience to anticipate user needs and introduce personal context. This is anticipatory design in practice. In the article, I define the components of anticipatory design, consider the privacy implications of anticipatory systems, examine how our search interfaces as a primary interaction model lend themselves to anticipatory design, and look at how inferred and contextual cues can be brought into a search prototype to improve the search user experience.
Much about user experience design is concerned with subjective improvements to language and structure, style, tone. The role of the user experience designer connotes a ton about the sorts of improvements at the surface of our websites, at the obvious touchpoints between patron and library. Unfortunately, this approach can neglect deep systemic or technical pain points to which “design” is wrongfully oblivious but which are fundamental to good user experience. Speed is a major example. Website performance is crucial enough that, when it is poor, the potential for even the best designs to convert is diminished. The most “usable” website can have no effect if it fails to load when and in the way users expect it to.
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