A Core Method of asking at scale using standardized questions. Enables data collection from larger samples but sacrifices the depth of interviews for breadth and standardization.
Definition: A Core Method of asking at scale using standardized questions. Enables data collection from larger samples but sacrifices the depth of interviews for breadth and standardization.
A Survey is a Core Method built entirely on the Asking Building Block, designed to gather data at scale using standardized or specifically formulated questions.
Surveys trade depth for breadth. Where an interview might explore one person's experience in detail, a survey captures specific data points from many people. This makes surveys essential for:
The limitation is that surveys cannot adapt in the moment. You cannot follow up on an unexpected answer the way you can in an interview. The questions must anticipate what matters, which is why qualitative research often precedes survey design.
The word "survey" creates confusion across disciplines. In market research, Cost Per Interview (CPI) often refers to survey responses, not live conversations. In computer science or academia, "survey" might mean a literature review—nothing empirical at all.
In stakeholder conversations, be precise. A survey in UX research is a structured instrument for collecting self-reported data from a sample of users. It is not necessarily representative or statistically valid—that depends on your sampling method and sample size.
The three foundational research activities—Asking, Observing, and Testing—that combine to form all UX research methods. A framework for understanding that complex methods are built from simple components.
The three primary UX research methods built from Building Blocks: the UX Test, the User Interview, and the Survey. Each represents a different combination of asking, observing, and testing activities.
Research focused on numerical measurement with the goal of generalizing findings from a sample to a broader population. Answers 'how much,' 'how many,' and 'how often.'
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.
This term is referenced in the following articles:
Four pillars that protect your data: verified participants, respectful experience, study review before launch, and continuous quality monitoring.
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.
You will always introduce bias into your research, that is unavoidable. The goal is not elimination but management. Understanding the difference between systematic and unsystematic error is what makes findings trustworthy.
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.
Good research is not a series of disconnected activities, it is a cohesive process that transforms business questions into actionable insights. This is the map for that journey.
Rather than a sharp divide, qualitative and quantitative research exist on a continuum. The most powerful insights come from combining both, understanding why something happens and measuring how often.
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.
User Experience is not a single thing, it is a complex result of interconnected components organized in a hierarchy. Understanding this structure is essential for translating stakeholder desires into actionable research.
No matter how complex a method sounds, it can be broken down into three simple activities. Understanding this framework transforms how you plan and execute research.
There are two fundamentally different ways we gather data. Research we design and control, and data users generate without our prompting. Most teams over-rely on one and misunderstand the other.