Key Takeaways
- The questions that keep recurring are the ones with a fixed scale behind them. The recommendation question, the three-item satisfaction index and the effort question survive because the number means roughly the same thing wherever it gets asked. Reword one and you keep the question but lose the comparison.
- No public dataset ranks survey questions by popularity. What exists is a handful of standardized metrics plus a long tail of house-written questions, so pick questions by what you plan to do with the answer rather than by a claimed popularity order.
- The scale decides what the answer is worth. Pew Research Center found 58% of respondents named the economy as their top election issue when it appeared in a list, against 35% who volunteered it unprompted. Same topic, two formats, 23 points apart.
- Agree or disagree is the weakest common format. Pew's work on acquiescence bias shows some respondents agree with whatever statement you put in front of them, which matters because one of the most copied customer questions is written that way.
Most question lists hand you wording and stop. That leaves out what decides whether the answer is usable: the response scale, the moment you ask, and the metric the number feeds. Five labelled points with a published convention behind them give you a figure you can track for three years. The same question rewritten in your own voice on a 1 to 4 scale gives you a number nobody, including your future self, can interpret. So every example below carries its scale and the reading it supports, grouped by the moment it belongs to.
Why "popular" is the wrong filter
There is no register of question popularity. Vendors publish lists drawn from their own template libraries, which tells you what their customers clicked, not what works. What does exist is a small set of standardized items, each with a documented origin and a conventional scale:
- The recommendation question, introduced in Harvard Business Review in 2003, asked on 0 to 10.
- The three-item satisfaction index behind the American Customer Satisfaction Index, each item on 1 to 10. A NASA Planetary Data System survey run on that methodology publishes all three items with their endpoint labels.
- The effort question, proposed in Harvard Business Review in 2010 on the grounds that reducing customer work predicts loyalty better than exceeding expectations does.
- Importance and satisfaction ratings on the same outcome, the pairing behind the opportunity scoring in Harvard Business Review's account of outcome-driven innovation.
Those four cover satisfaction, loyalty, effort and unmet needs. Everything else below is a house question: useful, specific to your business, not comparable to anyone else's. Standard items go in verbatim because their value is the benchmark, house questions get written for your decision because their value is specificity, and mixing the two tiers is how teams end up with a reworded satisfaction score nobody can benchmark.
Skip the survey entirely if you already know what you would do with every possible answer, or if nobody has agreed who reads the results. In a 30-comment r/CustomerSuccess thread on satisfaction surveys, the person who started it came back after the replies to say timing and brevity mattered more than the question set. Shipping fewer questions at a better moment beats a longer form.
The four standard questions worth copying verbatim
Satisfaction, as three items rather than one
The index version asks three questions, each on a 1 to 10 scale: overall satisfaction, performance against expectations, and closeness to an ideal. The weighted average gets rescaled to 0 to 100 for reporting.
| Item | Scale (1 to 10) |
|---|---|
How satisfied are you with [X] overall? | 1 very dissatisfied, 10 very satisfied |
ItemHow satisfied are you with [X] overall? Scale (1 to 10)1 very dissatisfied, 10 very satisfied | |
How does [X] compare with your expectations? | 1 falls short of expectations, 10 exceeds expectations |
ItemHow does [X] compare with your expectations? Scale (1 to 10)1 falls short of expectations, 10 exceeds expectations | |
How close does [X] come to your ideal? | 1 not very close to the ideal, 10 very close to the ideal |
ItemHow close does [X] come to your ideal? Scale (1 to 10)1 not very close to the ideal, 10 very close to the ideal | |
Three items instead of one is not padding. A single satisfaction score drifts with mood and recency, and the expectations item separates "this was bad" from "this was fine but I expected more", which point at different fixes. If you only have room for one, keep the first and accept that you have a mood reading rather than an index.
Recommendation, on 0 to 10
The recommendation question asks how likely the respondent is to recommend the company, product or service to a friend or colleague, on an 11-point scale from 0 to 10. Answers of 9 or 10 count as promoters, 7 or 8 as passives, 0 through 6 as detractors, and the score is the promoter percentage minus the detractor percentage, so it runs from -100 to +100.
