Behavior Patterns Articles & Videos

  • Reciprocation: Why Login Walls Aren’t Always “Better"

    The reciprocity principle states that people, when given something upfront, tend to feel a sense of obligation to repay what has been provided. Login walls reverse this sequence and require users to disclose personal info before allowing access to content. People often resent this, and may not be as forthcoming or cooperative as a result.

  • Repeated User Actions Are Frustrating

    It's frustrating for users to go back-and-forth and back-and-forth to the same web page, bouncing around without getting what they need. Analytics data can help identify pages that don't help users progress.

  • Love at First Sight in Eyetracking

    When users search for information, they don't always keep looking for the best solution. In our eyetracking studies 20% of the time, users make do with the first result and don't look any further.

  • Dangerous UX: Consequential Options Close to Benign Options

    Confirmatory and destructive actions should be far apart from each other; use additional redundant visual signals to differentiate between them and avoid user errors.

  • Abandoning Best Practices in UX

    When should one abandon best practices in user experience, and what does it take to declare that something is a best practice?

  • 5 Types of E-commerce Shoppers

    Extensive user research with people shopping online identified 5 main types of behavior: product-focused, browsing, researchers, bargain-hunters, and one-time shoppers. Each user type benefits from different UX elements.

  • Compensatory vs Noncompensatory: 2 Decision-Making Strategies

    Ease users’ purchase decisions by designing interfaces that support both compensatory and noncompensatory decision-making strategies.

  • COVID-19 Has Changed Your Users

    People’s behaviors and preferences have shifted. Research will help you figure out how your users have changed and how your designs need to adapt.

  • Changes in Important Information-Seeking Behavior on the Internet Over 22 Years

    We studied the most important activities users perform on the internet, repeating an old classic study. Users' most critical behaviors have shifted substantially over 22 years, due to more information available online and the constant presence of mobile devices.

  • Video Game Engagement vs Addiction

    An engaging gameplay experience is good design. But there's a fine line between engagement and addiction, which would be bad UX, especially in the long term.

  • Different Information-Seeking Tasks: Behavior Patterns and User Expectations

    Fact-finding tasks were less memorable, while complex research-based tasks required more effort from users. Top user expectations for each task type varied.

  • Passive Information Acquisition on the Increase

    People increasingly discover critical information online without actively searching for it, but such information has poor context and may have credibility issues.

  • Teenage Users Compared to Other Age Groups

    Age groups differ in how they use websites, the internet, and computers. Our findings from studying teenagers are contrasted with our other user research with children and adults: user experience designers should target their designs based on target audience behavior patterns.

  • The Pinball Pattern of Scanning Search Results Pages

    Today, a SERP (search engine results page) contains so many design elements that users don't have a simple way of picking out their preferred link. Eyetracking studies show that users' eyes bounce around the page between items in a scan pattern that resembles a pinball machine game.

  • Slips vs. Mistakes

    User errors while using computers take two forms: slips (right intent, wrong action) and mistakes (wrong intent). Understanding the differences between the types of user error will help you design to prevent or minimize these problems.

  • Bounces vs Exits in Web Analytics

    It's important to study why users leave websites. Analytics tools give you two metrics for web pages: exit rate and bounce rate. Understanding the difference between these two numbers is essential for better UX design.

  • Choice Overload Impedes User Decision-Making

    Too many offerings (e.g., products or services) on a website make it harder for users to make a decision due to analysis paralysis. Alternatively, too many options can also cause users to hastily make a decision and later regret their choice due to buyer's remorse.

  • How Information-Seeking Behavior Has Changed in 22 Years

    We organize online information-seeking activities that lead to important decisions and actions according to 5 dimensions: purpose, method, content, social interaction, and device used to carry out the activity.

  • Mental Models for Cloud-Storage Systems

    Users have a rudimentary understanding of cloud services and attempt to fit them into their existent, simpler mental models that they had formed for similar, more-traditional services.

  • Complex Search-Results Pages Change Search Behavior: The Pinball Pattern

    Because today’s search-results pages have many possible complex layouts, users don’t always process search results sequentially. They distribute their attention more variably across the page than in the past.

