Well-written survey questions are the foundation of trustworthy research. They guide respondents through the process, shape the quality of the feedback, and ultimately influence the decisions businesses make with the results. By ensuring that questions are neutral and free from leading language, researchers can gather data that truly reflects the opinions and behaviors of respondents. Conversely, biased questions can distort data, leading to misleading conclusions and poor decision-making.
The Profiles team at Kantar understands that survey design plays a critical role in getting closer to what people really think, feel, and do. That’s why we partner with clients to create unbiased, effective questionnaires that drive confident decisions.
In the following article, we’ve compiled tips and best practices for crafting unbiased survey questions from our experts that can help lead to more accurate and reliable data.
Understanding Survey Bias
Survey bias occurs when the wording, structure, or context of questions influence respondents' answers in a way that does not accurately reflect their true opinions or behaviors.
Some of the most common types of survey bias include:
- Leading Questions: These are questions that suggest or encourage a respondent to produce a particular answer. Leading questions can sometimes contain emotionally charged language that subtly nudges respondents toward a particular response.
- Loaded Questions: These questions (also known as a complex question), are those that contain assumptions or imply something that is not necessarily true. Loaded questions can force respondents to accept a premise that may not be true before they can answer.
- Double-Barreled Questions: A double-barreled question asks about two (or more) things but only allows one answer. This makes it difficult to interpret what the response actually reflects.
- Ambiguous Wording: These are questions that are unclear or vague, leading to varied interpretations. Respondents may understand the question differently based on their background or context.
- Unbalanced Scales: These are response options in a survey that skew toward a particular sentiment. Unbalanced scales will favor one side of an issue (either positively or negatively) by offering more options or more extreme wording on that side of the scale. These biases can significantly compromise data quality, making it difficult to derive meaningful insights and leading to potential errors in decision-making processes. And in survey research, quality is everything.
Principles of Crafting Unbiased Questions
Writing unbiased survey questions is critical to collecting accurate and meaningful data. Even small missteps in question wording or structure can introduce bias, confuse respondents, or lead to inconsistent answers. The goal is to remove any unintended influence from your questions so that the data truly reflects what respondents think and feel (not what they think you want to hear).
Below are some key principles to guide the creation of unbiased, respondent-friendly questions:
- Use Neutral Language: Questions should be worded in a way that doesn't lead respondents toward a particular response. Avoid emotionally charged language or phrasing that implies a “right” answer.
- Be Specific and Clear: Ensure questions are straightforward and unambiguous, so respondents understand exactly what is being asked. Precise wording helps ensure all respondents understand the question the same way, which improves reliability.
- Avoid Double-Barreled Questions: Focus on one issue per question to prevent confusion and ensure clear responses. When you combine two or more concepts in one question, you risk muddying the responses, especially if the respondent feels differently about each element.
- Balance Response Options: Provide a symmetrical range of answer choices to avoid built-in bias. Scale labels should reflect equal and balanced intervals along a continuum.
- Pilot Testing: Before launching your full survey, test your questions with a small sample of respondents. This helps uncover wording issues, unclear concepts, or unintentional bias that might otherwise go unnoticed. It also gives you a chance to fine-tune your question order, response options, and survey flow.
Examples of Biased vs. Unbiased Questions
To illustrate the difference between biased and unbiased questions, consider the following examples:
Leading Question Example:
- Biased: Don't you agree that our new survey tool is much easier to use?” This question implies that the tool is easier to use and nudges the respondent toward agreement, rather than allowing for an unbiased opinion.
- Unbiased: “How would you rate the ease of use of our new survey tool?” This version allows respondents to share their honest opinions without being influenced by the wording.
Double-Barreled Question Example:
- Biased: How satisfied are you with our customer service and pricing?” This question asks about two different aspects (customer service and pricing) but only allows for one answer.
- Unbiased: How satisfied are you with our customer service?' and 'How satisfied are you with our pricing?” Splitting the question into two separate ones, makes it easier for respondents to give accurate feedback as they may feel differently about customer service and pricing.
Unbalanced Scale Example:
- Biased: Not at all important, somewhat important, Important, very important, extremely important' (2 levels for not important and 3 for important).” In this example, there are only two levels for not important (not at all important and somewhat important) and three levels for important (important, very important, and extremely important). This scale would overrepresent positive sentiment, which could inflate the average score and give a misleading impression of importance.
- Unbiased: Not at all important, somewhat unimportant, somewhat important, very important. In this version, the scale is balanced with two levels for not important and two for important.
Best Practices for Effective Survey Design
Effective survey design goes beyond just crafting unbiased questions. Here are some best practices that can help encourage respondents to provide thoughtful and honest answers, along with creating a smooth and more intuitive experience:
Start with general, then get specific
Start with general questions before moving to specific ones. This helps ease respondents into the survey, improves engagement, and creates a logical flow that builds context for more detailed answers.
Use consistent scales
Always try to use the same scales throughout your survey to avoid confusion. Switching between different scales can confuse respondents and increase the chances of inconsistent or invalid answers. Consistency also makes it easier to analyze the data later on.
Avoid Jargon and technical language
Your audience may not share your background or terminology. Replace industry jargon, acronyms, or complex phrasing with plain language to ensure all respondents understand the questions. If specialized terms are necessary, offer a brief definition or explanation in the question text. Clear, simple language ensures broader comprehension, leading to higher quality responses and reducing the risk of misinterpretation.
Be culturally inclusive
Surveys often reach people from diverse cultural backgrounds. Make sure your language, examples, and imagery are inclusive and respectful. Avoid idioms, references, or assumptions that may not translate across regions or cultures. Doing so helps you avoid unintentionally excluding or alienating segments of your audience.
Assure Anonymity and confidentially
Let respondents know their answers are confidential. This encourages honesty, especially when asking about sensitive topics, and leads to more candid, actionable feedback. Make it clear how their data will be used, stored, and protected. Even a brief note about anonymity at the beginning of the survey can go a long way in building trust.
Additional Resources
For further guidance on crafting unbiased survey questions, Kantar Profiles offers a range of resources:
- Check out our survey sample questions and templates
- Get additional guidance on how to choose the right question types
Conclusion
Crafting unbiased survey questions is both an art and a science—and it’s essential for collecting data that truly reflects what people think, feel, and do. From avoiding leading questions to balancing response scales and ensuring cultural inclusivity, every detail in your survey design contributes to the integrity of your insights.
Poorly designed questions can distort results and lead to misguided decisions. But when surveys are thoughtfully constructed, they become powerful tools for discovery—helping brands uncover meaningful truths, improve experiences, and make confident, data-driven decisions. By applying the principles and best practices outlined in this article, you can elevate the quality of your research and get closer to the people behind the data.
Want to learn more?
Navigating the complexities of survey design can be challenging. The Profiles team at Kantar offers customizable research services tailored to your specific needs. Our AI-driven anti-fraud technology ensures data integrity, and our global reach provides access to over 170 million consumers across 100 markets. We position ourselves as your strategic partner in achieving accurate insights.
Watch our 8-minute module: The Impact of Bias in Survey to explore factors that have the potential to prompt bias answers and what you can do to collect more reliable data. Or, get in touch with our experts that can provide you expert survey design assistance based on your specific research needs and objectives.
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