Deep Diving into Hick's Law: Why Simplicity Matters in Product Design?
Hick's Law underpins the usability elements that are critical for products to establish connection with end user and help them take faster decisions within the product.
In our digital world, filled with sleek apps, endless menus, and one-click conveniences, a subtle psychological principle governs much of what feels intuitive and effortless in user experiences. It's called Hick’s Law—a rule of thumb that has quietly influenced everything from how Amazon structures its menus to how LinkedIn guides users through profile completion.
Yet, despite its frequent name-drop in UX and product circles, Hick’s Law is often misunderstood, oversimplified, or misapplied. It’s commonly reduced to “just show fewer options,” when in reality, it’s about how human brains navigate choice, and how smart design can reduce the cognitive cost of decisions without dumbing things down.
In this article, we’ll take a deep dive into what Hick’s Law really says, why it matters to digital product builders, and how to apply it not dogmatically, but thoughtfully—especially when designing complex interfaces, onboarding flows, or decision-heavy journeys.
🎓 The Real Hick’s Law: A Logarithmic Understanding of Choice
Back in 1952, psychologists William Edmund Hick and Ray Hyman conducted a series of experiments to understand how humans respond to increasing numbers of options. They weren’t designing apps; they were studying reaction time in controlled lab conditions. But their findings laid the groundwork for one of the most enduring ideas in UX design.
They found a logarithmic relationship between the number of choices presented and the time it took for people to make a decision:
RT=a+b⋅log2(N)RT = a + b \cdot \log_2(N)RT=a+b⋅log2(N)
Where:
RT is the reaction time (how long someone takes to decide),
N is the number of choices,
log₂(N) reflects the information content (in bits), and
a and b are constants based on task and context.
What this formula tells us is fascinating: doubling the number of choices doesn't double the decision time. Instead, it increases it incrementally. Why? Because our brains don’t evaluate every choice linearly. We categorize, cluster, dismiss, and prioritize—especially when the information is familiar or structured.
This is a profound insight for design: users aren’t paralyzed by options per se, they’re paralyzed by unstructured, unfamiliar, or meaningless options.
🧩 From Theory to Practice: What Hick’s Law Teaches Product Designers
So, how does a 1950s psychology experiment help us design better websites, apps, and digital flows in 2025?
Hick’s Law is best seen not as a rigid constraint, but as a cognitive lens—a way to anticipate how users might feel when confronted with a set of decisions. It tells us that:
Every choice has a mental processing cost.
That cost accumulates logarithmically.
But we can offset or reduce that cost with smart design choices.
Let’s explore how this plays out.
1. Fewer Options, But With Purpose
The first and most common takeaway from Hick’s Law is to reduce visible options, especially at key decision points like landing pages, sign-up screens, or call-to-action menus.
But it’s not just about fewer items. It’s about fewer distractions, clearer intentions, and higher confidence. A cluttered page overwhelms not because it's long, but because the brain is forced to parse irrelevant options or interpret unclear ones.
💡 Good design asks: “What decision is the user trying to make here?” and removes everything that isn’t in service of that.
2. Progressive Disclosure: Show Less, Reveal More
One of the most powerful UX patterns derived from Hick’s Law is progressive disclosure. This means breaking down complex workflows into step-by-step sequences, only showing the relevant options at each stage.
Think of a multi-step checkout process, or a job application wizard. Users are more likely to complete these flows when they're led one logical step at a time, even if that means more total screens.
🧠 Why it works: it distributes cognitive load and leverages short-term memory more efficiently.
3. Information Architecture: The Power of Categorization
Here’s where Hick’s Law meets information design.
Humans love categories. We’re wired to group things. When you cluster items into categories and subcategories, users can employ what cognitive scientists call a “divide and conquer” strategy. Instead of evaluating 100 choices, the brain scans 5 categories and then 10 items inside one of them. The decision time drops dramatically.
This is why Amazon’s "Shop by Department" model or Spotify’s genre filters work so well. The options are still vast, but you never face the full firehose at once.
🧠 Cognitive load isn’t just about how many choices there are—it’s about how they’re structured and perceived.
4. Language and Labeling: Words as UX Primitives
Even with only three options on a page, if the labels are ambiguous (“Do Stuff”, “More Info”, “Go”), the decision becomes harder.
Hick’s Law is deeply tied to how fast we can comprehend a choice. Labels that are clear, expected, and unambiguous reduce decision time. Those that are clever, technical, or nonstandard increase it.
