Survey response bias is a critical topic for customer experience professionals.Creating a market research campaign can be time consuming. However, how can you be sure that the survey responses are genuine? This is where we gauge survey response bias. In this blog, we will discuss the meaning of response bias with examples. We will also share why it happens and how it can negatively impact the survey campaign. Recognizing and mitigating this bias is essential for drawing accurate conclusions from survey data. 

Survey Response Bias Definition

Survey response bias is the tendency of respondents to answer questions inaccurately, perhaps, due to subconscious influences or pressures. This issue is significant because it can lead to distorted data, misrepresenting sentiments, opinions, or behaviours of the survey population. For researchers and customer experience professionals, accurate survey data is paramount, as it forms the foundation of insights and subsequent strategic decisions.

Consider a scenario where a company conducts a customer satisfaction survey. If respondents believe that their honest feedback might negatively impact their relationship with the company, they may provide more favourable ratings than they actually feel. As a result, the company may overestimate customer satisfaction and neglect areas needing improvement.

What Causes Survey Response Bias?

Several factors can cause response bias. This can lead to inaccurate data. Every market research professional needs to dive into the key factors that can skew critical data. This can help create better strategies to achieve accurate results in the upcoming campaigns.

1. Cognitive and psychological factors

The current mind state of every respondent can significantly impact their survey responses. Survey response bias is dependent on cognitive and psychological factors. This includes fatigue, stress, or mood that can influence how individuals answer questions. For instance, a respondent who is tired or stressed may rush through a detailed questionnaire. At the end, you get inattentive or inconsistent responses.

2. Social factors

Social desirability bias stems from the desire to conform to social norms and expectations. Respondents may provide answers they believe are socially acceptable or favourable rather than their true thoughts. This can occur if the results are publicly viewed and people are pressured into answering in a manner that will be crowd-favoured. Common examples are political views or views on social norms that are typically sensitive to discuss on a public forum. 

3. Survey designing factors

Designing survey questions in a certain manner can also contribute to response bias. Leading or loaded questions, which suggest a particular answer, can prompt respondents to answer in a biased manner. For example, a question like “How satisfied are you with our excellent range of products?”. This assumes a positive experience. This can lead respondents to provide higher satisfaction ratings than their actual experience .

The order and format of questions can also impact responses. For instance, asking a sensitive question too early in the survey might make respondents uncomfortable. They might not be too honest in their subsequent answers. Similarly, using complex language can confuse respondents. They can skip the answers or provide a randomized response to avert the question.

4. Environmental factors

The setting where a survey is conducted can also impact responses. Factors such as the presence of others, the perceived confidentiality, and the respondent’s current environment can all affect how they answer questions. For example, respondents might provide more socially desirable answers if they feel that they are being monitored in a public setting.

Understanding these causes of survey response bias is essential for designing surveys that minimize bias and accurately capture respondents’ true thoughts and feelings.

How does Survey Response Bias Impact Data? 

Response bias does not provide fruitful conclusions. This can cost resources and is time consuming. There are negative impacts of response bias.

• Biased responses fail to showcase the true sentiment, opinions and experiences of the target audience. Researchers cannot make impactful or useful decisions for the same population they are surveying. 
• Exaggerated responses can cause a false perception for industries where customer satisfaction is paramount (retail, hospitality, FMCG etc). On the other hand, extremes of responses may create a false sense of dissatisfaction, prompting unnecessary changes. 
• Incorrect data can lead to product or marketing misalignments with customer needs, wasting resources and revenue. 
• Sometimes, the response bias can occur due to incorrectly collecting of customer information (without consideration of external influences or a fool-proof research method). 
• One must consider that people are prone to influences from social pressures, external environments, and errors from question phrasing. 

Accurate data helps businesses understand customer needs, identify improvement areas, and make strategic choices for success.

What are the Types of Response Bias in Surveys?

Here are some 10 types of response biases in surveys that can impact data quality:

1. Acquiescence bias

Acquiescence bias is a “yes-saying” bias. Here respondents have the tendency to agree with statements or answer positively, regardless of their true feelings. This bias can occur in questionnaires when questions are framed in a way that encourages agreement. Respondents may appear more favourable or agreeable than they genuinely are. This brings skewed data.

2. Social desirability bias (Hawthorn Effect)

Respondents answer questions to appear favourably by others. This is known as the Hawthorn effect. This often results in overreporting positive behaviours or attitudes and underreporting negative ones. Example: Seeking political opinions from people on social media platforms openly. People are more inclined towards choosing answers opted by the majority. This does not disclose their true feelings. 

3. Extreme response bias

Some respondents consistently choose the highest or lowest options on a scale, rather than a balanced response. This can distort the data, especially in scales meant to capture subtle differences in opinions.

4. Central tendency bias

Central tendency bias occurs when respondents choose middle or neutral options to avoid offering a strong opinion. This can reduce the accuracy of results by masking true preferences.

