Research methods quiz

The research methods entries in the glossary, in brief. Open any one for the interactive demo behind it.

Heuristic evaluation

A quick expert review that checks an interface against a short set of usability rules - you can see this in action right here.

Five-second test

Show a design for five seconds, then ask what you remember. What sticks is what the layout really highlights - and what it quietly obscures. You can try this test right here on the page.

First-click testing

First-click testing asks one simple question: where do users go first to complete a task? That first click matters more than any other - get it right and the task usually follows; get it wrong and it rarely recovers.

Usability testing

Watch real users attempt real tasks with your design to spot where it breaks down. Focus on what they actually do - not just what they say - and note their expectations, interpretation, confidence, and perceived effort. Give them a task, observe closely, and ask questions to understand why.

Leading questions

A question worded so it nudges you toward a particular answer - through a loaded word, a built-in assumption, or a scale that only points one way. It measures the wording, not the truth.

Survivorship bias

Survivorship bias is the error of focusing only on what made it through, while ignoring what didn’t - and the lessons those failures hold. In UX, it’s the trap of studying only the users who stayed: your analytics, reviews and surveys are full of survivors, and silent about everyone who hit a wall and left.

Sample size and statistical significance

Sample size is how many people (or sessions) a finding rests on; statistical significance assesses how surprising your measured difference would be if there were really no effect, under a specified model and assumptions. It does not prove an effect is real, important or repeatable. Small samples swing wildly by chance, so a difference can look dramatic and still mean little - which is why significance goes hand in hand with sample size and effect size.

False consensus effect

The false consensus effect is our tendency to overestimate how many other people think, feel and behave like we do. We treat our own preferences as typical, so designers and teams quietly assume users share their tastes, tech-savvy and priorities - and build for themselves while believing they're building for everyone.

Empathy map

An empathy map is a simple four-quadrant canvas - says, thinks, does, feels - for organising what you've learned about a user into one shared picture. It's a synthesis tool: you take scattered research observations and sort them into those quadrants, so a team builds a common, evidence-based sense of the person rather than each member imagining a different one.

Tree testing

Tree testing checks whether users can find things in your site’s structure, stripped of all visual design. You give them a text-only outline of the navigation and a task - 'where would you go to do X?' - and watch which path they take. It isolates one question: is the information architecture itself findable, or is good design papering over a confusing structure?

Acquiescence bias

Acquiescence bias is the tendency to agree with statements regardless of content - to say yes, agree, or pick the positive option to appear agreeable, avoid effort, or please the researcher. When every question is phrased to make agreeing sound positive, this bias quietly inflates your results, measuring politeness instead of true opinion.

Surveys and questionnaires

Surveys and questionnaires collect structured answers from many people at once - cheap, scalable, quantifiable. Their weakness is that the data is only ever as good as the questions: a leading, loaded, double-barrelled or vague question quietly manufactures the answer, so a badly-written survey produces confident numbers that mean nothing.

Affinity mapping

Affinity mapping helps you make sense of qualitative research by grouping individual observations - each on its own sticky note - into clusters of related ideas, then naming the themes that emerge. Instead of starting with pre-set categories, you let the structure emerge from the data itself, turning a wall of scattered notes into a few clear patterns you can act on.

Customer journey mapping

A customer journey map charts the whole relationship a person has with a brand over time and across channels - from first awareness through consideration, purchase, onboarding, support and (you hope) loyalty - plotting their actions, thoughts and emotions at each stage. It zooms out from a single task to the end-to-end experience, exposing the emotional highs and lows the rest of the organisation rarely sees joined up.

Synthetic users

Synthetic users are model-generated responses that simulate real research participants. They can help explore ideas, draft questions or test materials, but they’re not evidence about real users and must not replace recruitment, observation or interviews.

Hindsight bias

Hindsight bias is that 'I knew it all along' feeling: once you know the outcome, it seems obvious and predictable - even if you had no idea beforehand. It quietly reshapes your memory of what you expected, which can be risky in research, because it makes teams think they didn’t need the study they just ran.

Observer-expectancy effect

The observer-expectancy effect occurs when a researcher’s expectations subtly shape a study’s outcome - through how they phrase questions, respond to answers, or interpret behaviour. You might unconsciously steer participants toward agreement or read ambiguous actions in a way that supports your desired result.

Social desirability bias

Social desirability bias is the tendency to answer in ways that make us look good rather than ways that are true - over-reporting the admirable, under-reporting the embarrassing. In research it means self-report drifts toward the flattering: people say they read the terms, exercise more, and skip the ads more than they really do, especially when someone's watching.

Think-aloud protocol

Think-aloud is a usability-testing method where participants verbalise their thoughts as they complete a task - what they’re looking for, expecting, or unsure about. It turns silent actions into spoken commentary, revealing not just where someone struggles but why, exposing hesitation and flawed mental models that a screen recording alone can’t capture.

