What Is Response Bias And How To Avoid It? A Must Read!

Surveys play a massive part in every organization’s growth. How? By getting data without response bias that generate insights worth taking action on. These actions, taken correctly, ultimately bring sustained growth to a company.

So to make sure these surveys yield the needed data, your team spends countless hours preparing a template, questions, and flow. 

What could go wrong now, right? Well, everything. 

If you don't use the right set of questions or ask them the wrong way - it can lead to bias in response. Or simply - response bias. 

There are different types of response biases that can ruin your survey. This is why we are writing this blog. To inform you, educate you, and help you avoid them.

If you wanna know about the blog in no time, here's a quick summary of the response bias and how to avoid them.

Survey Bias: A Quick Summary

The following are the types of survey bias, examples and how they can be avoided in a nutshell. 

What Is Response Bias?

According to the Encyclopedia of Survey Research Methods, response bias means:

“Response bias is a general term that refers to conditions or factors that occur during the process of responding to surveys, affecting how responses are provided. Such circumstances lead to a nonrandom deviation of the answers from their true value.”

Or in simple terms, if your survey has any factor that can influence the survey participants in how they respond, that is response bias.

Here's an example of how response bias works. 

Q. How often do you smoke in a week? 

• Frequently
• Often
• Once a week
• Once a month

As you can see, the questions assume that every respondent is a smoker and didn't provide an option for a non-smoker. Thus, the response will be biased as well.  

9 Types Of Response Bias And How To Avoid Them

You know what response bias is, its effect on surveys, and ultimately your business’ growth. But what are the different respondent biases you’ll come across, and how best to avoid them?

That’s what we discuss here with these 9 response biases, starting with;

1. Desirability Bias

The desirability or social desirability bias in surveys comes when respondents know their honest opinions won’t necessarily be appreciated or accepted for sensitive questions. 

So, rather than choosing an option aligning with their thoughts, they go with the socially desirable response, over-supporting ‘good behavior’.

Here’s a great example – “On a scale of 1 to 10, how much do you support the concept of net zero carbon?” Or “Do you find everyday alcohol consumption acceptable?”

For these 2 questions, respondents would mostly side with the socially responsible and accepted responses, even when they think differently. 

And for questions like “Should you donate a part of your income to charity every month”, you’ll see positive responses, even when those taking the survey don’t donate or haven’t started yet.

How to avoid desirability bias?

Start by making the survey anonymous for all respondents. You’ll straightaway notice more honesty in answers.

Secondly, ask indirect questions where respondents don’t feel like being judged. Example: Instead of asking “How much time do you waste at the workplace every day?”, ask, “How much time do you think people waste in the office every day?”.

Try framing questions with neutral wording. Example: Instead of asking “What do you dislike about the office culture?”, ask, “What changes would you love to see in the office culture?”.

2. Demand Bias

This type of response bias originates when respondents are influenced simply because they’re a part of the survey. They change behaviors and opinions as they’re a part of a study or survey.

There are several reasons why people do that. The most common is when respondents can see the live poll status, as they’ll change answers, to either positively or negatively affect the overall result. 

If people really like a brand, they’ll support its ideas without giving much thought to theirs in the survey. That’s another way demand bias is generated. 

Lastly, when a respondent personally knows the survey taker or researcher, he/she will provide support by choosing favorable options.

How to avoid demand bias?

Start by choosing survey groups that are appropriate for a particular survey, not the one where you know most people.

To get absolutely honest opinions, write emotion-free questions. 

Example: Instead of starting questions like “As a long-term customer…”, begin directly. Talk about how grateful you are to your long-term customers in the introduction, not in the questions.

Also, ask them for their ideas on a new product, website design, etc. Don’t give them yours or they’ll not think much and side with that only.

3. Acquiescence & Dissent Bias

Acquiescence and dissent bias is about survey takers being either extremely positive or extremely negative.

In this state, they’re not thinking about giving an honest, thoughtful answer, but just choosing to be positive or negative with their replies.