✍️ Rule of thumb: use the words your users use. Not your team. Not your stakeholders. Your users.
5. Breadth vs. Depth: Rethinking the “3-Click Rule”
There's a myth in UX that “users should be able to get anywhere in 3 clicks.” But Hick’s Law suggests a more nuanced truth: users don’t mind multiple steps, as long as each step is obvious and frictionless.
It’s better to design a shallow, broad hierarchy with clear, predictable choices at each level, rather than a deep tree that hides content behind confusing categories.
Steve Krug (author of Don’t Make Me Think) puts it best: “I don’t mind clicking, as long as each click is a mindless, unambiguous choice.”
🤯 Misunderstandings and Misapplications of Hick’s Law
Like many psychological laws, Hick’s Law can be over-applied or misinterpreted. Let’s bust a few myths.
❌ Myth #1: “Less is always better.”
Truth: Not always. If users know what they’re looking for, they’ll scan a long list fast—especially if it’s ordered alphabetically, numerically, or spatially. Cutting down options can hurt when it hides relevant items behind vague labels or additional clicks.
❌ Myth #2: Hick’s Law = Visual Clutter Management
Truth: Hick’s Law isn’t about aesthetics. It’s about reaction time and decision complexity. Clean design helps, but it’s the cognitive structure, not just the visual layout, that matters most.
❌ Myth #3: Hick’s Law applies uniformly across all users
Truth: Not quite. Reaction time is affected by familiarity, practice, and stimulus-response compatibility. For example, users who use a product daily won’t experience the same delays as new users. Hick’s Law is most relevant at first-use or decision bottlenecks.
🧪 Case Studies: Hick’s Law in Real Products
Let’s examine how Hick’s Law plays out in some real-world systems:
Case Study 1: Amazon's E-commerce Navigation System
Problem: Large e-commerce platforms like Amazon offer an enormous variety of products, leading to a potentially overwhelming number of choices for users. If all available links were presented without structure, users would be "bombarded with choices," potentially causing them to be "stuck in the decision-making process" or even abandon the site.
Hick's Law Application: Amazon addresses this by categorizing choice. Instead of a flat list of every product or category, menu items are organized into high-level categories that "slowly expand as the users select options". This creates a compartmentalized decision-making process where options are kept hidden until they are actually needed. This strategy leverages the understanding that a person's response time increases logarithmically with the number of choices. By minimizing the number of visible choices at any given moment, Amazon applies the "less is better" principle to reduce cognitive load.
Usefulness/Impact: This application simplifies the interface and the shopping process significantly. It helps prevent "choice paralysis" and avoids bombarding users with options, which could intimidate them. By reducing the cognitive stress and competition for the user's attention, it contributes to a more user-friendly and natural experience, making it "much lighter to find the relevant information". This approach is vital for user engagement and conversion rates.
Case Study 2: Online Checkout and Registration Forms
Problem: Digital processes that require multiple steps, such as completing a purchase or registering for an account, can appear very complex and daunting if all fields and options are displayed on a single screen. This can lead to "choice paralysis" and users abandoning the process.
Hick's Law Application (Progressive Disclosure): Designers break down complex processes into smaller, more manageable screens, a technique often referred to as "progressive disclosure" or "obscuring complexity". Instead of one long form, a multi-page series of smaller forms is used, where only the immediately relevant information or actions are presented at each step. For example, a payment process might first prompt for email and password, then show shopping cart details, and then collect delivery information on subsequent screens. The use of a "Completeness Meter" (e.g., for LinkedIn profiles) can also guide users through these steps and reduce friction [Script, uxpin_interaction_design_best_practices, 651].
Usefulness/Impact: This method makes processes feel more user-friendly and less overwhelming. Even though a single long form might theoretically take less total time, the perception of effort is reduced with smaller, paced steps, making it more likely that the user will complete the process and not abandon their action. The goal is to make the interface self-evident, obvious, and self-explanatory at each stage, requiring minimal effort from the user.
Case Study 3: Self-Service Scales in Supermarkets
Problem: Older self-service scales in supermarkets often present a single, flat list of many numbered buttons, each corresponding to a fruit or vegetable. The numerical association is arbitrary and changes frequently, meaning there's "no useful criterion in the arrangement of options" from the user's perspective, leading to a linear (high) decision time.
