How to Avoid Biases in Surveys for Accurate Market Research

Selection bias occurs when survey respondents do not represent the entire customer base. For example, if you only survey customers who visit your physical store, you may not obtain an accurate representation of your entire customer base. To avoid this, use random sampling methods, such as online survey tools, to reach a broader audience and randomly select respondents from a pool of potential participants.

Suppose you run an online store that sells skincare products. You decide to conduct a survey to gather insights into your customer base. You send out a survey to your email list and receive 500 responses. However, 70% of your email list consists of women over the age of 50, and only 10% are men. In this scenario, you are likely to obtain biased results that do not accurately reflect your entire customer base.

2. Confirmation Bias:
Confirmation bias occurs when survey questions are designed to confirm preconceived notions or hypotheses. As an entrepreneur, you may want to confirm that your product or service is popular, but leading questions can lead to biased results. To avoid this, use neutral, open-ended questions that allow respondents to provide honest opinions without feeling pressured to confirm or deny a preconceived notion.

Suppose you are launching a new line of vegan snacks and want to conduct market research to determine customer preferences. You design a survey that asks questions like "How much do you love our new vegan snacks?" and "Would you recommend our snacks to your friends?". These questions are leading and may bias the responses towards positive answers, even if customers do not actually like the snacks.

3. Response Bias:
Response bias can occur when respondents provide answers that cater to social desirability or the researcher's expectations. As an entrepreneur, you may want to know what your customers think about your brand, but respondents may overstate their loyalty to appear supportive. To avoid this, ensure anonymity and use clear, unambiguous questions that make it easier for respondents to understand what is being asked.

Suppose you are conducting a survey to determine how frequently customers use your online fitness classes. You ask the question "How often do you use our online fitness classes per week?". The responses you receive may be biased because some respondents may overestimate or underestimate their usage to appear more or less active.

4. Order Bias:
Order bias occurs when the order of questions or responses in a survey influences the answers given. For example, if you ask customers to rate a particular feature of your product before asking about their overall satisfaction, they may be more likely to rate the feature positively, even if their overall satisfaction is low. To avoid this, reflect on the order of questions or responses and/or randomise it where appropriate to reduce the likelihood of bias.

Suppose you are conducting a survey to determine how satisfied customers are with your restaurant. You ask customers to rate the quality of the food, service, and ambiance before asking about their overall satisfaction. This order may bias the responses towards positive answers because customers may be more likely to rate individual components positively before considering their overall satisfaction.

Here are some dos and don'ts to help you avoid survey biases in your market research:

Do:

• Clearly define your research objectives and survey goals before designing the survey to ensure that questions are relevant and align with your business goals.
• Pre-test surveys with a small sample of respondents to identify and address potential biases before conducting the full survey.
• Use skip logic to direct respondents to questions that are relevant to them, rather than asking everyone the same questions.
• Keep survey questions short and straightforward to reduce respondent fatigue and increase completion rates.

Don't:

• Use leading questions that suggest a particular answer.
• Include complex or technical language that may be difficult for respondents to understand.
• Make assumptions about respondents based on demographic factors, such as age, gender, or ethnicity.
• Overuse scales, such as the Likert scale, which may not provide accurate insights into respondent opinions.

Incorporating these best practices can help ensure that your market research is effective and unbiased, ultimately leading to better business decisions. By avoiding biases in your market research, you can obtain accurate and reliable survey results that inform effective business decisions. Enrol in Creo's Market Research course to become more mindful of biases and take steps to avoid them. Learn how to gather insights that are truly representative of your customers and make data-driven decisions that benefit your business.