Survey Question Builder & Bias Checker
Check a survey question for leading words, double-barreled wording, jargon and length, then get a more neutral rewrite.
Question
Bias check
How to use the survey question bias checker
Paste one survey question. The tool checks for leading words (such as amazing or excellent) that push people toward an answer, double-barreled wording that asks two things at once, business jargon that confuses respondents, wording that assumes experience, and length. When it finds leading words or a double question, it suggests a neutral rewrite, split into two questions where it can.
Why question wording matters
Bad questions produce bad data. Leading words nudge respondents toward a positive or negative answer. Double-barreled questions make a clean answer impossible. Jargon makes people guess or skip. A quick check before you send a survey is one of the cheapest ways to improve the data you get back.
Common uses
- QA on customer satisfaction surveys before launch
- Reviewing NPS follow-up questions
- Checking post-purchase email surveys
- Refining product feedback forms
- Training new researchers to write neutral questions
The most common bias patterns
- Leading: "How much do you love our amazing product?" pushes toward a positive answer.
- Double-barreled: "How satisfied are you with our product and support?" asks two things.
- Jargon: "How well does our platform leverage your workflow?" leaves people unsure what you mean.
Keep in mind that this is a word-based check. It catches the common patterns, but a careful human read is still worth it.
Frequently asked questions
Should I use a 5-point or 7-point scale?
A 7-point scale gives more detail. A 5-point scale is faster to answer and works for most surveys. NPS uses an 11-point scale (0 to 10) by design.
How many questions should a survey have?
As few as you need. Completion tends to drop as surveys get longer, so cut any question you will not act on.
Should I ask demographic questions first or last?
Usually last. They can feel personal, and people are more willing to answer once they have already invested time in the survey.
How should I handle "no opinion" answers?
Offer "Not applicable" or "Don't know". Forcing an answer creates fake data. Track the share of those answers separately.