Hick's Law Application (Splitting Heterogeneous Choices): A more functional model adopted by modern scales applies Hick's Law principles by splitting the choices into two levels. Users first select a general category (e.g., "Fresh Fruit," "Vegetables," "Dried Fruit") from a concise, consistent list. Once a category is chosen, a second-level menu with fewer, more homogeneous items becomes visible. This is a key strategy to "reduce the number and the heterogeneity of the options".
Usefulness/Impact: Even though this introduces more levels to the interaction, it re-establishes a "consistent list" at the first level and reduces the immediate number of options displayed. This allows users to cluster options meaningfully and focus their attention on a subset, leading to a sub-linear (low) time of choice. This approach directly addresses the "paradox of choice" by focusing on the quality of how choices are organized and presented, rather than just the quantity.
Case Study 4: Long, Ordered Menu Lists (e.g., Contact Lists, State Selectors)
Problem: Some applications require displaying inherently long lists of items, such as contact directories, country lists, or lists of states, where minimizing the total number of items is not feasible. A naive application of Hick's Law might suggest these lists would always result in very long decision times.
Hick's Law Application (Contextual Nuance): While Hick's Law generally states that more items lead to longer selection times, there's a critical nuance: if the list is ordered (e.g., alphabetically) and the items are familiar or known to the user, they can be remarkably efficient at scanning. Users don't process each item sequentially; instead, their "eye lands first" and they "adjust their gaze accordingly" to quickly skip over irrelevant content because they know the name and order of the item they're looking for. Steve Krug's "second law of usability" also states that "it doesn't matter how many times I have to click, as long as each click is a mindless, unambiguous choice," implying that the speed of ignoring is key for long, ordered lists.
Usefulness/Impact: This understanding allows designers to effectively utilize long, ordered lists where appropriate, even if they contain many items. It prevents unnecessary design complexity to shorten such lists, acknowledging that users can navigate them efficiently by quickly finding and selecting their desired, known item. This means users are effectively "ignoring the 99 items that aren't my name" to find what they need.
🧩 Summarizing
These case studies demonstrate that Hick's Law is not merely a theoretical formula but a fundamental principle that guides designers in creating intuitive, efficient, and user-friendly products across various contexts. By understanding its implications, designers can strategically simplify decision-making, manage complexity, and ultimately enhance the user experience.
📚 References
Hick, W. E. (1952). On the rate of gain of information. Quarterly Journal of Experimental Psychology, 4(1), 11–26. https://doi.org/10.1080/17470215208416600
Hyman, R. (1953). Stimulus information as a determinant of reaction time. Journal of Experimental Psychology, 45(3), 188–196. https://doi.org/10.1037/h0056940
Krug, S. (2014). Don’t Make Me Think, Revisited: A Common Sense Approach to Web Usability (3rd ed.). New Riders.
Norman, D. A. (2013). The Design of Everyday Things: Revised and Expanded Edition. Basic Books.
Johnson, J. (2020). Designing with the Mind in Mind: Simple Guide to Understanding User Interface Design Guidelines (3rd ed.). Morgan Kaufmann.
Tidwell, J., Brewer, C., & Valencia, A. (2020). Designing Interfaces: Patterns for Effective Interaction Design (3rd ed.). O'Reilly Media.
UXPin. (n.d.). The Ultimate Guide to Interaction Design Best Practices. Retrieved from https://www.uxpin.com/studio/ebooks/interaction-design-best-practices/
Nielsen Norman Group. (n.d.). Progressive Disclosure: Reducing Cognitive Load. Retrieved from https://www.nngroup.com/articles/progressive-disclosure/
Budiu, R. (2015). Organizing Content: Information Architecture Basics. Nielsen Norman Group. https://www.nngroup.com/articles/information-architecture/
Schneiderman, B., Plaisant, C., Cohen, M., Jacobs, S., & Elmqvist, N. (2016). Designing the User Interface: Strategies for Effective Human-Computer Interaction (6th ed.). Pearson.
Iyengar, S. S., & Lepper, M. R. (2000). When Choice is Demotivating: Can One Desire Too Much of a Good Thing? Journal of Personality and Social Psychology, 79(6), 995–1006. https://doi.org/10.1037/0022-3514.79.6.995
Tognazzini, B. (2014). First Principles of Interaction Design (Revised & Expanded). Retrieved from https://asktog.com/atc/principles-of-interaction-design/