# User Research

> Systematic study of users' goals, behaviors, and context — the evidence that turns design decisions from opinion into judgment.

- Category: Process & Methods
- Canonical: https://www.themasterly.com/glossary/user-research

User research is the systematic study of what people are trying to do, how they do it now, and what stops them. It is the evidence that turns design from a contest of opinions into a set of judgments somebody can defend.

It divides into two jobs that get confused. Generative research asks what problem is worth solving and runs before anything exists. Evaluative research asks whether a particular solution works and runs against something built. Teams that do only the second end up with usable products that nobody needed.

## Choosing a method

| Method | Answers | Sample | Best before or after building |
|---|---|---|---|
| **Interviews** | What are people trying to do, and why | 6–8 per group | Before |
| **Contextual observation** | What they actually do, including workarounds | 4–6 | Before |
| **[Usability testing](https://www.themasterly.com/glossary/usability-testing)** | Where a design fails and why | 5 per group | After a design exists |
| **Surveys** | How common something is, among people who answer | Hundreds | Either, with care |
| **Product analytics** | What happened, everywhere, without explanation | Everyone | After |
| **[A/B testing](https://www.themasterly.com/glossary/ab-testing)** | Which version performs better | Thousands | After |

The pairing that does the most work is analytics plus interviews. One tells you where people stop, with complete coverage. The other tells you why, from a handful. Either alone produces confident work aimed at the wrong problem.

## Asking questions that return information

Most interview failure is in the questions, and three habits fix the majority of it.

**Ask about the past, not the future.** "How did you handle the last month-end close?" returns an account of something that happened. "Would you use a feature that automated it?" returns a prediction, and people are unreliable predictors of their own behaviour.

**Ask for the specific instance.** "Tell me about the last time this went wrong" produces detail. "What usually happens" produces a tidied-up summary with the interesting parts removed.

**Never describe your solution first.** Once an interviewee knows what you are hoping to hear, they will help you hear it. Save the concept for the end, if at all.

The most useful follow-up in any interview is silence, and the second most useful is asking what they did next.

## The B2B access problem

The methods are cheap and the participants are not, which is where most B2B research programmes quietly stop.

Enterprise users cannot be recruited from a panel or intercepted anywhere, and the people who are easiest to reach are the friendliest customers, which biases everything toward accounts that are already succeeding. Three routes work in practice.

**Ask customer success for a behaviour, not a favour.** "Three accounts that added a second user last month" produces a useful sample. "Anyone willing to talk" produces your fan club.

**Prioritise churned and downgraded accounts.** They hold the most information and are the hardest to reach, which is exactly why most teams learn nothing from them.

**Use internal proxies carefully.** Support agents and implementation consultants share the workflow without sharing the product knowledge, and they are available. They are a proxy, and the findings should say so.

## Making it change something

Research fails at the point of delivery more often than at the point of collection.

**Separate observation from interpretation.** "Four of six could not find the export" is an observation and is hard to argue with. "We need a bigger export button" is a proposal, and somebody may have a better one. Mixing them makes the observation contestable, which is the one thing it should not be.

**Show the recording.** Thirty seconds of a customer struggling ends a debate that a written summary prolongs.

**Rank by cost, not by irritation.** The finding that annoyed the researcher most is not reliably the one costing the most money.

**Write down what you decided not to act on.** Otherwise the same finding is rediscovered every round as though it were new.

## Building it into a normal week

Research fails as a project and works as a habit. Teams that sustain it tend to share a few unremarkable arrangements.

**A standing slot.** Two or three sessions in the calendar every fortnight, with participants recruited a round ahead. A rolling schedule removes the decision to do research at all, which is the decision that gets skipped under deadline.

**Everyone watches occasionally.** An engineer who has watched one customer struggle argues differently in planning than one who has read a summary. Rotating attendance costs an hour and changes more minds than any report.

**A findable record.** Findings scattered across documents get rediscovered as new. A single place, searchable, with the date and the evidence attached, means the second time somebody asks a question, the answer might already exist.

**A small standing question.** Something the team always asks, such as what the person was doing immediately before they opened the product. Consistency across sessions turns individual anecdotes into a pattern.

## In practice

A team sees a drop-off on a settings screen and plans to redesign it.

Six interviews with people who recently stalled there produce a different explanation. The screen is fine. Users stop because it asks for a piece of information they do not have and cannot get without emailing their IT department, and having sent that email, they close the tab and come back a week later, if at all.

Analytics could show the drop and never the cause. The redesign would have produced a clearer version of a screen that would still have stopped everybody in the same place.

What the research changed was the sequence rather than the screen: the field became optional at that point and requested later, when the user had a reason to care about it.

## Where teams get it wrong

- **Research as confirmation.** Sessions scheduled after the design is finished, to validate it.
- **Asking about the future.** Stated intent is a poor predictor of behaviour.
- **Talking only to happy customers.** They are the easiest to reach and the least informative.
- **Reporting findings with no evidence attached.** An unsupported claim is an opinion with a researcher's name on it.
- **Treating analytics as sufficient.** Complete coverage of what, and no coverage of why.

## Related terms

- [Usability Testing](https://www.themasterly.com/glossary/usability-testing)
- [User Persona](https://www.themasterly.com/glossary/user-persona)
- [Customer Journey Map](https://www.themasterly.com/glossary/customer-journey-map)
- [UX Design](https://www.themasterly.com/glossary/ux-design)

## Learn more

- [UX audit service](https://www.themasterly.com/services/ux-audit)

## FAQ

**What is user research?**

The systematic study of what people are trying to do, how they currently do it, and what gets in the way. It covers interviews, observation, usability sessions, surveys and analysis of behaviour already recorded in the product, and its purpose is to make design decisions on evidence rather than on the most confident opinion in the room.

**What is the difference between generative and evaluative research?**

Generative research asks what problem to solve and runs before anything is designed: interviews, observation, diary studies. Evaluative research asks whether a solution works and runs against something that exists: usability testing, tree testing, A/B tests. Teams commonly do the second and skip the first, then wonder why a usable product went unused.

**How many people do you need to interview?**

For qualitative work, six to eight per distinct group is usually enough to see the pattern, and the signal that you have enough is hearing the same things you already heard. Quantitative claims about how often something happens need far larger samples and are better answered from product data.

**How do you do user research in B2B when users are hard to reach?**

Recruit through customer success against a specific behaviour rather than general willingness, include churned and downgraded accounts because they are the most informative and the least available, and use internal proxies such as support agents while remembering they are proxies. Screening for what somebody did beats screening for their job title.

**Can analytics replace talking to users?**

No, and neither replaces the other. Product data tells you what happened and how often, with complete coverage and no explanation. Research tells you why, from a handful of people. A drop-off number and the reason for it are different findings, and acting on the first without the second usually produces a redesign of the wrong thing.

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