For example, “on a scale of 1 to 7, how satisfied are you with our customer service, where 1 is ‘Very Dissatisfied’ and 7 is ‘Very Satisfied’?”. The respondent consistently chooses 4, a neutral or middle option, even if they have strong feelings (positive or negative) about the service. The respondent avoids taking a definitive stance and instead opts for the middle choice.

5. Question order bias

The order in which questions are presented influences responses. Earlier questions may set a tone or context that affects how respondents answer later questions.

6. Confirmation bias

Respondents may selectively focus on information that aligns with their existing beliefs or experiences, which may lead to skewed or biased answers.

7. Recency bias

In a multi-response survey, audiences might favour the most recent items they’ve seen. This does not accurately reflect their views.

8. Leading question bias

Questions can be worded in a way to nudge a specific answer. People may be influenced to respond as per the nudge even if it does not reflect their true opinion. 

For example “How much did you enjoy our exceptional customer service experience?”. 

The respondent answers, “Very much,” even if their experience was only average. The phrasing (“exceptional customer service experience“) implies a positive experience. This can make the respondent answer more favourably even when they did not enjoy the service.

9. Cultural bias

Cultural backgrounds and norms influence responses, especially when questions are interpreted differently across cultures. This does not give an accurate viewpoint. 

10. Non-response bias

Certain groups are more likely to skip or avoid answering specific questions. For example, people are not willing to share sensitive responses based on sexual history, medical information or drug-related use. The responses fail to represent all perspectives accurately.

Tips to Mitigate the 8 Types of Response Bias

1. How to reduce sampling bias?

Use tools like random number generators to reduce sampling bias. This will enable you to give everyone in the target population an equal chance of selection. Apply stratified sampling by dividing the population into subgroups (e.g., age, gender, income) and selecting random samples from each stratum. This way, the sample will reflect the population’s demographics.  

2. How to reduce non-response bias?

There are many reasons why people may not want to respond to surveys. There are ways to solicit genuine responses. 

Optimize surveys for devices so that people can answer on the go. Additionally, offer survey incentives that are appropriate for the respondents. You can also automate gentle reminders at touchpoints. 

3. How to avoid social desirability bias?  

Offer confidentiality upfront. This will bring more genuine responses especially on sensitive topics of political views, cultural issues, health and wellness or medical history. Alternately, use imaginary scenarios for questions that are not directly linked to the participants. This will give you a general consensus of their viewpoints.   

4. How to avoid question order bias?

Randomize questions to reduce the influence of responses from the previous questions. Merren can help you randomize questions when curating a survey. You can also randomize multiple choice answers in a single click.

5. How to mitigate demand characteristic bias?

People are willing to respond when their feedback is valued and acted upon. Inform respondents that their feedback will be critical for future improvements. Assure them that there are no correct-incorrect responses.

6. How to prevent recall bias?  

People can forget events after the moment passes by. A simple resolution is to offer in-the-moment surveys to collect best possible responses on experiences. This works for retail experiences, events and across the hospitality industry. For example, after check out, offer an instant guest satisfaction survey to understand how your guest might have felt in the duration of the stay.

7. How to mitigate acquiescence bias?

Avoid prompting people to answer in a certain direction. Keep questions in a neutral language. Enable people to express experiences in their own words. To learn more, read about the preventive measures here.  

8. How to mitigate central tendency bias?

Use balanced scales with equal positive and negative options. Avoid neutral midpoints to encourage definitive responses. Clarify questions and provide context with examples to reduce uncertainty. Employ forced-choice formats or binary options. You can also apply confidentiality and keep surveys concise to prevent fatigue.

Avoid Survey Response Bias with These Guidelines

Completely removing response bias is not always possible. Here are some steps to consider if you want genuine responses: 

• Keep questionnaires short and goal oriented. Avoid respondent fatigue to get genuine responses.
• Avoid ambiguous or complex vocabulary. People have limited cognitive ability to answer surveys. Keep it simple to prevent survey drop-out rates. 
• If you want to ask sensitive questions, keep it confidential. Assure participants that the responses will not be used for external purposes. Assurance can help you achieve a high response rate. 
• You can use engaging elements such as emojis or audio surveys. These elements can encourage people to offer their responses. Alternatively, you seek responses in the form of photos, audios or videos to keep it media rich. 
• Avoid questions that may emotionally trigger people. Keep it objective and neutral. 
• Use the right survey tool that can help you curate the right type of question. 

Launch Highly Responsive Surveys with Merren

Understanding and addressing survey response bias is necessary to obtain genuine and reliable data. Survey response bias can significantly distort data, leading to misguided decisions and strategies. Recognize the types of bias, understand their causes, and implement best practices to mitigate them.
Opt for pre-designed survey templates without any cognitive effort. You can get an instant survey maker with our AI survey builder here. Ensure that your campaign is consistent with the help of pre-tested questionnaires. Additionally, you can access every customer data on the CX dashboard. What’s more? CX professionals can get an AI to assess data in real time.

To access every Merren feature, sign up for a 14 day free trial here.