Acquiescence bias is an extreme form of social desirability. But here, respondents simply agree with the research and question statements, rather than responding in a ‘socially acceptable’ way. So, whatever the question, the reply will be a ‘yes’ if that’s an option.

The reason for acquiescence bias stems from respondents’ perceptions of how they think the survey organizer wants them to respond. And then some respondents only choose positive options because they worry about their online image. 

While it’s good to get a lot of ‘yes’ answers in a survey, they don’t help much when you’re looking to collect and analyze genuine data.

The exact opposite of acquiescence bias is dissent bias. Here, as the name suggests, respondents are always disagreeing with the statements they’re presented with, rather than giving true opinions. The most likely reason for that is to make a mockery of the survey and finish it in no time!

How to avoid acquiescence and dissent bias?

Completely avoid loading and leading questions that prompt survey takers to give a predetermined response. Example: “How great do you think our new product update is?” – Don’t use a question like this.

Another way to avoid such bias is to go beyond the typical ‘yes’ or ‘no’ questions. Try including a rating scale, open-ended questions, and multiple-choice questions.

Try not to use extremely positive or negative answer options. Let people think when they see your options.

4. Non-response Bias

A non-response bias occurs when respondents skip certain questions or the entire survey. A lack of anonymity and a long survey are the prime reasons behind it.

For example, your employees will always be reluctant to answer a non-anonymous employee engagement survey. 

In the case of customer surveys too, if you’re collecting feedback after a long time of your customer’s product purchase, they’re unable to give a reliable response and choose to skip the survey entirely.

How to avoid non-response bias?

Firstly, keep your survey short and simple. Don’t ask all the questions in just a single survey.

Send an anonymity-enabled feedback survey at every customer and employee touchpoint to get reliable data right away.

Go omnichannel with your survey distribution. Don’t just send it over an email. Use all the social media platforms and also embed the survey on your website.

5. Extreme & Neutral Response Bias

When using Likert scale questions in a survey, extreme and neutral response bias creeps in easily if you’re not aware. In this, the respondents either choose the extreme options – ‘least likely’ or ‘most likely’, or stick to the neutral one.

Extreme bias happens mainly when strong words are used in a question. 

For example, consider the question: “How justified it is to give a rape accused a chance of trial?”.

Here, the respondent will mostly side with the ‘completely justified’ or ‘completely unjustified’ options.  ‍

Neutral response bias is a result of respondents not understanding a survey or wanting to finish it quickly to get some sort of reward or coupon. 

Whatever question you ask, these respondents will always choose the neutral or middle option. And that is a sheer waste of time and resources, as this data will lead nowhere.

How to avoid extreme and neutral response bias?‍

Form questions with positive or neutral wording. This will immediately invoke more thinking among survey takers.

Keep the entire survey simple and short, with jargon-free, one-liner questions and options.

Double-barreled questions are confusing and often lead to neutral response bias. So, try not to use it. 

6. Question & Answer Order Bias

The next type of response bias is the question-and-answer order bias. Talking about the question order bias first, as the name suggests, it is a situation where survey respondents give a biased answer because of the type of preceding question they answered. 

Basically, survey takers respond in a specific way as a pattern is developed from the preceding questions.

Here’s an example to gain more clarity;

Q1: Did you like the [product feature] of [product name]?

Q2: Are you comfortable with [product name]’s user interface?

Q3: Overall, how would you rate our [product name] on a 1 to 5 scale?

See the sequence of questions here. It starts from a specific feature of a product to its overall performance. If respondents gave a high rating to the first 2 questions, they’d be reluctant to give a lower rating to the product. And that’s how question order bias is created.

The answer order bias is created from respondents’ tendency to select the first or the last option in a multiple-choice question. The intent behind choosing the first answer option is that it is the first option read by the surveyees, which they take to be true. 

While choosing the last option is because of the recency effect, i.e., people remember the most recent option clearly so they choose that only.

How to avoid question-and-answer order bias?

Always start with the overall rating question before moving to ones on specific product/service feedback.

Group questions in the same category as one single question, or keep them entirely separate in a survey. Also, try minimizing options in the multiple choice questions, but provide the “Prefer not to say” options to make the survey inclusive.

