User surveys are a valuable tool for gathering feedback and insights from your target audience. However, designing a user survey that is clear, unbiased, and relevant can be challenging. In this article, you will learn some best practices for writing user survey questions that avoid common pitfalls and help you get the most out of your data.
Before you start writing your user survey questions, you need to have a clear idea of what you want to achieve and who you want to reach. What are the main objectives of your survey? What are the key questions you want to answer? Who are your ideal respondents and how will you recruit them? Having a clear and specific goal and audience will help you craft questions that are relevant, focused, and aligned with your research purpose.
In my experience avoiding bias and leading questions is of utmost importance. There are several ways to do this but I find some of the most effective to be the following: 1.) Include a "Other" or "Prefer not to Answer" option 2.) Make sure your demographic questions are at the end of your survey 3.) Create a plan of who to target before conducting your survey..have a sample in mind and a target audience pool to draw from. 4.) Avoid questions that only require users to submit a yes or no answer. 5.) Make sure questions are clear and ask just one thing at a time. Avoid a question asking the user to consider multiple questions within just one question. 6.) Avoid assuming something or demanding something for someone answering.
As I teach in UI/UX courses avoiding biases and leading questions in user survey design, and awareness of influencing factors is crucial. Biases can affect users as well as designers themselves. *Users may show the Hawthorne Effect, Confirmation Bias, Halo Effect, or Anchor Bias. *Designers could exhibit Expectancy, Observer, Sampling, or Interpretation Bias. To ensure comprehensive insights, combine qualitative data (interviews, usability tests) and quantitative data (surveys, A/B tests). This balanced approach fosters unbiased research, leading to user-centric design solutions.
One idea per question is a golden rule. Having optional answer with open text box for participant to enter her own answer is also powerful, however those kind of answers are hard to quantify, therefore this approach is unpopular among designers.
One of the most common sources of bias and confusion in user survey questions is the use of complex, ambiguous, or loaded language. To avoid this, you should use simple and straightforward words that are easy to understand and interpret. Avoid jargon, acronyms, technical terms, or slang that might confuse or alienate your respondents. Also, avoid using words that imply a positive or negative judgment, such as "good", "bad", "easy", "hard", or "important". Instead, use neutral and objective terms that allow your respondents to express their own opinions and experiences.
In my experience, I have noticed the significance of nonverbal communication both from the designers' and the user's side. Designers must focus on nonverbal communication during testing. Being welcoming yet neutral is vital. A warm demeanor encourages honest responses while remaining impartial ensures unbiased data. Maintaining a comfortable atmosphere empowers respondents to express authentic opinions and experiences, enriching the survey's validity and yielding valuable insights.
This is where LLMs could help, with a prompt like "Please offer me 10 neutral alternatives for the word..." or even nice try is "Please replace a scale from 0 to 5 with neutral words that depict how hard is to use a product"
Another way to avoid bias and leading questions in your user survey design is to avoid asking questions that suggest a desired answer or that combine two or more questions in one. Leading questions are questions that influence or persuade the respondent to answer in a certain way, such as "How much do you love our product?" or "Don't you think our service is better than the competitors?". Double-barreled questions are questions that ask about two or more different topics or aspects in one, such as "How satisfied are you with the quality and price of our product?". Both types of questions can skew your results and make it hard to analyze your data. Instead, ask questions that are open-ended, unbiased, and focused on one topic or aspect at a time.
Crafting neutral and specific questions is essential to collecting valuable user insights. To avoid leading questions, keep language neutral and let respondents freely express their opinions. For example, instead of "How much do you love our product?", use "How would you describe your experience with our product?". To avoid double-barreled questions, keep each question focused on a single topic. Instead of asking "Are you satisfied with the quality and price of our product?", split it into two questions like "How would you rate the quality of our product?" and "How would you rate the value for money of our product?". By keeping questions neutral and focused, we can ensure the validity of our data and the reliability of our insights.
Another important aspect of writing user survey questions is choosing the right type and format of response options. Depending on the type of question, you might use a rating scale, a multiple-choice list, a yes/no option, or a free-text field. Whatever option you choose, make sure it is appropriate for the question and the data you want to collect. For example, if you want to measure the level of satisfaction or agreement of your respondents, you might use a Likert scale, such as "Strongly agree, Agree, Neutral, Disagree, Strongly disagree". If you want to offer a range of choices, make sure they are mutually exclusive, exhaustive, and consistent. For example, if you want to ask about the frequency of use of your product, you might use options such as "Daily, Weekly, Monthly, Rarely, Never". Also, avoid using "Other" or "None of the above" options, as they can reduce the validity and reliability of your data.
1) The scale should make sense when associated with a question. When Likert-type scales are used to gather responses, the lower end of the scale usually refers to less agreement, frequency, importance, likelihood, or quality. 2) Anchor labels show the extreme ends of the scale, but should still have an associated value (although it's best to have labels and values for every level of the scale to avoid confusion). 3) A label for the center of the scale should be provided because the middle may be assumed to be a neutral response. 4) The scales should be consistent throughout the survey. If you're using a 10-point scale, don't make the next question 5-point. This makes answering questions more challenging for the respondents
Finally, the best way to avoid bias and leading questions in your user survey design is to test and refine your questions before you launch your survey. Testing your questions with a small sample of your target audience can help you identify and fix any issues or problems that might affect the quality of your data. You can also use online tools or platforms that can help you check the readability, clarity, and validity of your questions. By testing and refining your questions, you can ensure that your user survey is effective, accurate, and useful for your research goals.