Many survey makers struggle to get genuine responses, handle incomplete surveys, and make sense of conflicting data. 

If you're also one of them and wonder why you can never make sense of the survey data, you’re probably facing survey bias. 

Different types of survey bias may sneak into surveys, leading you down the path of wrong answers. 

The reliability of your study and the honesty of your participants depend on avoiding bias and outside influences.

In this article, I’ll cover survey bias, its different types, and how to write unbiased survey questions that help you measure the real deal.  

What is survey bias?

Bias is basically when something sways your results one way or another. 

In surveys, it can come from two main sources: you (the survey creator) and your respondents (the people answering your questions).

As the one deciding how to create the survey, you hold a lot of power. 

If you're not careful, your biases and assumptions can affect the survey design. 

If you ask leading or biased survey questions that nudge people toward a certain answer, or if you only survey a specific group of people, you're introducing bias in your survey. 

On the flip side, the people taking your survey can also introduce bias.

Maybe they misinterpret a question, accidentally skip a crucial part, or feel pressured to answer in a certain way because they want to please you or avoid looking bad.

When survey bias creeps in, it messes with your results and you get a skewed picture of what you’re trying to study. 

It could lead to bad decisions and wasted resources.

Now, let's go deep into the different types of survey bias you might encounter. 

Types of survey bias to be mindful of

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Some of the most common types of survey bias are as follows. 

Selection bias

Selection bias stems from the population that ends up taking your survey. Ideally, you'd have everyone in your target audience chime in, but that's not always the case. 

I have broken it down even further into its two subtypes. 

1. Sampling Bias

Sampling bias kicks in when you only get feedback from a small group of people who are similar to each other. 

Maybe you only ask people who are easy to reach, like your friends or people who happen to be around. 

That might not give you a true picture of what everyone thinks because you've left out some voices.

2. Volunteer Bias

Volunteer bias occurs when only people who really care about the topic take your survey. 

Let’s say you ask people to share their thoughts on a new product, but only the biggest fans of your brand respond. 

You might end up with results that are way more positive than what the general public thinks. 

Response bias

Response survey bias occurs when people don't give honest answers for various reasons. 

Again, there may be multiple reasons why people don’t respond accurately, each resulting in a different subtype of response bias. 

Let's zoom in on a few of its subtypes.

1. Social Desirability Bias

This is when people give answers that they think will make them look good or to avoid judgment. 

For example, if you ask people how often they exercise, some might say they work out more than they actually do because they want to appear healthy and fit.

2. Acquiescence Bias

This one's all about saying "yes." 

People might agree with statements more often than they truly believe, just to move on through the survey. 

Acquiescence bias occurs if your survey has a lot of leading questions or is just too long and people want to get it over with. 

3. Extreme Response Bias

Extreme response bias is when people choose the most extreme answer options, even if those options don't match how they really feel. 

Biased surveys that have a lot of questions with strongly worded answer choices often result in extreme response bias.

Question order bias

Question order bias is when the arrangement of questions in a survey influences how people respond. 

Human brains are wired to look for patterns and consistency. 

When we answer questions in a survey, we tend to stick with a theme or a mindset. 

If the first question primes us to think in a certain way, we're more likely to continue thinking in that way for the rest of the survey.

Let’s say you're conducting a survey about customer satisfaction for a software company. 

If you start by asking about overall satisfaction first and then dive into specifics like customer service quality, the order might affect how people rate each aspect.

If they're feeling generally happy, they might give higher ratings across the board, even if they had some issues with customer service.

Confirmation bias

Confirmation bias is the tendency to favor information that confirms what you already believe and downplay evidence that contradicts it. 

When we come across information that agrees with us, it feels good. It confirms that we're right, and who doesn't love being right?

This type of bias most commonly occurs when you analyze survey results.

For example, you get a mix of positive and negative reviews for one of your products through a survey. 

Confirmation bias might make you focus more on the positive ones – the ones that fit your idea of a successful launch. 

You might even downplay or dismiss the negative feedback because it clashes with your expectations.

Survivorship bias

Survivorship bias occurs when we focus on the people or things that have made it through a process or achieved a certain outcome while ignoring those that didn't. 

Let’s say you’re conducting a survey about the success of new businesses. 

If you only talk to entrepreneurs who have managed to keep their businesses afloat for a year or more, you might get a rosy picture of the startup landscape. 

You're missing the voices of all the entrepreneurs whose businesses failed within that first year. 

By only looking at the "survivors," you get an incomplete and overly optimistic view of the challenges new businesses face.

It's natural to want to learn from successful examples. We admire winners and want to emulate their strategies. 

But by focusing solely on success stories, you might miss out on valuable lessons from failures.

And we all know who the best teacher is, don’t we?

Non response/systemic bias

Non-response bias happens when some people don't take your survey. 

It can end up messing up your results because the opinions of those who didn't respond might be different from those who did. 

When certain groups are less likely to answer, their views get underrepresented.

Survey fatigue, lack of interest, and privacy concerns can cause non-response bias. 

If people get too many surveys, they might ignore yours. They could also skip it if it's too long or complicated. 

Sometimes, the timing isn't right—maybe they're busy or uninterested at that moment.

Another issue is relevance. If your survey topic doesn't seem important to them, they won't bother taking it. 

For example, if you ask about advanced technology in a survey sent to an older demographic, they might not feel it's relevant and will not respond.

Privacy concerns can also lead to non-response. 

People might worry about how you will use or share their information. They'll skip the survey if they don't trust that their data will stay private. 

How to avoid survey bias?

To get clear and accurate data, you need to avoid bias in surveys. But how do we do it?

Here are some actionable tips that describe how to avoid survey bias:

• Make sure your questions are easy to understand and don't push respondents toward a particular answer. Avoid using words that suggest a positive or negative response.
• Always provide a full range of answer choices so respondents can choose the one that best fits their opinion. Include both positive and negative options.
• Mix up the order of questions for each respondent to prevent earlier questions from influencing answers to later ones.
• Ask about one thing at a time. Double-barreled questions confuse respondents because they address two issues in one question.
• Provide a "Not Applicable" or "I Don't Know" option. This way, respondents don't feel forced to choose an answer that doesn't reflect their true opinion.

• Let respondents know from the get-go that their answers are anonymous. It will encourage them to be honest and reduce the chance of social desirability bias.

Make unbiased surveys with Formaloo

Understanding and addressing different types of survey bias can help you avoid misleading results and make better decisions based on your survey data.

Now that you know how to tackle survey bias, you're ready to create effective and trustworthy surveys.

Formaloo makes it easy to create beautiful, unbiased surveys from scratch or with ready-to-use templates. 

With user-friendly tools, randomizing question order features, ensuring anonymous responses, and a variety of customization options, you can design surveys that get honest feedback. 

‍Sign up for free today and start creating surveys that give you the insights you need.