Building a case for qualitative research

When it comes to qualitative research, sometimes UX Researchers have to defend its usefulness and validity as a research approach. That happens because others think we can’t make valid conclusions with qual research, either because the sample was too small or because user sessions aren’t performed equally. Some of my mentees ask me how they can advocate for qual research inside their companies to gather feedback about their users. I tell them about the differences between quant and qual and how they should use them, but I also try to give them some examples that apply to their companies so that they can take them and use them themselves.

About qualitative research

When the goal is to gather deep contextual insights about user behaviours and attitudes, the best approach is to use a qualitative research methodology. We can also use Qualitative research to uncover hidden truths about users — the unknown unknowns.

Qualitative research methods are loosely structured, and user samples are usually small. They typically involve direct contact with users.

These methods include moderated usability tests, user interviews, diary studies, etc. Data obtained from such methods is non-numerical and can take the form of quotes, observations or narratives. Analysing this type of data is time-consuming and complex, and we need to be careful not to let our opinions influence the findings.

About quantitative research

When the goal is to test theories and hypotheses about users’ behaviours and attitudes, using a quantitative methodology is best. We can also use Quantitative research to monitor the performance of a service and product.

Quantitative methods are highly structured, and user samples are large to obtain statistical significance. They usually don’t involve any direct contact with users.

These methods include surveys, A/B tests, tree testing, web analytics, etc. Data obtained from these methods are numerical and are subject to statistical analysis to draw more generalised conclusions. Analysing this type of data is objective but requires knowledge about statistics.

Qualitative vs Quantitative research

Both approaches have their benefits and downsides. We can use them throughout all phases of product development, separate or by combining them (Mixed Methods).

The ideal scenario is to have data from both types of research. They highly complement each other.

For example, if from your Analytics you identify a significant percentage of users is dropping out on the 2nd step of your checkout funnel, you know you have a problem there. You don’t know what the problem is. For that, you need to conduct some user interviews or usability tests.

Another example, starting with qualitative data now, is from user interviews, you identify motivations A, B and C for users to use your product. But you don’t know which one is more important. If you run a survey to quantify them, you can say that motivation C is more important than A and B.

Usually, you don’t have the time or budget to have both, so you must set the goal of your research and the research questions to choose the method you think you can take the most out of it.

Advocating for qualitative research

So now that I’ve gone through both approaches, it’s clear that qual research brings many benefits and is an essential tool for every researcher. If you are only looking at quant data, you might be missing out on crucial information about your users and not looking at the full potential of your products and/or services.

If it’s hard for you to do qual research because your management doesn’t believe in its results, show them the gaps in the current knowledge and explain why qualitative research is the right way to fill some of those gaps. If after trying time after time convincing them to do qual research and still they don’t see the value, maybe consider if that’s a good company for you to grow as a user researcher.

This article was originally published on the Service Design College network.