Designing an effective survey means more than just compiling a list of questions—it requires thoughtful planning, clarity of purpose, and attention to how participants will interact with the questionnaire. A well-designed questionnaire helps ensure high-quality data, reduces dropout rates, and enhances the overall experience for respondents. A fundamental principle in survey design is KiSS—Keep It Short and Simple. Use clear, concise language that can be easily understood across diverse age groups, backgrounds, and education levels. Avoid technical jargon, unfamiliar acronyms, idioms, or culturally specific phrases that may confuse respondents. Consistency in terminology is also critical—for example, if you introduce a concept using one term (e.g., "climate change"), avoid switching to another (e.g., "global warming") later in the survey. Be cautious about bias in question wording. Avoid:

• Leading questions (e.g., “Don’t you think the new policy is unfair?”),

• Double-barrelled questions (e.g., “How much do you enjoy collecting and analysing data?”),

• Negative questions (e.g., “Is it not easy to find information on this website?”),

• Ambiguous language (e.g., “Do you regularly exercise?” – what counts as "regular"?),

• Assumptive questions (e.g., “Which social media app do you use the least?” assumes all respondents use social media).

In terms of layout and presentation, ensure high readability by using standard, sans-serif fonts (e.g., Arial or Calibri), clear contrast (dark text on a light background), and appropriate font sizes. Avoid capital letters for entire words or sentences, which can feel like “shouting.” Use numbered questions, page breaks, and progress indicators to help respondents track their progress.

Types and formats of questions

A good questionnaire uses a mix of question types suited to the research aims and the respondent experience:

• Closed questions (e.g., multiple choice, checkboxes, yes/no) are easier to analyse and less demanding for respondents. Use these for collecting factual, behavioural, or categorical data.

• Open-ended questions invite richer responses but are more cognitively demanding and time-consuming to analyse. Limit their number (ideally, no more than 2–4 per survey) and avoid making them mandatory.

• Rating scales, such as Likert scales, are common for measuring agreement or satisfaction. Ensure your scales are balanced (e.g., equal positive and negative options, with a neutral midpoint if appropriate).

• Ranking questions ask respondents to prioritise items and are useful for comparing preferences, though they provide less detail than rating scales.

• Demographic and classification questions (e.g., age, income, education level, location) should be phrased with care. Use ranges instead of exact values for sensitive items, and consider using standard categories (e.g., ABS age groupings) to support comparability.

Note: See more information on Question Types.

Question sequencing tips

The order of questions influences how respondents perceive and engage with your survey. Apply the following sequencing principles:

• Start with easy, non-sensitive questions to build confidence and engagement.

• Group similar topics together to improve logical flow and reduce cognitive switching.

• Use skip logic to direct respondents past irrelevant questions, based on earlier responses.

• Place sensitive or personal questions (e.g., income, health, political views) later in the survey, once rapport has been established.

• Be cautious with long blocks of similar questions (e.g., Likert items), which can lead to fatigue and increased dropout rates.

Thoughtful survey design enhances data quality and helps ensure that respondents stay engaged from start to finish. Pilot testing is essential to identify issues with clarity, structure, or flow before launching the full survey.