When approaching a UX research project, one of the first things to consider is the method. And UX research has many methods. Methods can be categorized as quantitatively focused (e.g., A/B tests) or qualitatively focused (e.g., interviews). Most UX research methods can collect both qualitative and quantitative data. For example, surveys often collect both closed-ended
Your job title doesn’t have to be “researcher” or “statistician” to use data to drive design decisions. You can apply some best practices even when numbers aren’t your best friend. It’s actually easier when you’re a designer to enhance your skills with quantitative data than for statisticians to enhance their analytical skills with design principles.
We often talk of qualitative OR quantitative research. You needn’t think of this as an either-or situation. You can often optimize customer research with a mix of the two. While it might seem unorthodox to mix seemingly different fields, it turns out to be a common practice. Mixing qualitative and quantitative methods is neither new
There is an erroneous perception in the UX community that if your method is qualitative, then numbers somehow cannot or should not be used. These perceptions come from an informal practice that stems back to the beginning of the usability profession and continues through training programs and some UX experts. Unfortunately, this perception is misguided
Imagine a marketing department asking for more money to conduct a direct-mail campaign and their only justification was that marketing is a critical business advantage. Now contrast that with an argument that showed that in a previous direct-mail campaign the response rate of 3% was more than twice the industry average and was achieved from
