What is cognitive bias?

We are bombarded with millions of bits of information every day. Owing to evolution, our brains have learned to take shortcuts to understand and process this information efficiently. Cognitive bias refers to these mental shortcuts or systematic patterns of deviation from rationality in judgement and decision-making.

While cognitive biases help us make decisions more quickly, their fault lies in the fact that they are often based on hunches and incomplete information. For example, when someone hears that 1 in 10 people could be allergic to something, they tend to consider themselves in the unaffected 9 unless proven otherwise. This is a result of cognitive bias known as the "optimism bias."

Our brains are prone to cognitive biases because they help us process information efficiently. Without these biases, we'd spend an unimaginable amount of time trying to make simple decisions. However, it is essential to understand how false assumptions could influence design decisions and lead to suboptimal user experiences.

Impact of designer's cognitive bias

The process of UX design is a lengthy one, with different stages where bias could seep in. For instance, during the UX research phase, designers may encounter availability bias. This bias occurs when we rely on immediate examples that come to mind when evaluating a topic or decision, rather than considering all relevant information.

Imagine that during research, a designer comes across two users requesting a certain feature. The designer might conclude that this feature is important and requested by most users, when in reality, that is not the case. This could lead to misguided design decisions based on incomplete data. 

This is Availability bias at play. According to Wikipedia, availability bias is a cognitive bias in which we rely on immediate examples that come to our mind when evaluating a specific topic, concept, method or decision.

As a designer, if you allow cognitive biases to influence your product design process, the resulting product may no longer be optimised and might fail to meet stakeholder goals or user needs.

Now that we know how a designer’s cognitive bias could impact the product design process, let us also understand why, as a designer, you need to consider your users’ biases when designing.

Addressing user’s cognitive bias

While designers can work to circumvent their cognitive biases, it would be unrealistic to expect users to do the same. As such, it is crucial to consider potential user biases when designing products.

One common bias is familiarity bias, which states that people trust what they're familiar with. If a product offers an experience that deviates too far from industry norms, users may experience low adoption rates and high drop-off rates due to unfamiliarity.

However, designers can also leverage biases to benefit users and stakeholders. For instance, the principle of least effort suggests that when faced with multiple options, people tend to choose the option that requires the least effort. By offering a streamlined solution to users' problems without lengthy onboarding processes, designers can leverage this bias to increase product adoption rates.

We’ve only talked about 3 biases so far and the importance of identifying and leveraging them during the product design process. Further, we expand on a few more common biases.

List of common cognitive biases

Social proof

Social proof derives from a deeply rooted psychological bias. It implies that people tend to make decisions based on the choices of others, believing that the majority knows best. In Ecommerce products, social proof can be leveraged through customer reviews, testimonials, and displaying the number of users or customers.

For instance, Every product has a customer review section, which shows the general sentiment of people who have bought the product. It also displays the number of people who have reviewed the product.

Anchoring effect

This bias refers to people's tendency to base decisions on a reference point or "anchor." The anchoring effect refers to the cognitive bias wherein an individual’s decisions are based on a reference point or an anchor.

A great example of anchoring bias is seen during the checkout process of some food delivery apps. The payment phase always has an option to tip your delivery person, and there’s often a default amount mentioned in the payment tab. This leads people to base their tips off of this anchor in the app.

In the example above, ‘Most Tipped’ acts as an anchor. You’ll also notice this when buying gift cards online.

Bandwagon effect

Also known as herd behaviour, is a cognitive bias that occurs when people tend to adopt certain beliefs or behaviors because they perceive that others are doing the same. In the context of SaaS (Software as a Service) or e-commerce products, the bandwagon effect can be leveraged to influence consumer behaviour and drive product adoption. This is the reason companies like to show off their partner companies or testimonials on the homepage to convince potential users to try their products.

Scarcity effect

This bias refers to people's tendency to attach higher value to limited or scarce things. The Scarcity Bias is much more common than you may think. Whether it's concert tickets for your favourite artist, a popular brand of running shoe or a limited-edition collectible, when you think something is scarce, you tend to see it as more valuable. In Ecommerce products, this can be leveraged through time-limited sales or offers.

Conclusion

Cognitive biases can have a profound impact on the product design process and user experiences. As designers, it is crucial to identify and mitigate the influence of our own biases while also considering the potential biases of users.

By understanding common biases like availability heuristic, social proof, anchoring effect, and more, designers can create user-centric solutions that resonate with their audience while avoiding pitfalls caused by unconscious biases. Continuously evaluating design decisions through the lens of cognitive biases can lead to more informed and effective product design choices, ultimately resulting in better user experiences and increased product adoption.

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