How to Use Pareto’s Law in UI/UX Design

UX/UI design is often seen as just some kind of craft that helps businesses present their services and products. Professional UX/UI design companies focus on delivering business value to startups and large corporations worldwide. While that is, of course, partially true, UX/UI design is also a science and a philosophy of life. It uses the discoveries of phycology, economy, logic, and other scientific fields to present a whole new way of thinking and seeing the world.

One of the ideas that were adopted by designers was the Pareto law, and in this post you will learn how to apply it in industrial UX/UI design.

A Bit of History

In 1906, Vilfredo Pareto, an Italian economist, discovered that 20% of the pea pods in his garden produced around 80% of the entire yield each year. Not only did he find this fascinating, but he decided this outcome could be applied to many circumstances.  For example, there is an uneven but predictable distribution of wealth throughout society in the economy. 80% of the wealth and income belongs to only 20% of the population. 

On the subject of design, this same concept can be applied. 20% of the effort you make will give you 80% of the results. For example, let us look at the Internet surfing experience. Do users browse through every webpage on the website or visit only the most relevant and interesting ones?

Moreover, as a rule, people use only part of the functions of the websites, applications, and other products that they consider the most useful. In web design, visitors use only 20% of the functionality offered by the site. Now let us discuss how to emphasize the most important functions with the help of this law. You will also learn how to understand what functionality works efficiently and what doesn’t work at all. 

How to Emphasize the Main Functions of the Site Using Pareto’s Law

The main principle of Pareto’s law is to get rid of the excess. These are some techniques that will help you do it:

When analyzing your audience, you will understand their needs. Once you know your audience’s needs, you can create a ranking to satisfy their needs in the most favorable light.

  • Create a website that only highlights the main points. Your forms should have very few questions. Give potential customers the ability to save time. Customers, in general, want their address and, in some cases, their card number already in place, so they do not have to manually fill in that information over and over when they want to make a purchase.
  • When designing your site, keep it simple to make the customer’s experience positive.  In turn, this will affect the SEO indicators of your site, conversion rates, and the overall image of your company. You will find visitors will stick around for more extended periods, which will attract search engines.

Keep in mind; the more extended customers stick around, the higher the chances are for targeted action.  Well-designed sites are recognized on the internet and win the trust of internet users.

How to Determine 20% of the Effort

Outside of determining the needs of your targeted audience, you need to capture character. It’s highly recommended to use statistical tools such as Google Analytics to learn what areas of your site are the most frequented. Using Pareto’s Law effectively you can also conduct split testing. Using the A/B test will reveal the differences between two different versions of sites with different designs, so that you can understand which option works more efficiently.

The third type of testing, and one of the most effective ones, is usability testing. This lets users determine whether it’s convenient to use your site, whether all the buttons work, or whether the mobile version of the web resource is displayed correctly. This will give you accurate results from your audience.


Pareto’s Law is a practical approach to apply to UI/UX design. This principle can be expressed in as little as one sentence – it allows users to use less effort to get the results they are looking for.

Using this law will allow you to determine which functions are not as effective as expected, and which deliver the best result. This can be achieved through testing and continual trial.


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