  • Reciprocation: Why Login Walls Aren’t Always “Better"

    The reciprocity principle states that people, when given something upfront, tend to feel a sense of obligation to repay what has been provided. Login walls reverse this sequence and require users to disclose personal info before allowing access to content. People often resent this, and may not be as forthcoming or cooperative as a result.

  • Repeated User Actions Are Frustrating

    It's frustrating for users to go back-and-forth and back-and-forth to the same web page, bouncing around without getting what they need. Analytics data can help identify pages that don't help users progress.

  • Love at First Sight in Eyetracking

    When users search for information, they don't always keep looking for the best solution. In our eyetracking studies 20% of the time, users make do with the first result and don't look any further.

  • Abandoning Best Practices in UX

    When should one abandon best practices in user experience, and what does it take to declare that something is a best practice?

  • 5 Types of E-commerce Shoppers

    Extensive user research with people shopping online identified 5 main types of behavior: product-focused, browsing, researchers, bargain-hunters, and one-time shoppers. Each user type benefits from different UX elements.

  • Changes in Important Information-Seeking Behavior on the Internet Over 22 Years

    We studied the most important activities users perform on the internet, repeating an old classic study. Users' most critical behaviors have shifted substantially over 22 years, due to more information available online and the constant presence of mobile devices.

  • Video Game Engagement vs Addiction

    An engaging gameplay experience is good design. But there's a fine line between engagement and addiction, which would be bad UX, especially in the long term.

  • Teenage Users Compared to Other Age Groups

    Age groups differ in how they use websites, the internet, and computers. Our findings from studying teenagers are contrasted with our other user research with children and adults: user experience designers should target their designs based on target audience behavior patterns.

  • The Pinball Pattern of Scanning Search Results Pages

    Today, a SERP (search engine results page) contains so many design elements that users don't have a simple way of picking out their preferred link. Eyetracking studies show that users' eyes bounce around the page between items in a scan pattern that resembles a pinball machine game.

  • Slips vs. Mistakes

    User errors while using computers take two forms: slips (right intent, wrong action) and mistakes (wrong intent). Understanding the differences between the types of user error will help you design to prevent or minimize these problems.

  • Bounces vs Exits in Web Analytics

    It's important to study why users leave websites. Analytics tools give you two metrics for web pages: exit rate and bounce rate. Understanding the difference between these two numbers is essential for better UX design.

  • Choice Overload Impedes User Decision-Making

    Too many offerings (e.g., products or services) on a website make it harder for users to make a decision due to analysis paralysis. Alternatively, too many options can also cause users to hastily make a decision and later regret their choice due to buyer's remorse.

  • The Negativity Bias in a User's Experience

    Negative experiences have stronger emotional impact on humans than positive experiences do. Thus, in designing the user experience, we need extra emphasis on avoiding those lows.

  • Changes in How Senior Citizens Use Computers

    Our new user research with seniors (users aged 65 and up) shows 3 major shifts in how they use computers, compared with our first research with this audience, 20 years ago. Design for today's older users, and not for your stereotype of how these users used to be.

  • Change Blindness in User Interfaces

    Change blindness is the tendency for people to overlook things that change outside their focus of attention. In user interface design, this explains why screen changes that seem striking to the designer can be completely ignored by users.

  • Why Users Feel Trapped in Their Devices: The Vortex

    Many users report anxiety and lack of control over the amount of time they spend online. We call this feeling “the Vortex.”

  • Hick's Law: Designing Long Menu Lists

    Hick's Law (or the Hick–Hyman Law) says that the more choices you present to your users, the longer it takes them to reach a decision. However, combining Hick’s Law with other design techniques can make long menus easy to use.

  • Page Parking: Multi-Tab Obsession Common Among Millennials

    People open numerous tabs in rapid succession as a strategy to save time. The tabs serve as a memory aid.

  • Banner Blindness: Ad-Like Elements Divert Attention

    Recent eyetracking studies confirm an old finding: People tend to ignore design elements that signal advertisements.

