If you’ve read some of my previous columns on UXmatters, you could be forgiven for thinking my entire working life is spent largely surrounded in a sea of quantitative data. This is, rather surprisingly even to me, not nearly close to the truth. Looking back over recent months, by far the most common form of research I’ve carried out is that stalwart of qualitative studies—the interview.
A simple, semi-structured, one-on-one interview can provide a very rich source of insights. Interviews work very well for gaining insights from both internal and external stakeholders, as well as from actual users of a system under consideration. Though, in this column, I’ll focus on stakeholder interviews rather than user interviews. (And I’ll come back to that word, insights, a little later on, because it’s important.) Read More
Understanding the people who will ultimately engage with a product or service provides the foundation for user experience design. Modeling those people and segmenting our models into meaningful groups lets us explore different clusters of needs, then address our solutions to meeting the needs of people belonging to specific clusters.
Audience segmentation models come in many shapes and sizes. So far, the practice of UX design has focused primarily on the persona as the model of choice. This article explores alternative ways of segmenting audiences and the design research we need to derive each type of model. Read More
One of the key objectives of user research is to identify themes or threads that are common across participants. These patterns help us to turn our data into insights about the underlying forces at work, influencing user behavior.
Patterns demonstrate a recurring theme, with data or objects appearing in a predictable manner. Seeing a visual representation of the data is usually enough for us to recognize a pattern. However, it is much harder to see patterns in raw data, so identifying patterns can be a daunting task when we face large volumes of research data. Patterns stand out above the typical noise we’re used to seeing in nature or in raw data. Read More