The point in qualitative research where you are no longer hearing new information or discovering new insights from participants. The signal that you have likely uncovered the most important themes.
Definition: The point in qualitative research where you are no longer hearing new information or discovering new insights from participants. The signal that you have likely uncovered the most important themes.
Saturation is the point in qualitative research where you are no longer hearing new information or discovering new insights from your participants.
When the eighth user in a row points out the same confusing button, or the tenth interviewee describes the same unmet need, you have likely reached saturation for that specific issue within that target group.
Saturation is the practical, data-driven signal that tells you it is time to stop recruiting for that segment. Continuing beyond saturation produces diminishing returns—you collect more data but learn nothing new.
Saturation relates directly to sample homogeneity. When you test with a single, well-defined user segment:
With heterogeneous samples (mixed user types), patterns are harder to discern and saturation takes longer—or may never be reached for any specific issue.
Saturation applies to qualitative insight, not quantitative measurement. Reaching saturation means you have identified the themes; it does not mean you can generalize to the population or calculate percentages. That requires larger samples and different methods.
Research focused on understanding the 'what' and 'why' through rich stories, observations, and context. Seeks depth of understanding rather than statistical measurement.
A Core Method of structured asking designed for deep exploration of user needs, behaviors, and motivations. Distinguished from casual conversation by its defined goals, protocol, and systematic approach.
The number of participants in a research study. Appropriate sample size depends on research goals, method type (qualitative vs. quantitative), the precision required, and the number of distinct user segments being studied.
This term is referenced in the following articles:
An interactive sample size calculator for UX research, with the statistical foundations explained — from binomial problem discovery to power analysis.
The goal of good research is to define and recruit homogeneous segments. Understanding variables, demographic, behavioral, attitudinal, psychographic, is how you get there.
The idea that you only need five users is one of the most famous, and most misunderstood, heuristics in UX research. Here is what the numbers actually mean and when they apply.