ArticleRead (13): User Experience at Google: focus on the user and all else will follow

User Experience at Google: focus on the user and all else will follow. by Au, I., et al. (2008) In CHI 2008 Proceedings Extended Abstracts, ACM Press (2008), pp 3681-3686

Which research approaches should ensure that user experiences are interpreted to reflect underlined norms of online users, and promise a better identification for designers to predict user behaviors in the system design process? The case of Google in this article demonstrates a multi-method of user experience based on its corporate philosophy: “Follow the user and all else will follow”.

On the one hand, Google have traditionally sought to adopt their data-driven approach by applying web analytics of quantitative investigation in reflecting what is happening. On the other hand, built on the qualitative approach, Google interpret contextual factors of why users interact with the system designs via field research, diary studies, face-to-face interview. Such an approach is applied by the Google user experience (UX) team in exploring user behavior of Google Maps for the mobile application. They follow a method called Mediated Data Collection approach, in which participants and mobile technologies are assumed to mediate data collection about use in natural settings. Therefore, methods such as prior research on log analysis, recorded usage, focus group study, or field trial, telephone interviews, lab debriefs are combined to utilize the investigations on user behaviour.

This article stresses the bottom-up company culture as a key for designers and project managers to understand the essence of user experience. Three techniques are employed by: (1) injecting the corporate DNA to educate and train engineers and PMs about user experience (i.e. the ‘Life of a User’ training program and ‘Field Fridays’) (2) scaling to support hundreds of projects by UX team (3) helping focus projects on user needs by UX team or user research knowledge base.

Unlike the traditional desktop software design updated on annual basis, Google UX team practices some agile techniques to respond the rapid web cycles. For examples, solutions include guerilla usability testing, prototyping on the fly, online experimentation or enabling a live instant messaging dialogue between observers and moderator during lab-based testing.

The above three approaches are also combined with a global product perspective of designing for multiple countries. In sum, these 4 combinations of the Google case provide us an alternate analytic framework, and best enlist the methodologies for the studying of online user experience practically and implicitly.

ArticleRead (6): The folksonomy tag cloud: when is it useful?

The folksonomy tag cloud: when is it useful? By James Sinclair and Michael Cardew-Hall ,Journal of Information Science 2008 34: 15-29

With the assumption of folksonomy systems affecting user perceptions and patterns, it is interesting to see what empirically can be found from a user interface point to see how tag cloud impact users in information exploration. Sinclair and Cardew-Hall in this paper clearly conclude their findings in small-scale enterprise context, which supports arguments of Mathes (2004) and Brooks & Montanex (2006), that the usability of tag cloud is a social navigation aid tool when broad, general or vague information exploration is taken up. Increasingly, evidences from empirical survey support the function of tagging for broad categorization. [e.g. Noll and Meinel, 2007]

A proper appreciation of this research with which the need to evaluate Tag Cloud in its usability is asserted in its visual summary design, and its ability to serve for non-specific information discovery. Such results are also given weights to a substantial literature reviews of many pro-and-con characteristics of tag clouds. Here, we try to summarize both ends in usability and sociability analysis in the table below.


A very interesting section of this article is that: only 2 out of 89 participants with high level computer background in their experiment are familiar with the tagging mechanism. This percentage is surprisingly low while comparing to the overview that almost one third of online American users have used tagging mechanisms. Out of most curiosity is that since this study is a research on user patterns and perception, there is a missing data analysis to undertake. While the study has concluded that the cost of a query is reduced in the tag cloud scenario (compared with more typing efforts in search box), should the mean tags tagged per article of each participant need to be considered as one of the factors in the cost analysis? Indeed, this remains a question to explore.