AI survey question builder
Bad survey data usually comes from bad questions, not bad respondents. Leading wording, double-barrelled items, and lopsided scales quietly push answers in a direction, and you only discover it after the responses are in. This builder produces an LLM prompt that generates questions tied to your goal and explicitly guards against the classic biases — so the survey measures what you actually want to know.
How it works
You describe the survey’s goal, the audience, the question types you want (multiple choice, Likert scale, ranking, open-ended), and how many questions. The builder writes a prompt that instructs the model to keep every question anchored to the goal, use neutral non-leading wording, avoid double-barrelled and loaded items, and build balanced, labelled response scales. It also asks the model to return a short bias check next to each question, noting why it is neutral, so you can review the reasoning rather than trust it blindly.
Tips and examples
- One idea per question. “Was the product fast and easy to use?” is two questions. The prompt splits these automatically.
- Avoid the agreement trap. Always offer a genuine negative option; the prompt enforces balanced scales so “agree” isn’t the only easy answer.
- Put demographics last. Sensitive or boring questions at the end protect your completion rate — the prompt orders them accordingly.
- Pilot before sending. Even bias-checked questions benefit from five test respondents; the prompt suggests a pilot note where useful.