Three UX Laws That Optimize Information Seeking

Information architecture outline aside an illustration of a web page. The outline shows a parent of fruit with two children: apples and melons. The apples branch has three children: Pink Lady, Envy, and Honeycrisp. The melons branch has one child: Sugar Kiss. The web page illustration shows a long passage of fake content with a headline that reads 'apples.' A sidebar shows three navigation items from the apples branch of the outline.

The fundamental purpose of information architecture is to enable efficient information retrieval. We accomplish this with meaningful information structure and intuitive labels. And we bring them together with sensible navigation design.

The process must accommodate humans (information seekers) and computers (search engines). To do this, we need to understand how each processes information.

Search engine algorithms are quite complicated, and I won’t get into that here. In this piece my focus is on human beings. But these fundamentals will also have a positive impact on search engines.

UX Laws

Some designers reference a set of “UX laws.” These are principles and biases known to psychologists and human behavior specialists. Three of these laws apply well to IA: Law of Proximity, Hick’s Law, and Selective Attention.

Law of Proximity

This comes from the Gestalt school of psychology. It suggests that when we see objects in proximity, we identify them as a group by default.

The principle it creates for IA: group for efficient information indexing.

Hick’s Law

Also referred to as “Hick–Hyman Law,” Hick’s Law was part of a study in 1952 by psychologists William Hick and Ray Hyman. It demonstrates a parallel between the time we need to make a decision and the volume/complexity of choices.

The principle it creates for IA: simplify choices to reduce cognitive load.

Selective Attention

This is the process of focusing our attention only on a subset of an array of stimuli. It’s inspired by Donald Broadbent’s “Filter Model” and E.Colin Cherry’s “Cocktail Party Effect.” The Filter Model suggests a bottleneck of information, limiting people’s attention. The Party Effect expands that model. It proposes that we selectively attend to some information, while leaving the rest unattended.

The principle it creates for IA: isolate choices to improve focus and reduce cognitive load.

Applying the Principles

So, we have group, simplify, and isolate. Let’s visualize how these apply to information architecture, specifically in the context of a navigation system.

A grid of 70 boxes with ten columns and seven rows, each with its own label of a type of fruit. They are all gray.
Fig 1

The grid in Fig 1 represents a flat/unstructured information set of 70 fruit varieties. In the context of a website this translates as 70 links to 70 pages. So we have some work to do to streamline the information-seeking process.

Referencing our list of principles we can begin with Law of Proximity to group our fruits:

A grid of 70 boxes with ten columns and seven rows, each with its own color and label. Columns one through four are green with the names of apples. Column five is purple with the names of melons. Columns six through eight are gold with the names of oranges. Columns nine and ten are red with the names of berries.
Fig 2

This alone is a big leap towards digestibility. Fig 2 represents how we group our information into smaller segments. Instead of 70 fruits we now have 4 groups of fruits: apples, melons, oranges, and berries.

While we’ve made great strides, we still have 70 links to 70 pages. Our brains will use excessive cognitive energy to process this. So we need to build a navigation model that references Hick’s Law. This helps us simplify how many choices are available:

Grid of four boxes, each with its own color and label: apples in green, melons in purple, oranges in gold, and berries in red.
Fig 3

Fig 3 demonstrates how we minimize the 4 groups of 70 pages by consolidating each group into a single data point. As a navigation structure this reduces our total choices from 70 to 4: a 94% reduction in choices!

This system presents content in layers, displaying one segment at a time. The four category labels serve as efficient pre-filters. It’s clear that “melons” will lead to information about varieties.

Once we’ve targeted a group, we can use Selective Attention to isolate an information set:

A grid with one large box aside seven smaller boxes taking up the same height. The large box represents a passage of text with the headline 'melons.' The small boxes represent a navigation list with the names of seven types of melons.
Fig 4

Apples, oranges, and berries can remain unattended while we focus on melons. But they’re still within reach as a simplified set of labels (Hick’s Law), with their varieties tucked away in their own isolated navigation sets. I call this “local navigation,” meaning it’s localized to the content in the immediate branch of the IA.

Conclusion

Navigation design and information architecture must work together to reduce friction. This system makes large volumes of information digestible and focused. It’s designed to remove clutter and decrease cognitive load.

Understanding these three principles will help you pave simple paths for information seekers.

(This updated article was originally published on UX Collective’s Bootcamp.)

#InformationArchitecture #IA #Navigation #Design #UXLaws #UX #Psychology

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I’m Mark Wyner, an activist, dad, husband, Designer, writer, public speaker, and Mastodon moderator. If you want me to write for you or speak at your event please say hello.