CategoryStatistics

October 12, 2017 — When soliciting and listening to user feedback, you will inevitably run into bias on both sides of the coin: Biases will influence the people providing feedback, and your own biases will influence the way you receive that feedback. Bias is universal, but so too are the methods you can take to avoid it. By simply understanding what each bias is and by breaking down the ways that it appears during the feedback process, you can put measures in place to overcome misleading preconceptions and gather the most impartial feedback possible. In this article, Hunter Jensen will take a closer look at four of the most common types of cognitive biases that pop up when collecting and interpreting UX feedback — and how you can nip these biases in the bud, before they skew your production process. Read more…

April 2, 2012 — Whoever works with analytics on a day-to-to-day basis knows how important it is to have a continuity with the data. Any slip might be fatal: data can disappear, trends misunderstood and jobs lost. Losing data can have long-lasting consequences, as very often it isn’t possible to reprocess the data—so what is lost cannot be recovered. Read more…

January 14, 2008 — The main goal of data visualization is its ability to visualize data, communicating information clearly and effectivelty. It doesn’t mean that data visualization needs to look boring to be functional or extremely sophisticated to look beautiful. To convey ideas effectively, both aesthetic form and functionality need to go hand in hand, providing insights into a rather sparse and complex data set by communicating its key-aspects in a more intuitive way. Yet designers often tend to discard the balance between design and function, creating gorgeous data visualizations which fail to serve its main purpose — communicate information. Read more…