What is a cognitive bias?
A cognitive bias is an error that occurs when humans are processing and interpreting information in the world around them and it affects the decisions and judgments that they make.
Our brains are capable of progressing massive amounts of information but it also has its limitations. Cognitive biases are often the result of simplifying information and helping our brain to avoid a cognitive overload. They help us to make sense of the world around us and result in faster decision making. Some of them are related to memory, the way you remember an event might be different than it happened in reality and therefore this can result in biased decision making or problem solving. They can also relate to attention, since our attention span is very limited, people have to be selective about what they pay attention to in their surroundings.
The concept of cognitive biases was at first introduced by two researchers Amos Tversky and Daniel Kahneman in 1972. Since then, academics have introduced several cognitive biases that have an influence on our daily lives. In this article we want to show you the most common biases that you need to be aware of when doing user research.
Cognitive biases you need to be aware of as a UX Researcher
We tend to “anchor” our decisions based on the first piece of information we receive. For example, if you see an item reduced due to a Black Friday deal for which you’re used to paying $10 and see it on sale for $8, this reduced price will feel like a deal. However, it can be that the original price used to be $8 dollars anyway but you need an anchor to compare it to, and shopping sites know this all too well and they are happy to provide you with one. The problem is when even you know this, but you just can’t ignore it.
How can we avoid the anchoring bias?
- Do not lend too much weight to the first piece of information you receive, this is especially important if you do user research! For example, while user testing don’t start to focus on a specific problem as it arises, because it might just be an isolated result. Gather more feedback for making an informed decision. But by anchoring on one result we might discard features and change direction without having a deeper look at those results.
- As an anchor serves as a reference point for our comparisons, pay attention to how the items in a choice set are ordered! Ordering the numbers so the largest amount appears first makes each amount thereafter seem like less money. For example, people don’t typically order the most expensive option on the menu, they often do order the second most expensive item, which seems like a good deal in comparison to the highest-priced option.
Framing Effect Bias
The manner in which choices are presented to us also affects how we view them. A good example of this is a study that had participants watch a film of a traffic accident and then answered questions about the event, including the question ‘About how fast were the cars going when they contacted each other?’ Other participants received the same information, except that the verb ‘contacted’ was replaced by either hit, bumped, collided, or smashed. Even though all of the participants saw the same film, the wording of the questions affected their answers. The speed estimates (in miles per hour) were 31, 34, 38, 39, and 41, respectively.
How to counteract the Framing Effect Bias?
- Become aware of your decision frame, know that they exist, even if they are unconscious, and that you have to be aware of them in order to make the right decisions.
- Try to avoid making quick judgments, the time to explicitly think through the context can lead to more accurate and meaningful decision frames. Spending just a little more time thinking about for example research findings will vastly increase the ROI of the total investment.
- Gather more context before making a decision, acknowledge when you have enough data gathered to make an informed decision. Then consider how you could learn more about the topic. Be confident enough to admit when you’re unsure of what action to take based on your data. Get a second opinion from someone on your team or if necessary redo the survey, interviews, tests, etc.
- Experiment with different frames, try restating your question in reverse terms, or from a different point of view. Take a few seconds to step back and view your data from a success rate to a failure rate, or consider the actual number of people affected by the percentage of failure is a quick way to check whether your opinion is being unnecessarily influenced by framing.
- Ensure language is clear and you are not leading respondents to a certain answer, be aware that the way you ask questions e.g. in a survey can lead people to answer them differently than intended. Always check that the language is clear and you are not leading the respondents towards a certain reaction.
- Guide every user to the same conclusion with your design, how you present your main call to action or your value proposition on a site is crucial in every term. Ask yourself, what is it that I want my audience to achieve? Make sure you are guiding all your users with your visual cues to the same conclusion.
False Consensus Bias
The fact that we form opinions in favor of our own personal beliefs is an example of the False Consensus Bias. As a UX Researcher, I often fell myself into the trap of the False Consensus Bias when writing e.g. survey questions, unconsciously phrasing questions with the assumption that our users would appreciate the same UX features that I appreciate. Even though the core goal in UX design is to set aside your personal beliefs in favor of the wants and needs of your audience, we are only humans and like to see the product through your own lens – making it difficult to imagine that others would see it differently.
How to avoid the False Consensus Bias?
- Identify and articulate your own assumptions before starting the design process, a good example here is to write down your own assumptions regarding the results of e.g. a survey, make sure that these will be YOUR assumptions, then put them aside.
- Pretend every single one of your assumptions is wrong, this might help you to find out which of your assumptions are e.g. risky for the products’ success or the user satisfaction, then write down questions that challenge these assumptions.
- Collect feedback from a wide range of users, don’t ask only people in your own environment, those opinions will not be representative of your entire audience! As they might be the same age as you or have similar interests, which will only strengthen the False Consensus Bias.
- Everything you do must be backed up with data that indicates the product you researched for and designed will eventually be successful, not because it’s your personal opinion!
While doing research I often see this type of bias emerging, especially with people who like to agree with and support others in general. It can happen for many reasons, including seeing the researcher as someone who is a professional and therefore their opinion must be valued. People also try to answer your questions with the least amount of effort, they will avoid wasting time or energy to build up any resistance regarding the task at hand. The friendliness bias can indeed immensely ruin your hard work of gathering data as you will get endresults that are biased and therefore useless.
How to avoid the Friendliness Bias?
- Remove yourself from the picture, e.g. do unmoderated sessions next to moderated interviews/tests.
- If it’s an in-person research have someone outside your team serve as moderator, make sure that the one gathering the feedback is not responsible for making the design or developing the product. This way people are more likely to provide an honest answer regarding your product and you will be able to feel more comfortable to ask questions about it.
- Gather feedback digitally if possible, people are more open when sitting behind a screen than sitting in person with you in the same room.
- Keep surveys as short as possible and phrase the questions in simple terms, don’t ask too many questions, expect that people want to take the least effort of completing them! Don’t make them all mandatory, so people might skip questions that make them uncomfortable. Before you finish the survey take a step back and check which question might not be necessary to ask so you can cut the survey even shorter.
Our conclusion is that…
…user feedback is always fundamental for building any digital product! But you need to be aware of the cognitive biases our brains create to absorb the information in our surroundings, in order to get ‘clean’ and unbiased data. By simply understanding what each bias means and by breaking down the ways that it appears during the user feedback gathering process, you can put measures in place to overcome misleading preconceptions and gather the most unprejudiced feedback possible.
Are you interested in more psychology topics related to UX Design? Then stay tuned for further blog entries to come in our “Human Mind and Usability” section!
Sources which have been used for this blog entry and where you can read more about the topic:
- Colleen Roller: How Anchoring, Ordering, Framing, and Loss Aversion Affect Decision Making
- Hunter Jensen: Don’t Let Your Brain Deceive You: Avoiding Bias In Your UX Feedback
- Hannah Levenson: User Research Bias: How It Hurts Your App And What You Can Do About It
- Kendra Cherry: What Is Cognitive Bias?
- Leslie Ye: The Psychology of Choice
- Vito Rispo: The Power Of “Framing Effects” And Other Cognitive Biases