Cognitive Bias
A systematic pattern of deviation from norm or rationality in judgment.
Cognitive Biases are systematic patterns of deviation from norm or rationality in judgment. They are mental shortcuts that the brain uses to process information quickly and efficiently. While these shortcuts are useful for fast decision-making, they can lead to errors and distorted perceptions of reality.
In User Experience (UX) design, understanding cognitive biases is crucial because they profoundly influence how users perceive, interact with, and make decisions about digital products. A good UX designer anticipates and accounts for these biases to create interfaces that are clear, persuasive, and user-friendly.
Why Biases Matter in UX
Cognitive biases can dictate many aspects of a user's interaction:
Perception of Value: Biases affect whether a user thinks a product is worth the price or the effort to use.
Navigation & Discovery: They influence what users pay attention to on a screen and which paths they choose to take.
Trust & Credibility: Biases shape how quickly a user trusts a website, app, or piece of information presented to them.
Decision-Making: They drive choices, from clicking a specific button to completing a purchase.
By intentionally designing with these biases in mind, you can guide users toward desired actions, minimise friction, and create a more satisfying experience.
Anchoring Bias
The tendency to rely too heavily on the first piece of information offered (the "anchor") when making decisions.
Example: Show a high original price (the anchor) struck out next to a lower sale price to make the sale price seem like a much better deal.
Confirmation Bias
The tendency to search for, interpret, favour, and recall information in a way that confirms or supports one's prior beliefs or values.
Example: In search or filtering, showing results or suggestions that align with a user's past behaviour or stated preferences (e.g., "People who bought this also bought...").
Loss Aversion
The psychological tendency for losses to have twice the impact on people as equivalent gains. People prefer avoiding losses over acquiring equivalent gains.
Example: Framing features as things a user will lose if they cancel a service ("Don't lose access to...") rather than things they will gain if they sign up.
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