Avoiding cognitive bias in UX Research

As User Experience (UX) Researcher, I spend a good chunk of my time observing user behaviour, and whilst it may sound scientific, in some way or another we all go through this on a daily basis on some level or another. Whether it’s at a grocery store judging the person in front of you for hoarding half the store’s stock of toilet paper, or observing people’s reactions when they stare at you for wearing a facemask to avoid spreading deadly viruses, we all do it. Whatever the scenario is really, in some ways on a subconscious level, our thoughts and perceptions are affected by cognitive biases.

“A cognitive bias is a systematic error in thinking that occurs when we interpret information in a way that it affects the decisions we make.”

Being in UX research, ignoring them, or worse, not doing everything in your power to reduce their impact on the quality of your research can affect the conclusions and results achieved. There are hundreds of cognitive biases, but as I am still discovering these myself, let us take a quick dive into three of the most common cognitive biases  that I have faced and still facing as a UX researcher.

GiG UX Research

Framing Effect

What is it?

Quite possibly one of the most recurring biases in user research. Simply put, human beings don’t make choices in isolation, we are very much affected by the way it is presented to us.

For instance, when presenting a prototype to research participants and when asking them about their experience while using it, you should take special care on how you frame the question. A question such as “What did you dislike while using the product?” can cause the participant to only focus on the negatives of the product, quite possibly for the rest of the test duration and in turn might lead to misleading insights.

How can you avoid it?

Try leaning more towards neutral questioning such as “How do you feel when you use the product?” instead.

Sunk Cost Fallacy

What is it?

The more time you invest in something, the harder it becomes to abandon.

As researchers, we invest a lot of time conducting research and synthesising data. Obsessing over findings can easily distract us from the objective.

How can you avoid it?

It is important to breakdown research into smaller chunks by running smaller experiments and testing results frequently. In short, fail fast — fail frequently.

Clustering Bias

What is it?

Do you have a friend who has won multiple poker rounds back to back? Well, unless he/she’s counting cards, then this winning streak is bound to end. When we perceive this winning streak in a relatively short time period, this kind of probabilities is to be expected, even if they seem highly improbable. The luck will run out eventually…

Finding patterns or themes in data is the staple of qualitative research, however, it is often impossible to avoid seeing patterns that might just be smaller sets of randomness.

How can you avoid it?

Give it more significance! Combining qualitative research with quantitative data will help reduce the randomness of some insights since we will be adding more volume of data on a higher level — hence why when it comes to research methodology, like many others, I believe that mixed-methods is the way to go.

These are just a few examples of the different types of UX bias that I have experienced, at GiG UX research is a fundamental part of everything we do from product and design to markeitng. Stay tuned to our blog for more UX updates and tips.

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Carl Borg
UX Research Manager

Article first published

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