Quantitive & Qualitative data
So you want to conduct some research, but what’s the difference between quantitative and qualitative research?
The simplest explanation would be that quantitive research is the gathering of numerical data which is relatively easy to convert into graphs or tables, with qualitative research being a collection.
Examples of quantitive data could be analytic data such as the time spent on a page, funnels analysis, conversion data, heat mapping and A/B analysis, this kind of analysis allows you to detect issues or confirm hypothesis or changes in your design.
Be careful with quantitive data collection though as sometimes this data can be skewed, for example, if you asked participants to complete a yes / no survey with which they do not see any value or was lengthy then they may answer the questions quickly and incorrectly.
Qualitative data is on more of a personal basis such as user testing within a lab environment, diary studies, focus groups or 1:1 interviews. This type of analysis gives you a deeper insight into problems with your design and allows for opinions to fed back. This data is harder than quantitive data to turn into graphs and charts.
Some methodologies that give you both quantitive and qualitative data, but more of that another time.
So which one do I use I hear you say? I utilise both quantitive and qualitative methods, starting with quantitive data to identify the problem, then I use a qualitative methodology to dig deeper into that problem. Alternatively, if I understand the problem, I would go straight into design then run this change through user testing to get feedback.
Finally, this change would be put into the live environment to get quantitive data back usually in the form of A/B testing allowing for a gradual release so as to get data back before pushing live to everyone.