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Praveen Manchi
Journal№ 08
  • UX Laws
  • Interaction Design
  • Information Architecture
By Praveen Manchi · Feb 07, 2026 · 6 min

Hick's Law: How to Speed Up User Decisions Through Design

A 2000 grocery-store study found 24 jam varieties converted at 3% while 6 varieties converted at 30% - a textbook demonstration of Hick's Law. Here's how decision time scales with choice count, and how to design around it.

Hick's Law: How to Speed Up User Decisions Through Design

Hick's LawDecision Time

  1. The Jam Study

    Iyengar and Lepper found 3% of shoppers bought from a 24-jam table versus 30% from a 6-jam table - ten times the conversion.

  2. Logarithmic Cost

    T = a + b x log2(n + 1): decision time grows with the logarithm of the number of choices, adding a real, measurable cost.

  3. Group Before Listing

    Twenty items in four labelled categories of five let users skip whole branches by reading one label.

  4. One Primary Action

    Cap navigation at five to seven items, make one action dominant per screen, and mark a recommended option for hesitant users.

[ DECISION MODEL ]

More choices mean slower decisions

Hick's Law (the Hick-Hyman Law) says decision time increases with the number and complexity of choices. Grouping, progressive disclosure and recommended defaults cut apparent choice without cutting capability - most critical in checkout, sign-up and navigation.

  1. See options - n choices
  2. Scan - compare each
  3. Hesitate - grows with log2(n+1)
  4. Decide or leave
On this page

What Is Hick's Law?

In 2000, researchers Sheena Iyengar and Mark Lepper set up a tasting table in a California grocery store. On one day shoppers saw 24 flavours of jam; on another, just 6. The 24-jam table drew more browsers, but only 3% of them bought a jar. At the 6-jam table, 30% did - ten times the conversion, from a quarter of the options.

That result is a real-world demonstration of Hick's Law (formally the Hick-Hyman Law): the time it takes to make a decision grows with the number and complexity of the choices on offer. William Hick documented the relationship in 1952 in "On the Rate of Gain of Information"; Ray Hyman extended it in 1953 with "Stimulus Information as a Determinant of Reaction Time." The formula - T = a + b × log₂(n + 1), where T is decision time and n is the number of choices - comes from information theory, not guesswork.

"The time it takes to make a decision increases with the number and complexity of choices." - Laws of UX

Why Designers Must Care

  • Navigation menus with a dozen top-level items force scanning, comparing, and second-guessing before a user commits to a click.
  • Product pages with several competing calls to action produce hesitation - and hesitation on the web usually ends in leaving, not deciding.
  • Onboarding flows that expose every setting on day one slow first-time users down before they've seen any value.

How to Apply Hick's Law

  • Cap primary navigation. Five to seven top-level items is a reliable range; push depth into progressive disclosure rather than a flat, wide menu.
  • One primary action per screen. If there's only one thing a user should do next, make it visually dominant and unambiguous.
  • Group before you list. Twenty items sorted into four labelled categories of five let users skip whole branches by reading one label.
  • Mark a recommended option. "Most popular" pre-decides for hesitant users without removing choice for anyone else.
  • Stagger complexity. Introduce advanced features after the basics are working, not in the same screen.

Real-World Examples

Apple's original Siri Remote for Apple TV (2015) shipped with about half a dozen buttons and a trackpad, in place of the dense button grid found on a typical universal remote. Fewer controls meant less scanning and fewer wrong presses. Google's homepage takes the idea further: one input field on an otherwise empty page removes every competing decision before the user has typed a character.

Key Takeaways

  • More choices mean slower decisions and a higher risk of no decision at all - Iyengar and Lepper's jam study put a number on it: 3% versus 30%.
  • Grouping and categorisation reduce apparent choice without cutting capability.
  • A recommended default speeds up hesitant users without constraining anyone else.
  • Apply Hick's Law hardest where abandonment is most expensive: checkout, sign-up, and primary navigation.

References & Further Reading