Two details get dropped in practice and both matter. The scale is 0 to 10, not 1 to 10, and collapsing it breaks the buckets. And the follow-up asking for the main reason behind the score is where the usable material sits: the number tells you the direction, the sentence tells you what to change. Keep that follow-up open and optional.
Effort, and why its popular wording is a problem
The original effort question asked how much effort the respondent personally had to put forth to handle their request, on a 1 to 5 scale. The revision in wide use today is a statement rated on a 1 to 7 agreement scale, saying the company made it easy to handle the issue. CustomerThink's account of that revision sets out the change and the reasoning.
Here is the catch the question lists skip. Pew Research Center's guidance on writing survey questions documents acquiescence bias: faced with an agree or disagree statement, some respondents agree regardless of content, unevenly across education levels. Pew's recommended alternative is a forced choice between two statements. So the most-copied effort wording sits on the format with the known measurement problem. To track effort over years, ask it directly and show all five points.
Unmet needs, as a pair of ratings
Asking people what to build gives you a feature list, usually one that reflects whoever answered last. The pairing approach asks two ratings about the same outcome, typically on 1 to 5 or 1 to 7: how important that outcome is, and how satisfied they are with it today. Rank the gaps and you have an ordered list of opportunities rather than a wish list. It costs two rows per outcome, so cap it at six outcomes before the grid gets punishing on a phone.
40 popular survey questions by moment
Each row carries the scale the question needs and the reading it supports. Where a scale says "open", keep the field optional. Our notes on multiple choice question design and open-ended question wording cover the traps inside each format.
After a purchase or signup
| Question | Scale | What the answer tells you |
|---|---|---|
How satisfied are you with your purchase so far? | 1 to 10 | Baseline for the satisfaction index |
QuestionHow satisfied are you with your purchase so far? Scale1 to 10 What the answer tells youBaseline for the satisfaction index | ||
How easy was it to complete your order? | 1 to 5 | Checkout friction |
QuestionHow easy was it to complete your order? Scale1 to 5 What the answer tells youCheckout friction | ||
What were you trying to get done today? | Open | Job the buyer hired you for |
QuestionWhat were you trying to get done today? ScaleOpen What the answer tells youJob the buyer hired you for | ||
Which of these nearly stopped you buying? | Multiple choice, randomized | Objection ranking |
QuestionWhich of these nearly stopped you buying? ScaleMultiple choice, randomized What the answer tells youObjection ranking | ||
How did you first hear about us? | Single choice plus other | Channel attribution, self-reported |
QuestionHow did you first hear about us? ScaleSingle choice plus other What the answer tells youChannel attribution, self-reported | ||
How does the product compare with your expectations? | 1 to 10 | Expectation gap against promise |
QuestionHow does the product compare with your expectations? Scale1 to 10 What the answer tells youExpectation gap against promise | ||
How likely are you to recommend us to a friend or colleague? | 0 to 10 | Promoter and detractor split |
QuestionHow likely are you to recommend us to a friend or colleague? Scale0 to 10 What the answer tells youPromoter and detractor split | ||
The second question earns its place more than the first. Order friction is fixable this quarter, where a satisfaction figure takes a programme to move.
After a support interaction
| Question | Scale | What the answer tells you |
|---|---|---|
How much effort did you personally have to put in to get this resolved? | 1 to 5 | Effort score, comparable over time |
QuestionHow much effort did you personally have to put in to get this resolved? Scale1 to 5 What the answer tells youEffort score, comparable over time | ||
Was your issue resolved? | Yes or no | Resolution rate, the denominator for everything else |
QuestionWas your issue resolved? ScaleYes or no What the answer tells youResolution rate, the denominator for everything else | ||
How many times did you have to contact us about this? | Numeric | Repeat-contact cost |
QuestionHow many times did you have to contact us about this? ScaleNumeric What the answer tells youRepeat-contact cost | ||
How satisfied were you with the agent who helped you? | 1 to 5 | Agent-level quality |
QuestionHow satisfied were you with the agent who helped you? Scale1 to 5 What the answer tells youAgent-level quality | ||
What would have let you solve this without contacting us? | Open | Self-service gaps |
QuestionWhat would have let you solve this without contacting us? ScaleOpen What the answer tells youSelf-service gaps | ||
How clear was the answer you received? | 1 to 5 | Explanation quality, separate from outcome |
QuestionHow clear was the answer you received? Scale1 to 5 What the answer tells youExplanation quality, separate from outcome | ||
Ask the resolution binary first. A high satisfaction rating from someone whose problem is still open is a reading of the agent's manner, not of your support. The dichotomous question examples guide covers where yes or no beats a scale.
