Businesses create surveys to understand customer feedback, conduct market research, do demographic analysis, and a lot more. The results of these surveys are extremely critical in several areas of business. Such as improvement in products, and services, launching new ones, understanding customer profiles, doing detailed demographic analysis, etc. 

If the survey responses are used to make critical business decisions, then the quality of the decisions would depend on the quality of the responses gathered. Response biases are the inaccuracies or inconsistencies that get into the customer responses due to several reasons. In simple terms, the customer didn’t actually mean what she or he has responded. This could be because of survey design, question design, wrong customer sample, and many others. Biases in the survey response lead to lower-quality response data. Hence it is important to understand some of the key biases and try to eliminate as many as we can.

In this post, we will dive deep into “Acquiescence bias”. This difficult-sounding bias is also known as Yes bias, or Confirmation bias.

What is Acquiescence Bias?

Acquiescence bias is where a user agrees to a statement without actually truly meaning or believing the same. It’s also called “Yes Bias” or Confirmation Bias. Here a user who takes a survey chooses an option that agrees with the survey statement or gives mere confirmation even if she doesn’t totally believe it’s true. So it becomes a biased opinion as opposed to an independent unbiased response. 

Here are a few example survey questions that may lead to this bias.
– How much did you like our feature <X>? 
– How much do you agree with the statement – I consume healthy meals almost every day. [Options: Fully Agree, Agree, Disagree]

The above questions are also called “leading questions”, where the user very likely chooses the option which agrees with the question statement.

Acquiescence Bias Question Example
Acquiescence Bias Question Example
Acquiescence Bias Example
Acquiescence Bias Example

Acquiescence bias can also arise because of the faulty question options. For example, consider a question like – I properly plan and organize my day, with the option as Yes/No. The survey participants will most likely provide a positive response to this question.

This bias is overwhelmingly caused by leading or unclear questions followed by a limited number of options such as True/False, Agree/Disagree, Yes/No, etc. The other key reasons are long or poorly worded questions, vague questions, lengthy surveys, choice of demographic, and so on. We will explore them in more detail in the following section.

If not understood and rectified, this will lead to inaccurate response data. If a business needs to use this data for critical decision-making, this bias will lead to suboptimal outcomes.

Causes for Acquiescence Bias

Now that we have identified and understood this bias, let’s dive deep into what causes it. Below are some of the key reasons for the same.

1. Question Design - Leading questions

As we had explored earlier, leading questions are one of the key reasons why this bias creeps into your survey results. Leading questions are the ones where the surveyor asks the participant questions that lead to or favor a particular option more than the others. For example: 
– How much do you agree with this statement – Our product packaging is really amazing.
– The payment feature of our product is very smooth, do you agree with the statement?

These questions can potentially “guide” the participant to choose a more favorable option.

2. Options design - Limited number of options

Designing the options for a survey question can potentially introduce this bias. For example, consider a question –
Our product packaging is amazing. With 2 options -Yes, No. 
With such a leading question and very limited answer option, the user most likely is going to choose a positive option.

acquiescence bias options example Providing a limited number of options can lead to this bias

3. Question Design - unclear or poorly worded questions

Unless the question is clearly worded, it can confuse a user. In such a situation, she may choose the positive option. For most users, selecting a favorable option is highly likely if they don’t fully understand the question. Also, the survey creator may design the wording in such a way that it seems eager to elicit positive feedback as opposed to trying to get a more objective view from the user.

4. Cultural implications and social influence

Users in some cultures are more likely to offer a positive response unless their experience or feedback has been highly negative. They may do it out of politeness, but for the brand, it may bias the responses and paint a more positive picture. 

Similarly, social influences and the positive self-image of the participant may result in more positive responses. For example: questions like –
You should use your car less. Yes/No
I organize my calendar well for the day. Yes/No

These kinds of questions are most likely to fetch positive responses, though the participant’s action would suggest otherwise.
Question order is also important here. Let’s say a user has answered a question like this – I am methodical in my approach to work, True/False. If the user has answered this question positively and then if you pose a question like – I organize my calendar well for the day, there is an extremely high chance that the user answers the same positively as well. This is a result of our trying to seem consistent throughout.

5. Lengthy survey and non motivation

If the questionnaire is long or the user is not motivated to take the survey, they are very likely to try and finish the survey quickly by providing positive responses. As we have discussed earlier, if the user doesn’t understand the question properly or is eager to be done with the survey, then it’s very common to go for positive responses.

6. Non-anonymous surveys, especially non-anonymous employee surveys

This effect can be very prominent where the respondents are non-anonymous and there is a fear of action or the fear of being judged based on their feedback. If a participant can be identified and a response can be tied back to them, it may seem safe to agree to a more social viewpoint.

This doesn’t impact customer experience surveys that much as generally for a brand, the customers are in a position of power. But in the case of employee surveys, unless there is an assurance of anonymity, the responses can very likely contain this bias. Especially if they believe that the response can be tied back to them and perception can be built based on their responses.

7. Surveyor superiority and In-person Surveys

The real or perceived superiority of the surveyor impacts the outcome of the survey as well. If the respondents feel that the surveyor is superior, they are most likely to provide a positive view. This effect gets even more prominent in the case of in-person surveys or interviews. When the users are called onsite and interviewed, it’s important to keep in mind that out of politeness and gratitude, the users may opt for more positive responses than they would otherwise provide.

