And the key point: this article is about quant, not qual. In contrast, quant does focus on collecting UX metrics, so we need to ensure that these numbers are correct. Qual aims at insights, not numbers, so statistical significance doesn’t come into play. Since this is a common confusion, let’s clarify: there are two kinds of studies, qualitative and quantitative. Read on if you do want to know where that number comes from, when to use a different number, and why you may have seen different recommendations. If you don’t really care about the reasoning behind that number, you can stop reading here. In most cases, we recommend 40 participants for quantitative studies. We want to strike the perfect balance - collecting enough data points to be confident in our results, but not so many that we’re wasting precious research funding. If you test with too many, you’re essentially throwing your money away. If you test with too few, your results may not be statistically reliable. Where do these recommendations come from and how many participants do you really need? This is an important question. (In fact, we’ve recommended different numbers over the years.) Apparently contradictory recommendations (ranging from 20 to 30 to 40 or more) often confuse new quantitative UX researchers. The exact number of participants required for quantitative usability testing can vary.