Product and feature feedback
| Question | Scale | What the answer tells you |
|---|---|---|
How important is [outcome] to you? | 1 to 5 | Half of the opportunity pair |
QuestionHow important is [outcome] to you? Scale1 to 5 What the answer tells youHalf of the opportunity pair | ||
How satisfied are you with [outcome] today? | 1 to 5 | The other half |
QuestionHow satisfied are you with [outcome] today? Scale1 to 5 What the answer tells youThe other half | ||
Which features did you use in the last month? | Multiple choice, randomized | Self-reported adoption |
QuestionWhich features did you use in the last month? ScaleMultiple choice, randomized What the answer tells youSelf-reported adoption | ||
What did you expect this feature to do that it does not? | Open | Mental-model mismatch |
QuestionWhat did you expect this feature to do that it does not? ScaleOpen What the answer tells youMental-model mismatch | ||
How would you feel if you could no longer use this product? | Very disappointed, somewhat, not disappointed | Attachment, read as a share rather than a mean |
QuestionHow would you feel if you could no longer use this product? ScaleVery disappointed, somewhat, not disappointed What the answer tells youAttachment, read as a share rather than a mean | ||
What are you doing outside the product that you wish you could do inside it? | Open | Workaround inventory |
QuestionWhat are you doing outside the product that you wish you could do inside it? ScaleOpen What the answer tells youWorkaround inventory | ||
Cancellation and churn
| Question | Scale | What the answer tells you |
|---|---|---|
What made you decide to cancel? | Single choice plus other | Coded churn reasons |
QuestionWhat made you decide to cancel? ScaleSingle choice plus other What the answer tells youCoded churn reasons | ||
Which tool are you moving to? | Open | Competitive loss, named |
QuestionWhich tool are you moving to? ScaleOpen What the answer tells youCompetitive loss, named | ||
How well did we fit your needs? | 1 to 5 | Fit versus execution |
QuestionHow well did we fit your needs? Scale1 to 5 What the answer tells youFit versus execution | ||
Was price the deciding factor? | Yes or no | Separates price from value |
QuestionWas price the deciding factor? ScaleYes or no What the answer tells youSeparates price from value | ||
What would have to change for you to come back? | Open | Winback conditions |
QuestionWhat would have to change for you to come back? ScaleOpen What the answer tells youWinback conditions | ||
The binary on price pays for itself. Teams routinely read a free-text cancellation answer mentioning cost as a pricing problem when it is a value problem, and one yes or no field tells the two apart.
After an appointment or a call
| Question | Scale | What the answer tells you |
|---|---|---|
How easy was it to book this appointment? | 1 to 5 | Booking friction |
QuestionHow easy was it to book this appointment? Scale1 to 5 What the answer tells youBooking friction | ||
Did the appointment start on time? | Yes or no | Operational reliability |
QuestionDid the appointment start on time? ScaleYes or no What the answer tells youOperational reliability | ||
How satisfied are you with the outcome of the meeting? | 1 to 5 | Perceived value of the slot |
QuestionHow satisfied are you with the outcome of the meeting? Scale1 to 5 What the answer tells youPerceived value of the slot | ||
What is still unclear after our conversation? | Open | Follow-up material, named by the client |
QuestionWhat is still unclear after our conversation? ScaleOpen What the answer tells youFollow-up material, named by the client | ||
What nearly stopped you keeping this appointment? | Open | Cheapest no-show research available |
QuestionWhat nearly stopped you keeping this appointment? ScaleOpen What the answer tells youCheapest no-show research available | ||
Would you like us to schedule the follow-up now? | Yes or no | Next step, captured while intent is live |
QuestionWould you like us to schedule the follow-up now? ScaleYes or no What the answer tells youNext step, captured while intent is live | ||
That fifth question is underused, and answers to it usually name something mundane a better appointment reminder would have handled. The last one is the only question here that does work rather than measuring it.
