14 March, 2024

Getting to the Truth: Understanding and Mitigating Survey Bias

While we like to believe that data, numbers, statistical analysis, and math belong to a world of cold, hard, inarguable facts, the real truth is this: Sometimes, data lies.

Why? Because lurking under the surface of even the most carefully designed survey is an invisible force always working against the truth, undermining data quality, obfuscating reality, and giving market research professionals a major headache in the process.

This force is, of course, survey bias, and it presents a particularly destabilizing variable in the world of market research. After all, if we can’t trust the data, what value could market research possibly have?

Here’s the good news: With the right research methodologies and a good understanding of how survey bias operates, it is absolutely possible to successfully mitigate its effects.

Let’s take a closer look.

What is survey bias?

Survey bias refers to a phenomenon in which the outcome of a survey is skewed or distorted as a result of inaccurate, untruthful, or otherwise influenced participant responses or feedback. It is caused by various influencing factors that can impact the truthfulness or accuracy of participants’ answers, and thus negatively impact or otherwise distort the accuracy of research results.

There are many different forms of survey bias. Some originate within the participants themselves, often subconsciously – a product of natural human behavior in which participants may alter their responses to align with societal norms or present themselves more favorably. Other types of survey bias creep in as a result of poor survey design, such as the inclusion of leading questions that steer the participant towards one answer over another. No matter the bias, the consequence is always the same: Survey results that do not accurately represent reality.

3 common types of survey bias

There are many different types of survey bias. Let’s take a look at the three most common survey bias examples:

1. Social desirability bias

This type of survey bias involves participants answering questions in a way that they feel, consciously or subconsciously, is more socially or morally acceptable. In instances of social desirability bias, participants give answers that they believe will make them look better to others while withholding their true feelings, experiences, or preferences.

Social desirability bias example

This type of survey bias is common in surveys dealing with more sensitive or highly personal topics. For example, a participant may underreport alcohol consumption, use of personal care/hygiene products, or how often they exercise or watch TV while overreporting other behaviors they consider more socially acceptable.

2. Courtesy bias

Courtesy bias occurs when a participant fails to fully state their level of unhappiness or dislike for a product or service as they feel that doing so would be perceived as rude or impolite. Courtesy bias can be more prevalent in cultures where courtesy is a fundamental aspect of social norms.

Courtesy bias example

Courtesy bias is particularly prevalent when participants are asked to rate levels of service they’ve received at a restaurant, for example, as this feedback is likely to have a direct impact on actual people (the workers at that restaurant).

3. Acquiescence bias

This form of survey bias takes the form of participants’ tendency to answer all questions in a survey positively, even if this poses a contradiction, in an unconscious effort to appear agreeable to the researcher.

Acquiescence bias example

An example of acquiescence survey bias would be if a participant answers “I agree” to both the statements “I prefer to spend time with others” and “I prefer to spend time alone”. These statements are contradictory, and one of these two answers must be incorrect.

Predicting the Growth of Plant-Based Proteins

Learn how HUUNU predicted key consumer trends in the plant-based protein market.

Read Case Study

How can survey bias influence results?

Survey bias can impact survey results in a number of significant ways:

Misleading conclusions

When data is compromised by survey bias, it generates misleading or inaccurate conclusions and insights, which can in turn compromise the quality of decision-making.

Inaccurate representations and overstatements

Survey bias can generate unrealistic expectations regarding the projected performance of a product, service, or idea in-market. Through inaccurate representations and overstatements of the product, service, or idea’s appeal, resources may be directed toward something that will not, in reality, succeed, even if the data indicates that it might.

Wasted resources

Market research is often used to determine where best to invest resources. If a survey indicates a certain product should move on to development, but that result is premised on biased survey data, then there is a significant risk that the resources invested in bringing that product to market will be wasted.

Use predictive market research to help prevent survey bias

While traditional methodologies struggle to mitigate the impact of survey bias, an innovative predictive market research design can minimize most forms of data bias as it relates to claimed human behavior.

In a prediction market methodology, for example, participants are asked to bet virtual currency on how they believe a target audience or consumer segment will respond to a product, idea, event, or concept. Because participants are not answering for themselves, but rather trying to predict how others will behave based on their tacit knowledge, they’re much more likely to answer honestly and more accurately, without the influence of various response biases. The result is significant mitigation of survey bias, more accurate results, higher quality data, and more successful predictions of in-market success.

With CRG Predictive Intelligence, the data never lies

CRG’s industry-leading HUUNU platform is a behavior-based predictive research methodology with a proven in-market accuracy rate of 90%, three years out and beyond. Whether you’re testing a new product, advertising messaging, or early-stage ideas, HUUNU’s innovative prediction market methodology delivers accurate results free of the negative impacts of survey bias, for bulletproof decision-making and crystal-clear strategic guidance.

[CONTACT US]

Leverage the proven power of predictive intelligence today.

FAQs

Why does survey bias matter?

Survey bias compromises the value and effectiveness of market research methodologies. Without high-quality, unbiased data, companies are unable to get the insights they need to drive their decision-making, or, worse, act upon faulty data, leading to wasted investments.

Is there a way to eliminate survey bias?

Unfortunately, human beings will always be prone to bias, but with the right consumer insights mechanism, you can mitigate the effects of survey bias to a point where it becomes negligible.

What are the best practices for reducing survey bias?

The best way to reduce survey bias is to adopt a predictive research methodology, such as a prediction market, which asks participants to predict how others will respond to the product, service, or idea under testing, as opposed to supplying their own opinion. Human beings are much better at predicting how others will behave and thinking about others’ responses reduces the chances of, for example, social desirability bias.