If you’re into qualitative research at all, it wouldn’t have taken long before you had someone ask you about the statistical significance of your research and how you could back your findings with such a small sample size, or to find others out there trying to make qualitative research look more scientific by trying to extract hard data from it.
There are three main ways that you can try to make qualitative research look more scientific, being:
- Use a relatively large sample size
- Ensure that your test environment doesn’t change
- Ensure that your test approach doesn’t change (don’t change the script, and stick to it)
Now, there are some times when one or more of these tactics is appropriate, but conversely, in many instances it has been my experience that by breaking these rules, you are able to get much greater insight into the research question(s) you have set yourself.
There are many different kinds of qualitative research study, so in the interests of clarity, let’s pick one just like I’ve been working on this week – a lab based combination of interview & a wee bit of usability which is intended to ensure that my client’s proposition is sound, that it is being well communicated, that the users understand what the service is and how it works, and to weed out any critical usability issues.
In the interest of not making you read an enormous post, I’ve divided this into three parts. So, let’s start with part one – a large sample size. Now… to the best of my knowledge there is no scientific way to determine the correct number of participants in a qualitative research study. Now, I’m no statistician (if you are, please feel free to weigh in here), but it is my understanding that the likelihood of reaching a statistically significant result using the methodology I’ve described above, is pretty much nil. Not that it’s impossible, but you’d have to do a heck of a lot of interviewing.
And here’s one golden rule of qualitative research that always holds true – if the research is going to take too long or be too expensive, it will not happen. You can count on that one.
As a result, sample size for qualitative research is often driven by the time and budget available – and that’s not necessarily a bad thing. In fact, this is one subject upon which Jakob Nielson and I actually quite agree. Jakob says that most of the time elaborate usability testing is a waste of time and that you should test with no more than five users. He has a natty little graph that illustrates why this is so:
As you can see – by the time you’re up to five or six users, you’ve gotten to the bottom of most of the usability issues, and from then on you spend more time repeatedly seeing what you’ve already seen before and uncovering very few new findings. In my experience – this is as true for other aspects of research as it is for usability.
I would add a caveat which is that if you have user groups that are quite divergent in their attitudes, experience, or requirements/goals etc. you will want to ensure that you apply this rule to each of those groups. So, for example, if you have an audience of ‘buyers’ and an audience of ‘sellers’ you’ll want to get no more than five each from each key audience. One final caveat – when I say no more than five, I also say no fewer than three (and, what do you know, so does Jakob). You need at least three to identify what are actually patterns from those things that are just personal quirks – because that’s what you’re looking for here – the patterns.
Is it scientific to use such a small user group? If you want to make it look that way, you can look to Jakob for some algorithms and graphs. In my experience – it doesn’t matter whether it is scientific or not. The richness of the information and insight you receive even from this small sample size makes the return on investment enormous – and the small sample size makes it an activity that almost any project can incorporate into their timeline and budget. At the end of the day – those things are far more important than scientific validity.
Is it worth doing qualitative testing with only a small sample size? Absolutely yes. In fact, in many ways, this is the best way to do this research. Qualitative research is not about numbers, it is about the richness of the information and insight you can get access to by spending time with the people who form your audience (or potential audience), and looking for patterns in their reactions and responses.
In many cases, increasing the size of your sample so that it seems more ‘valid’ is a waste of time and money as the later interviews become more and more a repetition of finding you’ve already identified and confirmed. This time and money could be much better spent improving your product and conducting another round of research.
If it’s numbers you’re after – go do a survey. I say embrace and defend the small sample size of qualitative research.
What say you?
(Coming soon: Part Two – Ever-Evolving Prototypes are Ace)