Card sorting

Card sorting is a research method where users group labelled cards into categories that feel natural to them. It reveals how they mentally organise information - the raw material for an information architecture built on their logic, not yours.

Thematic analysis

Thematic analysis is a method for uncovering patterns of meaning in qualitative data. You read through the material closely, assign short descriptive codes to meaningful sections, then group those codes into broader themes. It’s the rigorous, auditable cousin of affinity mapping: a repeatable route from raw transcripts to defensible insights.

User interviews

A user interview is a one-to-one conversation designed to uncover someone’s needs, context, and experience. Its value comes from asking about actual past behaviour - you get evidence, not hypotheticals, leading questions, or yes/no questions, which yield polite fiction. The skill lies in getting people to reveal what they actually did, not what they might do or what you’d like to hear.

Eye tracking

Eye tracking records where gaze lands on a screen and how long, showing scan paths and heatmaps of fixations. It reveals what got looked at, what was skipped, and in what order - but gaze isn’t the same as attention, comprehension or intent, so results need interpreting alongside task behaviour and participant feedback. You can see this in action on this page.

Task analysis

Task analysis breaks down a goal into the actual steps and sub-steps users take to achieve it - the decisions, actions, and information needed at each point. It replaces a vague sense of 'they just book a flight' with the real, often surprising sequence, revealing where effort, confusion, and errors actually occur so you design for the task as it is, not as you imagine it.

Triangulation

Triangulation means checking a finding by comparing it across multiple sources, methods, or perspectives, and trusting it most when they align. Every method has its own blind spots and biases - analytics can’t explain motivation, interviews capture what people say not what they do - so a conclusion that holds up across several methods is far more reliable than one based on a single, flawed viewpoint.

Recall bias

Recall bias is the difference between what people remember doing and what they actually did. Human memory isn’t a recording; it’s a reconstruction - lossy, smoothed, and skewed toward the vivid, recent, and emotional. So any research that asks people to remember past behaviour collects an edited highlights reel, not an accurate log.

Research bias

Research bias is any consistent influence that skews a study's results away from the truth - not random error that averages out, but a steady lean introduced by how you recruit, ask, observe or interpret. It’s not a single mistake but a whole family of them, lurking at every stage of research, and the first defence is simply knowing where each kind tends to strike.

Synthetic personas

Synthetic personas are AI-generated stand-ins for users, built from a model rather than real research. They can help draft or pressure-test ideas, but they reflect the model’s assumptions and biases - useful for exploration, not a substitute for talking to real people.

Contextual inquiry

Contextual inquiry means interviewing people as they work, in their own environment, doing real tasks. You observe what they actually do and ask questions while it’s happening. You become the apprentice, they the master - so instead of a tidy account from a desk, you get the messy truth: the workarounds, the interruptions, the context that a meeting-room interview would never reveal.

A/B testing

A/B testing shows two versions to two random groups and compares a metric - clicks, sign-ups, sales - to estimate which performs better. It measures the effect of those particular variants on that particular metric, for the people and period you sampled. It won't tell you about comprehension, accessibility, long-term or novelty effects, or unmeasured harms - and done hastily it manufactures false winners from noise.

Diary studies

A diary study asks participants to log their experiences themselves, in the moment, over days or weeks - capturing what happened, when and how it felt, as life actually unfolds. It trades the one-shot snapshot of an interview for a record over time, which is the only way to study habits, long arcs and infrequent events without relying on faulty memory.

Guerrilla testing

Guerrilla testing is quick, cheap, informal usability testing - grabbing a few willing strangers (in a café, a hallway, a high street) and watching them try your design for ten minutes each. It trades the rigour and control of a formal study for speed and almost no cost, betting that a handful of fresh users will still expose the biggest, most obvious problems fast. You can try this approach right here on this page.

Expert review

An expert review is a UX specialist evaluating a design against their knowledge and established principles to predict where users will struggle - no participants required. It’s fast and cheap and catches a lot of obvious problems, but it’s a prediction of usability, not a measurement: an expert flags what’s likely to go wrong, where user testing shows what actually does.

Field studies

A field study is research conducted in the user's real environment rather than a lab - observing how a product is actually used amid the noise, interruptions, other people and physical constraints of real life. Where a lab isolates a user with a task, a field study keeps the whole messy context intact, because that context is often what really shapes whether something works.

Usability testing vs heuristic evaluation

Usability testing watches real users tackle tasks; heuristic evaluation is expert review against established usability principles.

Five-second test vs first-click test

A five-second test checks first impression, comprehension, or recall; a first-click test measures where users begin when trying to complete a task. You can see and try these tests in action on this page.

Nielsen's 10 usability heuristics

Nielsen's 10 usability heuristics are ten practical guidelines for spotting interface problems - keep users informed, speak their language, prevent errors, and so on. They form the basis of a heuristic evaluation and remain the most widely used standard in usability.