Dividing your user base into distinct groups based on shared characteristics, behaviors, or needs. The foundation for targeted research, personalized experiences, and meaningful sample design.
Definition: Dividing your user base into distinct groups based on shared characteristics, behaviors, or needs. The foundation for targeted research, personalized experiences, and meaningful sample design.
Segmentation splits your user base into groups that are meaningfully different from each other. The goal is not just description—it is identifying groups that require different product decisions, research approaches, or communication strategies.
Segmentation directly affects your research design:
Bad segmentation creates groups that are statistically distinct but practically identical in behavior. If your "power users" and "casual users" want the same things from your product, the distinction is not useful.
Good segmentation produces groups where knowing which segment a user belongs to changes what you would build or recommend for them.
Fictional characters created to represent the goals, behaviors, and characteristics of a real group of users. A tool for keeping specific user types in mind throughout product development.
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.
The process of evaluating potential research participants against eligibility criteria before they enter a study. Good screening protects data quality; bad screening wastes everyone's time.
This term is referenced in the following articles:
Transform interview transcripts and observation notes into actionable themes through systematic coding. The difference between an opinion and a finding is whether two people agree.
An interactive sample size calculator for UX research, with the statistical foundations explained — from binomial problem discovery to power analysis.
Standardized measurement instruments provide benchmarks and comparability. But using them effectively requires understanding what each one actually measures, and what it does not.
The research technology (ResTech) landscape has exploded with specialized tools for every phase of the research process. Understanding this ecosystem helps you choose tools that amplify your capabilities without creating dependency or replacing critical thinking.
The most powerful insights rarely come from a single source. They emerge from the strategic partnership between UX research and Data Science, fusing deep contextual understanding with patterns identified at massive scale.
As research practices mature, ad-hoc methods break down. Research Operations (ResearchOps) shifts focus from executing individual studies to building infrastructure that allows researchers to work efficiently and consistently at scale.
Stop paying agencies for every study. How to build, manage, and nurture a proprietary pool of users for faster, cheaper research.
Stop asking 'How much would you pay?' The 3 methods to get honest answers: MaxDiff, Conjoint, and Van Westendorp.
Market research, UX research, CX research, product research, are these different things? At their core, they are all related methods for gathering data to reduce uncertainty. The key is understanding what each is best suited for.
Great research dies in toxic teams. How to build 'Psychological Safety' and a unified insights function.
The quality of your research is directly tied to the quality of your participants. Recruiting is not an administrative task, it is a methodological decision that determines whether your findings will generalize.
Don't wait for the beta. The 3 critical moments to test: Concept (Generative), Prototype (Formative), and Live (Summative).
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.
The structure of your study, who sees what, and in what order, determines what conclusions you can draw. Understanding the trade-offs between study designs is fundamental to research craft.
A researcher's greatest fear is not delivering bad news, it is being ignored. UX research theater undermines credibility by performing research-like activities that lack empirical substance.
Research disciplines, methods, and principles are not isolated concepts, they form a unified system. Understanding this framework is what separates scattered activities from strategic research practice.
Don't just report averages. How to clean data, visualize distributions, and calculate statistical significance.
Research does not happen in a vacuum. It happens in a complex, messy, human ecosystem of competing priorities, overlapping roles, and different ways of thinking. Success depends less on perfecting methods and more on navigating this reality.