Qualitative user data refers to user data that describes attributes or properties. Examples include session replays, direct customer feedback, user testing – and anything else that involves deep, direct insights into customer sentiment and motivation.
A quick and easy way to distinguish between qualitative user data and quantitative user data is to think descriptions for the former and numbers for the latter. Qualitative data is subjective and can be challenging to analyze at scale, while quantitative user data is objective and easy to analyze.
Qualitative user data adds a whole new dimension to a brand’s visibility into digital customer experience. Collecting it provides useful, direct insights into customer sentiment – and certainly gets key stakeholders to take notice of the data.
As WiderFunnel’s Michael St Laurent says regarding a key tracker of qualitative data, session replays: “session recordings can provide incredibly in-depth insights when used effectively. In fact, they’re often the easiest and most cost-efficient way to get into the minds of your customers.”
Due to the deep, rich nature of qualitative insights, they are typically from a small sample size. It’s therefore important to combine them with quantitative user data to ensure that not only the nature but also the scale of any issues can be established too.
To learn more about qualitative user data – and to see how leading companies harness data science to combine it with quantitative user data, maximizing visibility into digital experiences – download our report on digital experience transformation below now.