  • F-Pattern in Reading Digital Content

    Eyetracking research shows people read Web content in the F-pattern. The results highlight the importance of following guidelines for writing for the Web.

  • The Distribution of Users’ Computer Skills: Worse Than You Think

    Across 33 rich countries, only 5% of the population has high computer-related abilities, and only a third of people can complete medium-complexity tasks.

  • The Negativity Bias in User Experience

    People remember the bad more than the good. Users’ tendency to identify flaws in designs raises the bar for what they consider acceptable.

  • Prospect Theory and Loss Aversion: How Users Make Decisions

    When choosing among several alternatives, people avoid losses and optimize for sure wins because the pain of losing is greater than the satisfaction of an equivalent gain. UX designs should frame decisions accordingly.

  • Computer-Assisted Embarrassment

    Computer systems shouldn't make us feel bad. But they often do. Contextual usability methods can help discover social defects in user experience.

  • Millennials as Digital Natives: Myths and Realities

    As the new largest generation in the American workforce, Millennials are subject to rampant speculation, investigation, and even some moral panic. These young adults have high expectations about user interfaces and are confident in their skills, but they’re error prone and their tendency to multitask reduces their task efficiency.

  • Long-Term Exposure to Flat Design: How the Trend Slowly Decreases User Efficiency

    Clickable UI elements with absent or weak visual signifiers condition users over time to click and hover uncertainly across pages — reducing efficiency and increasing reliance on contextual cues and immediate click feedback. Young adult users may be better at perceiving subtle clickability clues, but they don’t enjoy click uncertainty any more than other age groups.

  • Page Parking: Millennials' Multi-Tab Mania

    Browser tabs separate the stages of collection and comparing and serve as memory aids to keep many alternate pages available for consideration as users are shopping or researching. 7 UX guidelines support this user behavior, which is particularly common among younger users.

  • Why Designers Think Users Are Lazy: 3 Human Behaviors

    Do you ever think your users are lazy, or maybe even a little bit dumb? Device Inertia, momentum behavior, and selective attention are common behaviors that can make users seem slothful. However, interface design, not deficient user effort, is the true cause for these error-prone user paths.

  • The Fold Manifesto: Why the Page Fold Still Matters

    What appears at the top of the page vs. what’s hidden will always influence the user experience — regardless of screen size.

  • Designing for 5 Types of E-Commerce Shoppers

    Considering e-commerce shoppers’ motivations and habits when they come to a site can help designers make decisions that improve overall site usability while supporting users’ needs.

  • User Expertise Stagnates at Low Levels

    Learning is hard work, and users don't want to do it; they don't explore the user interface and don't know about most features.

  • Internet Activity Bias Causes Lumpy User Behavior

    Dramatic differences in how much people use the web on different days can distort simplistic interpretations of site analytics.

  • College Students on the Web

    Students are multitaskers who move through websites rapidly, often missing the item they come to find. They're enraptured by social media but reserve it for private conversations and thus visit company sites from search engines.

  • Velocity of Media Consumption: TV vs. the Web

    The granularity of user decisions is much finer on the Web, which is dominated by the instant gratification of the user's needs in any given instant. Content must cater to this rapid pace.

  • How Little Do Users Read?

    On the average Web page, users have time to read at most 28% of the words during an average visit; 20% is more likely.

  • Middle-Aged Users' Declining Web Performance

    Between the ages of 25 and 60, people's ability to use websites declines by 0.8% per year - mostly because they spend more time per page, but also because of navigation difficulties.

  • Life-Long Computer Skills

    Schools should teach deep, strategic computer insights that can't be learned from reading a manual.

  • Digital Divide: The 3 Stages

    The economic divide is a non-issue, but the usability and empowerment divides alienate huge population groups who miss out on the Internet's potential.

  • Variability in User Performance

    When doing website tasks, the slowest 25% of users take 2.4 times as long as the fastest 25% of users. This difference is much higher than for other types of computer use; only programming shows a greater disparity.

  • Users Interleave Sites and Genres

    When working on business problems, users flitter among sites, alternating visits to different service genres. No single website defines the user experience on its own.