How to reduce question order bias?

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How to prevent question order bias in surveys regression analysis
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Gathering consumers’ opinions is one of the best ways for marketers to gain insight into customers’ perspective. Creating a survey might seem simple. But did you realize that the question order can significantly impact the results?

Question order bias occurs when the answers to earlier questions impact those of the follow-up questions. In this article, we will discuss how this bias can impact survey results and how to prevent them. 

What is a question order bias?

Order bias is also known as “order effects bias,” is a sort of response bias in which respondents may reply to questions differently depending on the order in which the questions are presented in a survey or interview.

This happens because respondents frequently want to give answers that are consistent with those they have already given. Respondents in this instance were probably trying to follow the fairness standard.

There are numerous additional reasons why question order could affect responses. Because of this, it’s crucial to consider it when creating surveys.

In the next section we would discuss some examples of order bias to understand it precisely.

Examples of question order bias in surveys

Examples of question order bias in surveys 

Here are the 4 basic examples of order  bias in a questionnaire item;

1. Leading questions

Leading questions make it very clear that there is a “right” response that the question is guiding. This  makes them the easiest examples of order bias to identify. Since the respondent was never given the chance to provide an honest response in the first place, this will always produce incorrect information.

Leading question examples

1. How wonderful was your interaction with our customer service staff?

You can see that this question is constructed so that there is no option for a different response because you have already presumptively stated that you believed the customer service team was outstanding. The customer is now required to rank the support staff on a scale of “awesome” to “outstanding.”

2. Would you be concerned if we stopped producing this range of products?

Instead of making assumptions like the first two questions, this example uses emotional language to guide a customer. The use of emotive language implies to the respondent that they should be concerned.

2. Ambiguous or vague questions

Many businesses may unknowingly become victims of this kind of question. These questions may seem sincere and innocent enough on the surface, but due to their ambiguity, they may end up confounding customers and leading to negative responses and could create question order bias in a survey.

Examples of ambiguous survey questions

1. How do we stack up against our rivals?

For instance, this question is just too general. Perhaps your customers haven’t used the goods made by your competitors, so they can’t comment.

Alternatively, what if your customers decide to start looking at your rivals since they have never considered it before? You also failed to provide a standard against which to compare; do you mean your product? Customer service caliber? Price? You’re giving customers complete freedom of choice.

2. Have you made any purchases in the previous three months? 

This should be rather evident as the majority of consumers have purchased within the last week, much alone three. However, where did they buy it? What did they purchase? Why is it relevant to the survey, exactly? How were they paid?

You can receive a variety of responses from survey participants by asking unclear questions.

How to prevent question order bias in surveys regression analysis

3. Double-barreled queries

These questions typically ask the customer to express an opinion on two subjects, which are typically unrelated, yet only allow for one response.

This can be another instance of businesses accidentally asking the same questions again to obtain additional information.

Examples of double-barreled questions in surveys

1. “How pleased are you with our aftercare and customer service?”

Although these subjects appear to be connected at first appearance, they are two entirely unrelated subjects.

Despite receiving exceptional customer service, the customer thought poorly of their aftercare package. They are unable to distinguish between the two and offer two opinions because of the nature of the question.

2. Would you prefer a more affordable and value-oriented version of our product?

Similar to the last example, they are two distinct topics. To various people, “value for money” can signify different things.

While some may view it as a synonym for “cheap,” others will anticipate the value to signify a high price but a higher-quality good. Once more, you’ll be skewing your responses depending on other people’s impartial readings of the sentence.

4. Absolute questions

By requiring respondents to give an absolute categorical response when they may not have one, these questions can sway their decisions.

They employ terms like

  • Never
  • Always
  • All

In essence, you want complete certainty from the customer.

Examples of a biased absolute question

1. Do you consistently use product X for cleaning purposes?

The issue with this is that it won’t work.