Event and webinar follow-up
| Question | Scale | What the answer tells you |
|---|---|---|
How relevant was today's content to your work? | 1 to 5 | Audience fit |
QuestionHow relevant was today's content to your work? Scale1 to 5 What the answer tells youAudience fit | ||
What is the one thing you will do differently after today? | Open | Stated intent, a usable headline |
QuestionWhat is the one thing you will do differently after today? ScaleOpen What the answer tells youStated intent, a usable headline | ||
Which section would you cut? | Single choice from the agenda | Agenda pruning, specific |
QuestionWhich section would you cut? ScaleSingle choice from the agenda What the answer tells youAgenda pruning, specific | ||
How likely are you to attend another session? | 1 to 5 | Repeat interest |
QuestionHow likely are you to attend another session? Scale1 to 5 What the answer tells youRepeat interest | ||
Who else on your team should have been here? | Open | Referral surface |
QuestionWho else on your team should have been here? ScaleOpen What the answer tells youReferral surface | ||
Send these inside an hour. Attention after a webinar drops faster than after any other interaction on this list.
Employee pulse
| Question | Scale | What the answer tells you |
|---|---|---|
Do you have what you need to do your job well? | Yes or no | Blockers, countable |
QuestionDo you have what you need to do your job well? ScaleYes or no What the answer tells youBlockers, countable | ||
How manageable was your workload this week? | 1 to 5 | Trend line, not a verdict |
QuestionHow manageable was your workload this week? Scale1 to 5 What the answer tells youTrend line, not a verdict | ||
What slowed you down most this week? | Open | Specific friction |
QuestionWhat slowed you down most this week? ScaleOpen What the answer tells youSpecific friction | ||
How clear are you on what you are expected to deliver? | 1 to 5 | Direction clarity |
QuestionHow clear are you on what you are expected to deliver? Scale1 to 5 What the answer tells youDirection clarity | ||
How comfortable are you raising a problem with your manager? | 1 to 5 | Safety proxy, worth tracking quarterly |
QuestionHow comfortable are you raising a problem with your manager? Scale1 to 5 What the answer tells youSafety proxy, worth tracking quarterly | ||
State who reads the raw answers before asking any of these. Anonymity that respondents do not believe produces careful answers, which is worse than fewer answers.
Choosing the response scale
Five rules, each with evidence behind it rather than convention.
Keep the scale fixed if you plan to compare. Changing a 5-point scale to 7 points next year resets your trend line. Pick the convention that belongs to the metric and leave it alone.
Label the endpoints in words. A row of bare numbers means something different to every respondent. The satisfaction items above label both ends, which is why the index survives translation.
Prefer a forced choice to agree or disagree. Pew recommends offering a choice between two alternative statements, which changes both the overall result and the pattern across education levels.
Randomize answer options. Pew notes a primacy effect in self-administered surveys, where respondents lean toward items at the top of a list. Randomizing spreads that bias evenly instead of favouring whichever option you typed first.
Decide between open and closed before writing the question. Pew's election example is the clearest illustration available: 58% picked the economy as their top issue when it appeared in a list, against 35% who volunteered it, and 43% of open-ended respondents gave an answer that was not on the closed list at all. Closed questions measure what you already thought of. Open ones find what you missed, and they get skipped far more often, which Pew's analysis of open-ended nonresponse puts at roughly 18% against 1% to 2% for closed items.
Five ways these questions go wrong
- Rewording a standard item to fit your brand voice. The 0 to 10 recommendation question with a friendlier verb is no longer the recommendation question, and the benchmark you were planning to cite no longer applies to your number.
- Two questions in one row. Asking what people liked and what they would change gets you an answer to whichever half is easier, and silence on the other. A 30-comment r/UXResearch thread collecting badly written survey questions keeps landing on a related fault: questions that presume the respondent's situation, which forces a wrong answer rather than no answer.
