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cognitive bias is an error in thinking that happens when people process and interpret information around them. It acts as a mental shortcut our brains use to quickly make sense of complex information. But these shortcuts can sometimes lead to mistakes or unfair judgments. For example, imagine you're looking for a new game app to download. If you've had great experiences with puzzle games in the past, you might think all puzzle games are fun, even without trying them. This happens because of a cognitive bias — your brain is relying on your past happy feelings about puzzle games rather than judging each new game on its own merits.
FALSE CONSENSUS EFFECT
The false-consensus effect occurs when people assume that others think the same way they do, often viewing alternate responses as deviant and unusual. For example, if a designer loves using shortcut keys, they might assume that all users prefer shortcuts too and might design a software interface that relies heavily on these shortcuts.
However, not all users are comfortable with shortcuts and some might prefer navigating through menus. This assumption could make the software less user-friendly for those who aren't like the designer.
Because of this bias, it’s easy to mistakenly think that only someone very different or unusual could fail to figure it out. Recognizing the false-consensus effect can help you create products that cater to a wider range of preferences and needs and not just your own.
NEGATIVITY BIAS
Negativity bias refers to the tendency of users to focus more on negative experiences than positive ones. This means that a single issue with a product can seem more significant than many of its good features, overshadowing the hard work put into creating a seamless user experience. For example, if users encounter a confusing checkout process on an otherwise easy-to-navigate shopping site, this frustration might dominate their perception of the site. They may not notice or comment on the smooth navigation because the negative experience at checkout stands out more in their memory.
This bias can make users more likely to remember and report negative experiences, influencing their overall satisfaction and loyalty to the product.
ANCHORING BIAS
Anchoring bias refers to the tendency for users to rely heavily on the first piece of information they see when making decisions. This initial information sets the "anchor" and all subsequent decisions are influenced by this anchor. For example, if users first see a premium product priced at $100 on a website, they might anchor to this price. When they later see a similar product for $70, they may perceive it as significantly cheaper and a good deal, even if, objectively, it's still expensive.
This can influence their purchasing decisions and how they perceive the value of products. The same applies to information and CTAs that they come across first on a website or app — they are likely to give more weightage to this initial information and make their decisions based on it.
HALO & HORN EFFECT
The halo effect is a phenomenon where our overall impression of a person, product, or entity influences how we feel about their various characteristics, often without any logical basis. Essentially, if we like one particular aspect of something, we tend to have a favorable view of everything else related to it. For example, if users find an app visually appealing the first time they use it, they might overlook minor usability issues because their initial positive impression creates a "halo" that makes everything else about the app seem better.
Conversely, if their first interaction is negative, they might continue to view the app negatively, even if it improves. This is called the horn effect and it shows how powerful and lasting a first impression can be in shaping user perceptions.
CONFIRMATION BIAS
Confirmation bias is a phenomenon where people tend to favor information that confirms their existing beliefs or hypotheses, often disregarding conflicting evidence. This cognitive bias is present in various aspects of life, including design and user experience development.
It can lead designers to misinterpret the reasons behind user behavior or product performance issues. For example, suppose a designer is convinced that a website's performance issue is due to its slow loading speed. They might focus solely on optimizing images and scripts, interpreting any slight improvements in speed as confirmation that they were correct.
However, the real issue might be poor navigation design, which isn't addressed because the designer was focused on load times. This oversight can prevent the real problem from being resolved, affecting the user experience negatively.