PHILIP BURGESS

User experience (UX) research relies heavily on understanding how users feel about a product or service. One of the most common tools to capture these feelings is the Likert scale. This simple yet powerful method helps researchers quantify attitudes, preferences, and perceptions, making it easier to analyze user feedback. This post explores what Likert scales are, how they work, and why they are essential in UX research. Likert Scales What is a Likert Scale? A Likert scale is

User experience (UX) metrics guide teams in understanding how users interact with products and services. But how often should teams review these metrics? Monthly or quarterly? The answer depends on the goals, product lifecycle, and the type of data collected. This post explores the benefits and drawbacks of both approaches and offers practical advice on what UX metrics teams should focus on to make informed decisions. Monthly vs. Quarterly UX Metrics Why Frequency Matters in

User experience (UX) plays a crucial role in shaping how people interact with digital products. To improve UX, teams rely on data that reveals how users behave, feel, and respond. But understanding this data starts with knowing the difference between a UX metric and a UX measurement tool . These terms are often used interchangeably, yet they refer to distinct concepts that serve different purposes in the design and evaluation process. This post explains what sets UX metrics

Every business wants to improve its products and services, but few realize how much value user experience (UX) research can bring. UX research uncovers how real users interact with a product, revealing pain points and opportunities for improvement. The question many leaders ask is: What is the return on investment (ROI) of UX research? This post explores how UX research delivers measurable benefits that directly impact a company’s bottom line. Quantifiable ROI of UX Research

Customer Satisfaction Score (CSAT) is often seen as a quick and easy way to measure how users feel about a product or service. Many teams rely heavily on CSAT to judge the success of their user experience (UX) efforts. While CSAT provides useful insights, it does not tell the full story. Relying on CSAT alone can lead to misleading conclusions and missed opportunities for improvement. This post explains why CSAT is not enough by itself and explores other important metrics and

When it comes to creating a seamless user experience, understanding how users feel about your product is crucial. But how do we measure that feeling? Enter CSAT metrics in UX design —a powerful tool that helps us quantify user satisfaction and make informed decisions to improve our designs. In this post, we'll explore how CSAT metrics can transform your UX process, making it more user-centered and data-driven. Why CSAT Metrics Matter in UX Design User experience is all about

User experience (UX) research aims to understand how people interact with products and services to improve satisfaction and usability. One tool that often appears in this field is the Net Promoter Score (NPS). While NPS is widely used to measure customer loyalty, its role in UX research is sometimes misunderstood or underestimated. This post explores what NPS really means for UX research and how it can shape the way we design better experiences. NPS What is NPS and How Does I

Customer Satisfaction Score (CSAT) is a key metric that measures how satisfied customers are with a product, service, or experience. It provides direct feedback from users, helping businesses understand whether they meet expectations. For UX researchers, CSAT offers valuable insights that influence design decisions and improve user experience. This post explores what CSAT is, why it matters, and how it interacts with UX research to create better products. CSAT What Is CSAT an

User experience (UX) research aims to understand how people interact with websites and apps to improve usability and satisfaction. One powerful tool in this process is clickstream analytics . By tracking the sequence of clicks users make, clickstream analytics reveals detailed patterns of behavior that help UX researchers identify pain points, optimize navigation, and design better digital experiences. This post explains what clickstream analytics is, how it works, and why it

User experience (UX) research relies on clear, reliable ways to measure how users feel about a product or service. One tool that has gained attention for its effectiveness is the SUPR-Q, or Standardized User Experience Percentile Rank Questionnaire. This post explains what the SUPR-Q is, how to measure it, and how UX professionals can use it to improve digital experiences. SUPR-Q survey What is the SUPR-Q? The SUPR-Q is a concise questionnaire designed to measure users’ perce

User experience (UX) research aims to uncover how people interact with products and services, revealing what works well and what needs improvement. One powerful tool in this process is the Single Ease Question (SEQ). This simple yet effective question helps researchers capture users’ immediate impressions of a task’s difficulty. Understanding SEQ’s role can transform how teams interpret user feedback and make design decisions. SEQ What is SEQ and Why It Matters The Single Eas

User experience (UX) research aims to create products that are easy and enjoyable to use. One key measure in this process is the error rate . Understanding what error rate means and why it matters can help designers and researchers improve usability and create better experiences for users. Understanding Error Rate What Is Error Rate in UX Research? Error rate refers to the number of mistakes users make while interacting with a product, divided by the total number of opportuni

When users interact with a product or service, the time they spend completing specific tasks reveals a lot about the design’s effectiveness. This measure, known as time on task , plays a crucial role in UX research. It helps designers and researchers understand how easily users can achieve their goals, identify pain points, and improve overall user satisfaction. This post explains what time on task means, how it applies to UX research, and why it deserves your attention. Unde

User experience (UX) research aims to create products that are easy and satisfying to use. One key measure in this process is the Task Success Rate (TSR) . It tells us how well users can complete specific tasks when interacting with a product or service. Understanding TSR helps designers and researchers identify usability issues and improve the overall user experience. Task success rate What Is Task Success Rate in UX Research? Task Success Rate is a metric used to evaluate t

User experience (UX) research often focuses on understanding users and improving product design. Yet, one critical factor that can determine the success of UX efforts is how well stakeholders are engaged throughout the process. Measuring stakeholder engagement is not just a nice-to-have; it directly impacts the quality of insights, decision-making, and ultimately the product’s success. This post explains why stakeholder engagement metrics matter in UX research and how to use

Research generates valuable insights that can guide product development, marketing strategies, and customer experience improvements. Yet, many organizations struggle to ensure these insights translate into real-world actions. Measuring research reuse is critical to understanding whether teams are actually applying what they learn or if valuable knowledge is left unused. This post explores how to evaluate research reuse and offers practical ways to improve the implementation o

By Philip Burgess | UX Research Leader When I first started working on user experience (UX) design, I quickly realized that delivering a seamless experience across multiple channels and platforms is one of the toughest challenges. Users expect to switch from a mobile app to a website or even a physical kiosk without feeling lost or confused. But how do you measure if your UX is truly consistent? Over time, I developed a practical approach to evaluate UX consistency that I wan

By Philip Burgess | UX Research Leader When I first started working in user experience, I was eager to quantify every insight I gathered. It seemed logical: if something is important, it should be measurable. But over time, I realized that not every UX insight fits neatly into a metric. Some insights lose their meaning or even mislead when forced into numbers. This post shares why some UX insights should remain qualitative and how turning them into metrics can sometimes do mo

By Philip Burgess | UX Research Leader When I first encountered AI confidence scores, I assumed they worked just like the confidence levels I learned about in research studies. It seemed natural to think that a high AI confidence score meant the same thing as a high confidence interval in scientific research. Over time, I realized this assumption was misleading. The two concepts serve different purposes and come from very different processes. Understanding these differences c

Balancing user experience metrics often feels like walking a tightrope. I’ve faced this challenge many times, trying to improve one aspect of a product only to see another suffer. Speed, quality, and satisfaction are key metrics that often pull in different directions. When they conflict, it’s tempting to pick one and ignore the rest, but that rarely leads to the best outcome. Instead, understanding how to navigate these trade-offs can help create a more balanced and effectiv