Leading questions are questions that suggest a desired answer or influence the respondent's opinion. They can skew the results of your user interviews and make your content creation less effective. In this article, you will learn how to avoid biased results from leading questions by following some simple tips and best practices.
The first step to avoid biased results from leading questions is to identify them. Leading questions often use words or phrases that imply a judgment, assumption, or preference, such as "don't you think", "wouldn't you agree", or "obviously". They can also use loaded terms that evoke emotional reactions, such as "waste", "harm", or "improve". To spot leading questions, try to reverse the wording and see if it changes the meaning or tone of the question. For example, "How do you like our new feature?" is a leading question that implies a positive response, while "How do you feel about our new feature?" is a neutral question that allows for any feedback.
Here's a general rule of thumb: If it feels like it's trying to make you say something specific, it's probably a leading question.
The second step to avoid biased results from leading questions is to use open-ended questions. Open-ended questions are questions that invite the respondent to elaborate on their thoughts, feelings, or experiences, without limiting their options or influencing their answers. They usually start with "what", "how", "why", or "tell me". They can help you gain more insights and understanding of your user's needs, preferences, and pain points. For example, instead of asking "Do you find our app easy to use?", which is a closed-ended question that only requires a yes or no answer, you can ask "What are some challenges you face when using our app?", which is an open-ended question that encourages the user to share their problems and frustrations.
Open-ended questions can always add perspectives that enhance the usability of your product. To incorporate maximum corner cases, frame your questions that allows the respondents to open up and communicate freely.
The third step to avoid biased results from leading questions is to avoid yes-no questions. Yes-no questions are questions that only have two possible answers: yes or no. They can limit the depth and quality of your user feedback and make your content creation less relevant and engaging. They can also introduce bias by making the user agree or disagree with a statement, rather than expressing their own opinion. For example, asking "Do you think our app is better than our competitors?" is a yes-no question that forces the user to compare your app with others, rather than focusing on their own needs and expectations. A better way to ask this question is "What are some features that you like or dislike about our app and why?", which is an open-ended question that allows the user to provide more details and reasons.
Questions starting with "how," "what," or "why" naturally prompt respondents to provide detailed answers. For instance, replace "Is the product useful?" with "Why do you find the product useful?"
The fourth step to avoid biased results from leading questions is to use neutral language. Neutral language is language that does not express or imply any opinion, preference, or judgment, but rather states facts or observations. It can help you reduce the influence of your own biases and assumptions on your user feedback and make your content creation more objective and accurate. To use neutral language, avoid words or phrases that indicate your own perspective, such as "I think", "we believe", or "our goal". Also, avoid words or phrases that suggest a certain outcome or expectation, such as "should", "must", or "need". For example, instead of asking "How can we make our app more user-friendly?", which is a leading question that implies that your app is not user-friendly enough, you can ask "How do you use our app and what are some areas for improvement?", which is a neutral question that reflects your user's experience and needs.
The fifth step to avoid biased results from leading questions is to test your questions. Testing your questions is a way to check if your questions are clear, relevant, and unbiased, and if they elicit the feedback that you are looking for. You can test your questions by asking them to yourself, a colleague, or a friend, and see if they can answer them easily and honestly, without feeling confused, pressured, or influenced. You can also test your questions by conducting a pilot interview with a small sample of your target users, and see if they provide the insights and information that you need for your content creation. You can then revise your questions based on the feedback and results that you get from your testing.
When testing your questions, ask participants to "think aloud" as they answer questions. This provides insight into their thought process and reveals any confusion or misunderstandings in your questions.
The sixth and final step to avoid biased results from leading questions is to analyze your results. Analyzing your results is a way to interpret and evaluate the feedback that you get from your user interviews and use it to inform your content creation. To analyze your results, you need to organize, summarize, and synthesize the data that you collect from your user interviews, and look for patterns, themes, and insights that can help you understand your user's needs, preferences, and pain points. You also need to be aware of any potential sources of bias or error that may affect your results, such as sampling bias, response bias, or confirmation bias, and try to minimize or correct them. You can then use your results to create content that is relevant, engaging, and valuable for your user.