A list of cognitive biases to watch out for in user research

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Understanding the psychology behind our decision making can lead to more informed choices. Here are top cognitive biases to avoid.

7 min read

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Cognitive biases are thought patterns that cause errors in judgment and rationality, and may cause us to behave nonsensically. Being aware of these biases and how they work can help us as designers create better user experiences.


However, designers can be victims of bias too, especially when it comes to user research. This article will take a look at a few biases that might cause designers to make bad design decisions.


Before we dive in, let’s first mention the status quo bias. While not the most important bias, if we fail to recognize it then it could hinder all our other efforts.


The status quo bias is a reluctance to explore improvement or change. This bias can occur when the current state of affairs doesn’t seem all that bad, but it can also happen when we’re demotivated due to a design brief, a certain working environment, or are simply feeling design burn out.


If you’re ready to uncover your own cognitive biases (yes, we all have them!) and make your research more reliable, then read on.



Bandwagon effect


The bandwagon effect is the tendency to do or believe something simply because others do.


In order not to fall victim to this effect, it’s best to avoid agreeing with stakeholders vocally. Instead, let research findings do the talking and allow stakeholders to express their stance via anonymous voting.



The bandwagon effect: A single person with arrows pointing in the direction of a large group of people.
The bandwagon effect is the tendency to do or believe something simply because others do.


Groupthink


Groupthink is a similar but more dangerous effect where the desire for harmony results in the suppression of dissenting viewpoints. The result is often an awkward mishmash of viewpoints that doesn’t actually represent anyone’s honest, independent opinion.



Ambiguity effect


The ambiguity effect leads us to avoid ambiguity.


It’s natural to favor investing our time and resources where we believe the risk will be worth the reward. When the likeliness of a reward is more ambiguous, we become more hesitant to investigate.


However, in design, the majority of outcomes are unknown simply because we’re not our users. This means that almost every decision we make involves taking a leap into the unknown. It’s scary and there can be a lot of dead-ends, but luckily there are things we can do to lower the risks when deciding which opportunities to explore.


  1. Stakeholder voting: More votes means more reliability.

  2. Strategic research: Start off with research methods that formulate speed over accuracy (for example, test low-risk or low-fidelity mockups before testing high-fidelity mockups).



The ambiguity effect: three amorphic shapes labeled as "ambiguity" and one perfect circle marked as "clarity"
The ambiguity effect is the tendency to avoid the unknown and prefer the familiar.


Curse of knowledge


The curse of knowledge is when those who are better informed find it difficult to empathize with the less informed.


One scenario that comes to mind relates to user experience. As designers, we often assume that our experience with the product mirrors our users’ experience. When in fact, we have to remember that we’ve spent hours and hours inadvertently mastering it. So, what seems well-executed to us, might actually be unfamiliar to users initially.


In order to work around the curse of knowledge and to truly validate a solution, we must take our own personal experience with a grain of salt and listen, empathize, and test.



Hard–easy effect


The hard-easy effect is when we overestimate the user’s ability to carry out difficult tasks and underestimate their ability to carry out simple tasks. This relates to the curse of knowledge, where we’re at a disadvantage by being the masters of our own designs.


Similarly but more specifically, the planning fallacy is the tendency to underestimate the time required to complete a task.