- Asking everyone every question. Branching exists so that the person who rated you a 9 never sees the question about what went wrong. Average burden across the whole respondent pool is what drives abandonment, not the length of any single path.
- Collecting free text with no retention plan. An open field collects whatever the respondent types, including health details or a colleague's name you never asked for. The data minimisation principle in Article 5 of the GDPR is hard to honour by design here, so say in the field label what not to include and keep raw text for a shorter window than coded themes. Our notes on GDPR-compliant software selection cover the vendor side.
- No action attached to any answer. Decide before launch which answer triggers a person doing something. If no answer changes anything, you are spending respondent goodwill on a chart, a point that runs through our guides to running a customer feedback programme and client feedback surveys.
Tools that help
Any form builder renders a rating field. What separates them here is whether the scale types exist natively, whether follow-ups can be conditional, and whether a bad answer reaches a human without an export step. The comparison of online survey tools covers the field more broadly.
meetergo is a Cologne-built scheduling and revenue-pipeline platform spanning sales, consulting, healthcare and education, with forms and polls as apps inside it rather than the whole product. Three things matter for a question set like this one.
Native rating, NPS and scale fields
The forms app carries 20+ field types including rating, NPS, file upload, signature and payment fields (checked 2026-10-20), so the 0 to 10 and 1 to 5 scales above exist as field types rather than as a row of radio buttons you build by hand. Typeform forms import with their Scale field intact.
Conditional follow-ups and answer scoring
Follow-up questions appear only when an answer matches, which is the branching rule from the mistakes list applied at the field level. Answer choices can carry points, and routing forms send the respondent to the right owner based on the result, so a detractor score can open a conversation rather than a chart.
A free poll tool for one-question asks
The survey and poll tool runs on a shared link, respondents vote without creating an account, participants and responses are uncapped, results update live, and exports go to Excel, CSV or PDF. Its page lists an anonymous voting option, worth reading precisely: a poll with no identifier is anonymous, a form that also collects an email is not, whatever setting you tick. Short questions can ride along with a booking through invitee questions, and submissions land in the built-in CRM as contact records.
Honest limitation: there is no statistical layer. No significance testing, no crosstabs, no sentiment or theme coding of free text. For a quarterly voice-of-customer programme reporting segment-level significance, export to a research platform. The free poll tool is single and multiple choice only, so branching lives in the forms app rather than in polls. Forms sit on every tier including the free plan, with routing on user-defined criteria from the Suite tier up (pricing).
Put your first question set in front of real respondents today. Start free with meetergo, no credit card required.
Booking + video conferencing in one tool.
Booking + video conferencing in one tool.
FAQs
How many questions should a feedback survey contain?
Five to seven for anything sent to customers, with one open question placed last. The binding constraint is total effort rather than a count: five one-tap ratings cost a respondent less than two questions asking them to compose sentences.
Which survey question is used most often?
The 0 to 10 recommendation question is the most widely standardized, which is not the same as the most asked. Nobody publishes an audit of what questions appear in the world's surveys, so treat ranked popularity claims with suspicion and choose on fit instead.
What is the best rating scale for a survey?
The one the metric already specifies: 0 to 10 for the recommendation question, 1 to 10 for the satisfaction index items, 1 to 5 for most house ratings. Where you are free to choose, 5 points with labelled ends reads cleanly on a phone and gives you enough spread to see movement.
Should a survey scale have a neutral midpoint?
Keep it for attitude questions, where neutral is a real position. Drop it for questions about something that did or did not happen, where the midpoint becomes a parking space for people who want to finish fast.
How do you ask survey questions anonymously?
Collect no identifier, do not pre-fill one, and say in the first line who sees the raw answers. Link-based polls without a login make this straightforward. Once a form captures an email or sits behind an account, the survey is confidential at best.
What should happen after the responses come in?
Code the open answers into a small set of themes, count how many responses sit behind each, and route the individual answers that need a human reply before you touch the summary. Reporting before routing is the most common way a feedback programme stops producing anything.