It will be extremely unlikely for someone to use your product 100 percent of the time, which will harm your survey results.

2. Please explain why you have never bought our goods.

This question comes across as harsh and overbearing, isolating the reply by singling them out as not purchasing your goods. Your customer has very little room to move because of this.

5 ways to prevent question order bias in surveys

Ordering bias could have a significant impact on the data’s insight and quality, which will affect the marketing choices you make. Here are five crucial pointers to help you reduce order bias in your upcoming survey.

1. Test your surveys in advance. 

Ask a small group of friends or coworkers to take the survey and offer feedback regarding the question sequence or anything else that might seem off or confusing. This is a chance to identify survey issues, such as the consequences of question order.

2. Randomize the order of unrelated questions. 

Bias is decreased by randomly ordering unrelated questions. You might want to shuffle questions like “what is your favorite sport?” and “what is your favorite dessert,” for instance. 

Randomization is not a perfect solution, but it can assist in lessening question order bias caused by question order effects. Certain questions, such as branched questions, must be posed in a certain sequence to be effective, and other questions must be answered in a certain order to make sense. It is preferable to avoid answering questions of this nature.

If you conduct a survey to learn more about your target market, think about randomizing these three crucial factors:

  • Randomization of questions

It’s best to change the order of the subjects when conducting concept testing.

For instance, you might compare two advertisements and ask respondents what they think about them.

The answers of respondents will become biased if ad A is always placed higher on the list in every question since they might value it more.

However, by often alternating between ads A and B, question order bias can be reduced and a wider range of responses is more likely to be observed. This is because the initial advertisement displayed has the potential to affect respondents’ opinions and responses to the subsequent questions.

  • Randomization of pages

Consider attempting to assess the potency of various advertisement videos. Spreading out the videos on various pages is preferable to placing them all on one page.

Consequently, every video will have its page. It not only prevents prejudice, but you may also add follow-up open-ended questions to gather more thorough data.

  • Randomization in blocks

Keeping with the prior idea, think about using block randomization if a large portion of your survey pages contains a video or image.

You will have several blocks from your pages because each page is a block. You can recognize the pages using block randomization, or you can distribute one random block to each respondent.

3. Group questions that are related

Grouping your survey questions will help reduce survey order bias.

It refers to questions where respondents have the option of selecting more than one response. Select, for instance, one of our top goods (pick up three).

According to research, question grouping increases dependability and makes guessing at hypotheses easier. Most importantly, question grouping can show a more accurate representation of the input from respondents.

4. Making survey branching optional.

By designing a branching survey, you can eliminate the importance of question order.

It enables you to establish separate parts throughout your survey to avoid priming and enables your respondents to skip certain questions that are irrelevant to them.

Asking a prospect to list the top three variables influencing their purchase decision, can help you pinpoint their specific pain concerns.

After that, you can guide them to the parts or pages that only show questions that are pertinent to those variables based on the factors they listed.

This includes a useful opt-out option for responders to filter out questions that are irrelevant or that they do not want to answer.

5. Begin broadly and go specific

Your survey should begin with general questions before moving on to more specific ones.  Since it warms up your respondents and increases their participation in the survey, it also lowers the likelihood of question framing.

Here is an illustration of the opposite situation to show why.

You’ll see that the first few questions in this survey are more detailed. They will decide how satisfied they are with the product overall based on their interactions with the branding and software.

Because of this, you should constantly format your questions so that they move from general to specific. The secret is to ask more intimate questions near the end of the survey rather than at the beginning.

 

Conclusion

When designing a survey, the sequence of the questions is important. A respondent might be persuaded to believe in a certain way based on how the questions are structured.

Even though we cannot rely on respondents to provide completely accurate answers, it is our duty as the survey’s designer to remove any potential for ordering bias.

Make sure you follow these three recommendations to prevent question order bias in your survey from creating the ideal survey that generates useful replies to assist you in making intelligent marketing decisions.

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