Think it is easy to create a questionnaire? Just draft a few questions, select appropriate answer options, and the survey is ready to launch—right?
Not quite! Even minor mistakes can skew your results of a market research study——or worse, make them completely useless. In this blog post, we’ll show you how to avoid common pitfalls to achieve meaningful and reliable results. This can lead to the basis for strategic decisions being flawed.
Possible consequences: Products and communication measures are not relevant for the target groups, innovations are developed that later turn out to be costly flops.
In this blog post, we’ll show you how to avoid common pitfalls to achieve meaningful and reliable results.
The Power of the First Question: Why Introduction of Your Questionnaire Matters
The first question in a questionnaire plays a crucial role in the success of the survey. It sets the tone for the entire process and can significantly influence participant engagement.
A well-formulated first question ensures that participants feel comfortable, perceive the survey as relevant, and are more likely to complete the entire questionnaire. A poorly chosen start, however, can lead to high dropout rates and negatively affect the quality of responses.
Furthermore, the first question can help put participants in the right mindset to better answer subsequent questions. It is often used to introduce participants to the survey topic and guide the direction of the survey.
Open vs. Closed? Choosing the Right Question Type When You Create a Questionnaire
The choice between open-ended and closed-ended questions is a critical decision when you create a questionnaire, as it directly affects the quality and type of data collected.
- Closed questions provide a limited set of predefined answer options, making it easier for respondents to answer quickly without much thought. They are simple to analyze since the responses are standardized. These questions work well when you need specific, quantifiable data. For example: “Have you heard of [product name] before? (Yes/No)”. Closed questions are ideal for gathering quick, comparable data and identifying clear patterns.
- Open questions, on the other hand, allow respondents to formulate their answers freely, leading to deeper, qualitative insights. They are especially useful for exploring respondents’ thoughts, feelings, or opinions. For example: “What did you like about this product?” However, open questions are harder to analyze because each response needs to be individually reviewed and categorized. They can also take more time to answer, potentially lowering participation rates.
In many cases, a combination of both types is most effective: closed questions for structured, quantifiable data and open questions for valuable qualitative insights.
Create a Successful Questionnaire: Response Scales, Flow, and Effect of Question Order
Other key elements of a high-quality questionnaire are clear and consistent response scales. They ensure that the answers remain precise, understandable and comparable. Inconsistent or unclear scales can cause confusion and severely impact data quality.
When using numerical scales (e.g., 1 to 5), it’s essential to define each option clearly, such as “1 = very dissatisfied” and “5 = very satisfied.” Scales should also be symmetrical to avoid bias toward positive or negative responses. For open-ended questions, ensure respondents have enough space to provide detailed answers without feeling restricted by layout or character limits.
The phrasing of questions is equally important. Avoid leading or suggestive questions that could influence respondents and compromise the neutrality of their answers. Instead, use neutral and objective language to capture authentic responses.
The order of questions also requires careful attention, as order effects can influence responses. Early questions can provide context and shape how later questions are perceived. To minimize these effects, carefully plan and test the sequence of your questions. For instance, questions outside the central topic or those that might influence others should be placed toward the end of the survey.
How Artificial Intelligence is Revolutionizing Questionnaire Creation
Using AI to create a questionnaire offers numerous advantages. AI tools analyze and refine the language of survey questions, identifying ambiguities or biases that might confuse respondents. By improving question clarity, AI enhances response accuracy and increases the overall reliability of survey results.
Another major benefit of AI is its ability to automatically generate questions. Using intelligent algorithms, these tools can create questions based on the criteria you provide, saving you significant time and effort. While you can always tweak the automatically generated questions to suit your target audience, AI offers an excellent starting point.
AI can also optimize the structure and flow of your questionnaire, ensuring that questions are presented logically to improve the survey’s flow and reduce response biases.
However, even with AI support, it’s important to review and adjust the final questionnaire to ensure it meets your specific needs.
Pretest, Please! Why Testing Your Questionnaire Is Critical
When you create a questionnaire and you are confident in their work, it’s essential to test whether respondents interpret the questions as intended. Personal experience alone is not enough to guarantee success.
A pretest is an invaluable tool for this purpose. It involves testing the entire questionnaire on a small group of participants to assess question clarity, identify confusing or ambiguous phrasing, and evaluate the response options. The pretest also allows you to check the survey’s logic, such as skip patterns, and highlights potential weaknesses that might otherwise go unnoticed. Additionally, it provides preliminary data, helping you refine your analysis methods.
It’s equally important to review the response options, especially for open-ended questions, to ensure that the survey captures sufficient data without overwhelming respondents. This level of detail cannot be reliably assessed through experience alone, as time requirements and question lengths are often underestimated.
By conducting a pretest, you can identify and fix not only content-related weaknesses but also structural and methodological mistakes. This significantly improves the quality of your data and the reliability of your results.
7 Tips for Creation a Better Questionnaire
The following seven points will show you how to reduce mistakes and improve your results:
- Start with an introducing first question.
- Combine open-ended and closed-ended questions.
- Use clear and consistent response scales.
- Phrase questions neutrally and objectively.
- Pay attention to question order and its effects.
- Leverage AI tools for optimization.
- Test your questionnaire with a pretest.
Conclusion
Questionnaire creation requires both attention to detail and a deep understanding of your target audience and survey objectives. Precise phrasing, a clear structure, and neutral questions are essential for producing reliable results. Avoid common mistakes, thoroughly test your questionnaire, and tailor it to the needs of your audience.
A well-designed questionnaire is the foundation for informed decisions and successful projects.
As Albert Einstein famously said: ‘If I had an hour to solve a problem, I’d spend 55 minutes thinking about the right question to ask.’
Take the time to get it right—it’s worth it!
With market research consulting by BESTVISO GmbH, you can design scientifically based questionnaires tailored to deliver even more reliable and relevant results.
Sources:
- Ortmanns, W., & Sonntag, R. (2023). Umfragen erstellen und auswerten: kompakt und leicht verständlich für Studierende und junge Forschende.
- Porst R. Im Vorfeld der Befragung: Planung, Fragebogenentwicklung, Pretesting. ZUMA-Arbeitsbericht. 1998;02:1–45. https://www.ssoar.info/ssoar/handle/document/20048