Over the years, psychology has proven to have effective research methods that help to explore and describe human behavior. There is a set of rules that every designer should know because that define how people perceive and interact with digital products. So here we present you 5 laws every UX designer should be aware of.
- Pareto’s Law: define that 80% of the consequences occur from 20% of the causes. It is used to illustrate that things are never equal and the minority often owns the majority. Focus the majority of effort on the areas that will bring the largest benefits to the most users.
- Fitt’s Law: Fitt’s Law states that the time required to acquire a target is a function of the distance to and size of the target. The longer the distance and the smaller the target’s size, the longer it takes to acquire the target.
- Pavlovian Law: Ivan Pavlov researched how stimulus and reaction works. His principle can be applied as a UX law to help enhance navigation. It can help choose the right color for the buttons and sections that need more attention. For example by making the CTA button red you are more likely to get the desired reaction
- Hick’s Law: The time it takes to make a decision increases with the number and the complexity of choices. Many designers think that they’re improving user experience by offering lots of choices, but the real thing is that they will face decision paralysis. Minimize choices to drive decision-making by breaking down complex tasks into smaller steps and Avoid overwhelming users by highlighting recommended options.
- Tesler’s Law: Larry Tesler realized that the way users interact with applications was just as important as the application itself. This theory is also known as the law of conservation of complexity and states that for any system there is a certain amount of complexity that cannot be reduced. A key objective for designers is to reduce complexity for the people that use the products and services we help to build, yet there is some inherent complexity in every process. Inevitably we reach a point at which complexity cannot be reduced any further but only transferred from one place to another.