Overcoming Cognitive Bias in Market Research

cognitive bias in market research, confirmation bias

It’s hard to avoid cognitive bias in today’s world, it has some part in almost everything we do. It is important to remember that no one is exempt from bias. While it has its uses, cognitive bias can distort how we view our surroundings and findings. This blog series will explore the impact of cognitive bias in market research, its processes, analyses, and outcomes. With each installment, we hope you’ll learn more about cognitive bias and how market researchers can work with and around it.

As part of our biology, our brains are wired in ways that limit our logical thinking and cause us to think and react in ways that don’t always make sense. This explains why people have a hard time changing their minds or do things like fall for crazy news stories. These in-built thought processes can be hard to recognize even in our own heads and even harder to challenge.

Much of what we hear about cognitive bias focuses on the social impact of our biases; however, bias impacts us in most aspects of our daily lives and affects more than just social behaviors. It plays a huge role in most work environments but for those of us in a research-related field, it is something we need to be diligent in acknowledging and addressing. The best way to navigate the bias minefield is by recognizing what bias looks like, how it impacts our decision making, and adjusting for it. That way we benefit from bias when needed and overcome it when it gets in the way.

Cognitive Bias 101: Explicit vs. Implicit Bias

There are two major types of bias – Explicit and Implicit, which are tied to the two thought systems (System 1 and System 2).

cognitive bias in market research

Explicit bias refers to the attitudes and beliefs we have about a person or group on a conscious level; these are biases we are aware of. Much of the time, these biases and their expression arise as the result of a perceived threat. When people feel threatened, they are more likely to draw group boundaries to distinguish themselves from others. Explicit bias is tied to System 2 thinking, which is slower, controlled, requires conscious effort, and dominated by analytical thought. System 2 lets us overcome initial impulses and suppress our knee jerk reactions. So, while System 2 is less likely to be impacted by cognitive bias and, in fact, lets us control our biases, it means explicit biases are more entrenched.

Implicit Bias is going to be our primary focus in this blog series. Implicit Bias is our internal unconscious thoughts, beliefs, and attitudes that guide our thinking; most often without us recognizing them. They occur outside of our awareness or control and are generally a product of System 1 thinking. System 1 is the brain’s automatic, intuitive, and unconscious thinking mode. It requires little energy or attention, but it is often bias-prone. System 1 requires the least effort and is generally what drives our day-to-day decision making, as it needs less mental energy.

Although everyone has implicit biases, research shows that implicit biases can be reduced through the very process of discussing them and recognizing them for what they are. Once recognized, implicit biases can be reduced or “managed,” and individuals can control the likelihood that these biases will affect their behavior. Market researchers need to recognize when implicit biases impact their studies, including study design, how respondents react to stimuli, and how we interpret study results. There may be steps market researchers can take to correct for implicit biases in their design and analysis.

Confirmation Bias

Confirmation bias – or, the seeking, interpreting, or favoring of information or evidence which is partial toward existing beliefs while giving less weight to information which does not conform – is one of the most common types of cognitive bias. It is also one of the most insidious. Everything from financial decisions to racism are impacted by confirmation bias. When conducting market research, scientific research, or polling, correcting for confirmation bias is critical.

Let’s look at confirmation bias an example of cognitive bias in market research. If a business owner has an idea for a new product that she really wants to pursue, she hires a market research firm to test the idea with the target audience. As the audience provides feedback, the business owner may latch onto the positive feedback about the product idea but disregard, downplay or completely ignore any of the negative comments. If she does move forward with the product, she’ll likely be doing so with unrealistic expectations about its success.

confirmation bias, cognitive bias

In the example above, the business owner may have such a deep faith in her product idea that the confirmation bias seeps into every facet of the market research process. The way she wants the questions phrased may be biased toward a positive audience response vs. one that better reflects reality. She may provide a product description that positions it in too favorable a light, thereby influencing the audiences in favor of the idea rather than allowing them to provide an accurate reaction. Additionally, the team that the owner hires knows what she wants and will be inclined to bias the results to tell the client what she prefers to hear. It is important when conducting research to be aware of both our own biases but also the biases of those surrounding us.

Confirmation bias can impact how market researchers analyze data and present results. When dealing with large data sets that may be ambiguous, it’s tempting to focus on small pockets of data that confirm one hypothesis or another; however, that ignores the totality of the data that may not clearly support any direction.

Part of what makes confirmation bias so insidious is the human inclination to seek the familiar. The comfort of familiar settings and surroundings is in part related to confirmation bias. Confirmation bias encourages us to seek or form patterns and stick to them, it can even reduce anxiety and stress in some situations. Common places we see this is in repeating music patterns and story lines. In music the ability to predict each successive beat or syllable is intrinsically pleasurable. This is a case of confirmation bias serving us well.

In addition, to standard confirmation bias, there are two close relatives of confirmation bias. The Back-Fire effect and Halo Effect:

The Back-Fire Effect

What is the back-fire effect? Essentially, when presented with information that contradicts closely held beliefs or runs counter to things which are emotionally important, you are more likely to double down on those beliefs. Why? A lot of it has to do with biology. The amygdala is in your brain interprets contradictions of thought as though you are being attacked by a predator rather than as pieces of information, and humans respond accordingly. The more important to you the belief the more adverse your brain is to accept the new knowledge.

In market research, the backfire effect can skew analysis and results. If the research uncovers something that goes against a belief – especially the client’s belief – we may be tempted to skew the results or spin the story to better support that belief. Doing so would seriously impact the market researcher’s reputation for providing accurate results. As market researchers, we need to recognize when there is an issue, identify the sore points, and take a step back. This applies to client reactions as well. Listening and adapting to the information presented is the key.

The Halo Effect

The halo effect occurs when we draw an overall impression of a person based on one characteristic. This especially applies to physical attributes influencing how we rate an individual’s other qualities. However, the halo effect applies to more than just people and how they look. It’s often a matter of aesthetics, from ad design to the look and feel of your brand. The halo effect has an opposite and equal title “the horns effect” which occurs in the same manner but rather than latching onto the positive characteristic we latch onto a negative.

Market researchers need to be aware of the halo effect especially during interviews. Regardless of what the individual looks like, cognitive bias in market research impacts the information that analysts provide. It’s important to let the data speak for itself and avoid letting your first impression be your only impression. In addition, this applies to how we present our research and findings. Attractive, organized, easy to interpret work is likely to have a greater value attached to it and be interpreted as more trustworthy than work that is disorganized.

halo effect, confirmation bias, cognitive bias in market research

Overcoming Cognitive Bias in Market Research

Cognitive bias is seemingly hardwired into our brains and there are evolutionary reasons why this is the case. Overcoming cognitive bias in market research means reflecting and being aware of your leanings. Read and absorb all the information rather than forming an opinion at the outset, encourage yourself and others to gather information in a conscious manner and allow yourself to be wrong.

Seek out information that disproves your theory and if you find it, accept that it will provide you with a more well-rounded understanding of the research. Make sure that evidence backs up what you are reading and that evidence comes from a trustworthy source. Remember, you can find data cut in hundreds of ways but not all of them come from good sources.

Listen for repetition, if you find yourself repeating the same statements over and over or your interviews keep bringing up the same phrases, make sure they’re based in fact and not based in you or the subject’s implicit biases.

Stay tuned for additional blogs in this series. We will explore other forms of cognitive bias, such as anchoring, attention bias and over confidence.

Elissa Cannonwood is a Senior Associate at Vivisum Partners. She has experience with both quantitative and qualitative research methods. Email Elissa at elissa.cannonwood@vivisumpartners.com