7 ways to prevent acquiescence bias in surveys

Now that we have seen how acquiescence bias is caused in the surveys, in this section we will explore how to prevent them. We will also explore whether the bias be completely prevented in the surveys. And what are some of the strategies to minimize if not completely eliminate the bias.

1. Avoid leading questions altogether

As we have seen in the previous sections, leading questions are one of the major causes of this bias. So it’s strongly recommended to avoid leading questions altogether. Here are some leading questions and how they can be put in a more neutral way.

Leading: Don’t you agree that our product is the best in the market?
Neutral: What are your thoughts on our product features compared to our competitors in the market?

Leading: How much did you enjoy the annual company-wide get-together?
Neutral: How would you rate your experience of our recent company-wide get-together?

Posing the questions in as neutral and objective a manner as possible can reduce acquiescence bias to a great extent. Also, the surveyor needs to make sure that the questions are not designed with an eagerness to get positive responses, but the goal should be to get objective views of the respondent.

Leading question vs Neutral question Leading question vs Neutral question

2. Avoid difficult questions. Go for clear and concise questions.

As discussed before, if a user doesn’t understand a question properly, she is very likely to choose a positive option. It’s important to put across the question in as clear and concise manner as possible. Simpler words and smaller sentences are the easiest to understand. It’s advisable to run the survey past some of the colleagues or real users before sending it to a larger base of respondents.

For a somewhat complex question, consider providing a description to further clarify your question. To keep the user focused and in the zone, you may also consider having one question per page. That way the user is more likely to keep focusing on a single question without getting distracted by the length of the survey.

One question per page - Affiniv Survey

3. Be brief to avoid survey tiredness

If there are too many questions in a survey, it can lead to tiredness, also otherwise known as “survey fatigue”. This can lead to decreased attention and effort, resulting in acquiescence bias.

To mitigate survey tiredness, designers should keep surveys concise, prioritize question clarity, provide incentives, and communicate the survey’s importance in the beginning. These strategies make sure that the respondent is “intellectually present” to provide more objective responses and reduce acquiescence bias.

4. Proper choice of response options

A limited number of response options can lead the users to choose the more positive options. Also when designing response options, it’s important to provide middle-ground options, instead of just Yes/No, True/False, Great/Terrible, etc.

For example: consider the following question.
Do you agree that our customer service is delightful?
Options – Yes, No.

The above question can be redesigned as –
Please rate our customer service.
Options: Scale 1 – Terrible, 2 – Bad, 3 – Neutral, 4 – Good, 5 -Amazing

The first question is most likely to get a positive response on average, whereas the second question can get a more varied response. This can help you mitigate the impact of acquiescence bias.

5. Use open-ended questions

Open-ended questions can get you an unbiased opinion, compared to multiple-choice questions. For a multi-choice question, the user can simply select an option and move on whereas, for an open-ended, descriptive question, the user will be able to describe her opinion in more detail. So this can be a great option for the questions where you feel there is a good chance of the response being biased.

However, you have to be careful while introducing more open-ended questions because these can result in drop-offs and lower overall completion rates. Especially if it’s a longer survey, the user has to put in additional effort to write the answer which can result in non-responses or lower responses. Unless you are careful, open-ended questions can prevent acquiescence bias but can potentially introduce non-response bias.

6. Message of Neutrality and Transparency

To elicit objective and neutral responses from the users, it’s important to convey the importance of the survey and the ground rules. For example, before the survey, the surveyor should clearly communicate the objectives of the survey and what will be done with the responses. This message should also encourage the user to be frank with their feedback and how it’s going to benefit the user as well as the community or the group. 

The user can also be requested and reminded to provide honest opinions in the question descriptions.

If it’s an employee survey, it’s important to start with a confidentiality statement on who has access to the employee responses. Also for sensitive surveys, you may consider using an agency to roll out the survey. This will help employees provide honest and candid responses without any fear of repercussions. This can considerably reduce the acquiescence bias in your results.

7. Choice of demographics and user groups

This is as important as the other points. As we have discussed before, some cultures encourage people to be more polite and hence you are more likely to get more positive responses, even if they don’t completely believe so. To mitigate this, it’s important to choose a mix of demographics so that the sample can be a true representative of the population. 

Can acquiescence bias be completely avoided?

The answer to this question can be “almost”! With the use of the above-described techniques, you can look to minimize the acquiescence bias. But please be aware that some bias can still be present in the data. Some demographic segments may respond more positively than others, some users may choose to be more socially correct, some questions can still be a little difficult to comprehend for some of them, and so on. 

But overall, using some of the strategies described here can help you considerably lessen the acquiescence bias.

How Affiniv can help get more unbiased responses?

Affiniv is a customer and employee survey platform that can help businesses get unbiased customer feedback. Businesses both large and small use our product to create surveys, distribute the surveys over Email, send the link to the users, Embed the surveys in the website, and more.

Using our pre-built templates, you can create a survey in minutes without worrying about the biases that can creep into your survey. Also, our survey experts advise businesses on creating customer experience and market research surveys and can review your surveys for free!

Use the link to create an account and send a survey in minutes.

Affiniv NPS Survey Dashboard

Want to create a great-looking survey and send out in 10 mins?

Using Affiniv, create a survey, and send it out to your customers in minutes. Use our survey review service to create unbiased and research-driven surveys.