7. Voluntary Response Bias

A voluntary response bias occurs when your sample is made of people who have volunteered to participate in the survey. 

While this isn’t always bad for your survey or data collection, it sometimes results in overreporting on one aspect, as you’re more likely to have a sample with similar opinions, which doesn’t bring out the intended quality of data.

How to avoid voluntary response bias?

• Try to target an audience for your survey. It shouldn’t be the other way around.
• If you’re getting volunteers for a survey, make sure their opinions aren’t similar. The quality of data will be much better.

8. Courtesy Bias

Courtesy Bias arises when people respond to surveys or questions in a way they believe will please the interviewer or avoid offending them. 

This bias can lead to dishonest or skewed answers because the respondent is more focused on being polite or agreeable than on providing truthful responses.

For instance, in a customer feedback interview at a restaurant, a diner might praise the service and ambiance even if they found it lacking, simply because they don’t want to be rude to the staff conducting the survey. 

Similarly, in an employee satisfaction survey conducted in person, an employee might overstate their satisfaction to avoid any potential conflict with management or to appear as a cooperative team member.

How to avoid courtesy bias?

To mitigate Courtesy Bias, anonymity should be emphasized in surveys. Assure respondents that their honest feedback, whether positive or negative, is crucial and will be kept confidential.

In face-to-face interviews, the interviewer should be trained to maintain a neutral tone and body language, providing a non-judgmental space for respondents to share their true thoughts.

Additionally, using online or written surveys where respondents do not have to face an interviewer can also help reduce this bias.

9. Question Order Bias

Question Order Bias refers to the influence that the sequencing of questions can have on how respondents answer later questions in a survey. 

The initial questions can set a tone or context that unintentionally sways the responses to subsequent questions, leading to biased or inaccurate answers.

Consider a public opinion survey that starts with several questions highlighting economic challenges and then asks about overall satisfaction with government performance. 

The negative framing of the initial questions may lead respondents to give a more critical assessment of the government than they might have if the questions had been ordered differently.

Another example is a product feedback survey that begins by asking about the most positive features of a product, which could lead to more favorable responses in later questions about overall product satisfaction.

How to avoid question order bias?

To combat Question Order Bias, it’s important to carefully consider the order of questions. Randomizing the sequence of questions for each respondent can help reduce this bias. Using software that allows for question randomization can be very effective.

Additionally, separating questions into distinct sections based on topic can help prevent earlier questions from influencing responses to later ones. 

For complex surveys, conducting multiple smaller surveys focusing on specific topics rather than one long survey can also be beneficial.

Why Resolving Response Bias Is Important? 

Data Inaccuracy 

When respondents choose options to develop a perceived notion about themselves, the gathered data is highly inaccurate and doesn’t represent the true opinions of the target market. This survey data is not going to help a company achieve its goals.

Poor Strategies and Dissatisfaction

Often, companies ignore or miss out on these biases and make crucial business decisions based on the collected survey data. The results are poor strategies and investments, along with sheer dissatisfaction. 

The decision-makers cut down on survey campaigns and market research, which eventually hurts their growth prospects even more.

Low ROI

Poor survey insights guarantee poor product performance, resulting in low return on investment for promising ideas and innovation. Not many organizations handle such setbacks well.

More Time, Money, and Resources 

Surveys full of response bias are repeated to test the data again, which takes more time, more money, and more resources. Not an ideal scenario for any company.

Bias Is Not Always Bad!

Yes, just because a survey has bias doesn’t mean it’s bad. If you have a clear idea of how these biases are impacting the overall data quality, it’s fine. Because let’s be honest, eliminating all bias from a survey is not in anyone’s hands.

Biases are also useful in categorizing your target market based on demographics, income level, interests, and more. So ultimately, biases lead to better data collection if you use them correctly.

Just don’t let it run all over your survey; everything will be fine. 

To know and understand more about how to tackle survey response biases, and how to conduct winning surveys, our team, at SurveySparrow, is here 24/7. Hit us up and let’s start now. Sign up today!