9 Common Survey Biases and How to Overcome Them

Survey bias can distort your data, and can pose a threat to your overall data quality and decision-making processes. It is possible to list such biases as the following, and then define how they should be overcome to reach credible results: We use this premise to analyze nine types of survey bias with practical techniques to navigate them successfully.

1. Selection Bias

Definition: Arises from failure to survey a representable sample among the population under study. For instance, someone may decide to conduct a customer satisfaction survey among only loyal customers while other factors such as new customers or dissatisfied customers will not have been considered.

• Stratified random sampling should be adopted since the population is divided into various subgroups, and the sample should reflect the composition of the population more closely.

• Relax your targeting criteria for your survey and make it possible to offer several means of dissemination like online email, social media, and face-to-face among others.

• It is also necessary to check the response rates according to demographic characteristics so that they do not deviate in one direction.

2. Response Bias:

Definition: Occurs when the respondent votes in a manner he or she thinks is right or correct according to what is required of him or her by society. This frequently distorts responses in the surveys of a topic that is sensitive such as income or health practices.

• Give surety to ensure that there is no increased pressure on the respondents.

• Ask sensitive questions indirectly (for example “What do people you know do to move around?”

3. Question Order Bias:

Definition: Preceding questions often may introduce a certain bias or precondition to the answers to the questions that follow. For instance, it is possible to slightly bias the results if a question starts with a topic like satisfaction with a certain aspect of the product’s offering or overall satisfaction.

• Listing or countering questions for respondents should be done in a rotary or random manner.

• For distinction, general and specific questions must be separated with neutral transitions.

• Now, pre-hypothesis pilot surveys should be conducted to determine if question order affects the responses obtained.

4. Leading Question Bias

Definition: This is established if the questions posed are worded in a manner that is directed toward a regular choice. For example, “How much do you love our product?” imposed a positive attitude towards the product.

• To reduce bias, prefer neutral words and will not be able to influence the respondent’s answers.

• Give equal opportunities for balance to answers where positive and negative responses will be assumed.

• Get someone other than you to go through the survey so that you can eliminate any leading questions by mistake.

5. Acquiescence Bias:

Definition: Several respondents would state yes simply because they cannot state any when answering yes/no or agree/disagree questions.

• Make certain you respond to both positively and negatively constructed statements.

• To be more precise, use a Likert scale for example “I strongly disagree’ I disagree,” “I agree,” "I strongly agree.”

• Remind respondents that their answers should be as truthful and as much a result of thinking as possible.

6. Non-Response Bias:

Definition: Occur when some people are less willing or unable to complete the survey questionnaires hence making the data set deficient or imbalanced. For instance, millennials may not be willing to complete long surveys.

• Surveys must also be short and well-presented.

• Use emails or notifications to remind participants to be more active.

• For the broader population, one should offer cash rewards, vouchers, or some other added incentives.

7. Cultural Bias:

Definition: This is a bias that results from the failure to consider multiculturalism in survey questions or answers’ interpretation. For example, non-fluent speakers are likely going to be challenged by idiomatic expressions.

• Ensure that the language used in a survey is understandable, that the expressions are comprehensible as well as the examples are given.

• Focus group discussion in areas of interest to ascertain cultural suitability.

• Survey with local professionals or translators to help you translate it properly in a local environment.

8. Recall Bias:

Definition: Uses respondent memory which means that the answers obtained may not be comprehensive or accurate. For instance, the request to customers to remember how a product they bought in the course of a particular year looks like.

• Do not ask too many recall questions in a single sequence; better still, limit them to events or experiences within the same day.

• Examples of cues include product images or time-based cues to help the users remember what it is they are supposed to provide.

• Do not ask questions that are too personal and try to avoid questions that are text specific.

9. Sponsorship Bias:

Definition: It happens when respondents design their responses about the identity of the sponsor of the survey. For instance, the employees will give excessively positive responses to a survey commissioned by the company out of fear of reprisal.

• To avoid a biased perception, use third-party methods of survey instruments.

• Make it understood that all comments are important and will be used in helping to shape organizational products/services.

• Make surveys anonymous and even where it cannot be done stress the importance of giving honest responses.

More Suggestions to minimize survey bias:

Pre-Test Your Surveys: Conduct test surveys on a small population of people to determine and excommunicate all probable motives of prejudice.

Use Clear and Simple Language: To make sure that no respondent is in a position to have a different meaning of the questions being asked, do not include any product peculiar terms, phrases, or unclear terms this will ensure that all the respondents are answering from a similar understanding.

Regularly Update Your Surveys: To avoid your surveys from becoming stale, check them regularly in a bid to update them on current trends or what clients are saying.

Conclusion:

Bias arises in surveys as an inherent problem but it is possible to reduce its extent and ensure that your survey information is reliable. If you want to conduct high-quality surveys, there is a tool that you may consider using, called Quizify. Thanks to its simple navigation and rich functionality, Quizify allows the creation of highly stimulating and sufficiently impartial surveys for your target audience. Head over to Quizify.io now and turn your surveys up a notch!