User experience survey questions

There is no shortage of UX question lists. Most of them hand you 40 questions with no guidance on which to use, and none of them mention that for several of the things you're trying to measure, validated instruments already exist and have been benchmarked across thousands of studies.

That's the decision worth making before you write a single question: are you measuring something standard, where a proven instrument gives you a comparable score, or are you investigating something specific to your product, where your own questions are the only option?

Get that wrong, and you either reinvent a scale badly or run a standardized survey that never asks about the feature you're worried about.

Below are 36 questions for the second case, grouped by what you're trying to learn, plus guidance on when to reach for the first.

These target product and app experiences. If you're specifically measuring a website, the website feedback survey guide has a question set built for that context.

Keep these last and optional.

Rating questions give you a numerical score, but open-ended follow-up responses give you a concrete next step.

A standard effort question like "How easy or difficult was it to complete your task today?" tells you that a user flow is painful. A professional follow-up like "What specific step prevented you from completing your task?" reveals that the culprit was the address field on step three.

That's the difference between a product designer receiving a vague support ticket and a designer having a clear hypothesis to test. Keep at least two or three open-text questions in your UX survey, and place them right after the rating score they explain while the reason is still fresh in your respondent's head.

The tradeoff is analysis time. Open-ended text takes longer to review than a bar chart, which is why platform analyze features matter here. Sentiment analysis and text categorization turn hundreds of open responses into clear themes, while cross-tabs let you check whether first-time users are describing a completely different product experience than your power users. They usually are, and simple averages hide it.

This matters more than it sounds. Proving that user experience work drives real business impact rather than vanity metrics is one of the hardest parts of your job. A score that only exists inside your own isolated spreadsheet is easy for stakeholders to dismiss. A validated survey scale isn't.

So if you need a number you can compare across releases, against competitors, or over time, use a pre-tested survey framework instead of inventing a scale from scratch.

The System Usability Scale (SUS) is the best-known example. It uses ten ease-of-use questions answered on a five-point agreement scale to produce a single, reliable score. While calculating it takes a bit more effort than a simple average and the score itself doesn't point to specific fixes, it gives you a clean metric you can trust.

SUPR-Q covers similar ground with a focus on usability and satisfaction, and the SurveyMonkey platform has it ready as a pre-built template linked at the end of this guide.

A simple rule for choosing:

Do not modify a standardized instrument's wording or scale. Once you change the items, the benchmark no longer applies and you've given up the only real advantage it had.

Start with the task, not the rating. Asking "were you able to finish what you came here to do?" before asking how satisfied someone is anchors the rest of the survey in a real event rather than a general impression.

Keep one scale throughout. If you use Likert scales, keep the same point system across every question, so a 1 always means the same thing from first question to last, in line with our poll question guidance.

Avoid unbalanced scales. A scale running from "enjoyed it a little" to "enjoyed it a lot" has no room for a negative answer, which quietly manufactures a positive result. The guide to UX surveys covers this and other biases in more detail.

Ask one thing per question. Combining taste and texture, or speed and clarity, produces answers you cannot act on.

Trigger in context where you can. A question asked immediately after someone finishes or abandons a task gets you a specific answer. The same question in a monthly email gets you a vague one. Behavior-based triggers make this possible on web experiences via the website feedback use case.

Once responses are in, filter and cross-tab by role, device, and usage frequency to find where segments diverge. Averages hide the beginner who cannot get through setup.

Decide first whether you need a comparable score or a diagnosis. That single choice determines whether you start from a validated instrument or from your own question set.

If you need the score, start from the SUPR-Q questions template, which has the instrument built and ready to send. If you need the diagnosis, pick the six questions above that map to the flow you're worried about and build from a product feedback survey foundation.