UX KPIs for Performance Measurement

⏱️ How To Measure UX (https://lnkd.in/e5ueDtZY), a practical guide on how to use UX benchmarking, SUS, SUPR-Q, UMUX-LITE, CES, UEQ to eliminate bias and gather statistically reliable results — with useful templates and resources. By Roman Videnov. Measuring UX is mostly about showing cause and effect. Of course, management wants to do more of what has already worked — and it typically wants to see ROI > 5%. But the return is more than just increased revenue. It’s also reduced costs, expenses and mitigated risk. And UX is an incredibly affordable yet impactful way to achieve it. Good design decisions are intentional. They aren’t guesses or personal preferences. They are deliberate and measurable. Over the last years, I’ve been setting ups design KPIs in teams to inform and guide design decisions. Here are some examples: 1. Top tasks success > 80% (for critical tasks) 2. Time to complete top tasks < 60s (for critical tasks) 3. Time to first success < 90s (for onboarding) 4. Time to candidates < 120s (nav + filtering in eCommerce) 5. Time to top candidate < 120s (for feature comparison) 6. Time to hit the limit of free tier < 7d (for upgrades) 7. Presets/templates usage > 80% per user (to boost efficiency) 8. Filters used per session > 5 per user (quality of filtering) 9. Feature adoption rate > 80% (usage of a new feature per user) 10. Time to pricing quote < 2 weeks (for B2B systems) 11. Application processing time < 2 weeks (online banking) 12. Default settings correction < 10% (quality of defaults) 13. Search results quality > 80% (for top 100 most popular queries) 14. Service desk inquiries < 35/week (poor design → more inquiries) 15. Form input accuracy ≈ 100% (user input in forms) 16. Time to final price < 45s (for eCommerce) 17. Password recovery frequency < 5% per user (for auth) 18. Fake email frequency < 2% (for email newsletters) 19. First contact resolution < 85% (quality of service desk replies) 20. “Turn-around” score < 1 week (frustrated users → happy users) 21. Environmental impact < 0.3g/page request (sustainability) 22. Frustration score < 5% (AUS + SUS/SUPR-Q + Lighthouse) 23. System Usability Scale > 75 (overall usability) 24. Accessible Usability Scale (AUS) > 75 (accessibility) 25. Core Web Vitals ≈ 100% (performance) Each team works with 3–4 local design KPIs that reflects the impact of their work, and 3–4 global design KPIs mapped against touchpoints in a customer journey. Search team works with search quality score, onboarding team works with time to success, authentication team works with password recovery rate. What gets measured, gets better. And it gives you the data you need to monitor and visualize the impact of your design work. Once it becomes a second nature of your process, not only will you have an easier time for getting buy-in, but also build enough trust to boost UX in a company with low UX maturity. [more in the comments ↓] #ux #metrics

How well does your product actually work for users? That’s not a rhetorical question, it’s a measurement challenge. No matter the interface, users interact with it to achieve something. Maybe it’s booking a flight, formatting a document, or just heating up dinner. These interactions aren’t random. They’re purposeful. And every purposeful action gives you a chance to measure how well the product supports the user’s goal. This is the heart of performance metrics in UX. Performance metrics give structure to usability research. They show what works, what doesn’t, and how painful the gaps really are. Here are five you should be using: - Task Success This one’s foundational. Can users complete their intended tasks? It sounds simple, but defining success upfront is essential. You can track it in binary form (yes or no), or include gradations like partial success or help-needed. That nuance matters when making design decisions. - Time-on-Task Time is a powerful, ratio-level metric - but only if measured and interpreted correctly. Use consistent methods (screen recording, auto-logging, etc.) and always report medians and ranges. A task that looks fast on average may hide serious usability issues if some users take much longer. - Errors Errors tell you where users stumble, misread, or misunderstand. But not all errors are equal. Classify them by type and severity. This helps identify whether they’re minor annoyances or critical failures. Be intentional about what counts as an error and how it’s tracked. - Efficiency Usability isn’t just about outcomes - it’s also about effort. Combine success with time and steps taken to calculate task efficiency. This reveals friction points that raw success metrics might miss and helps you compare across designs or user segments. - Learnability Some tasks become easier with repetition. If your product is complex or used repeatedly, measure how performance improves over time. Do users get faster, make fewer errors, or retain how to use features after a break? Learnability is often overlooked - but it’s key for onboarding and retention. The value of performance metrics is not just in the data itself, but in how it informs your decisions. These metrics help you prioritize fixes, forecast impact, and communicate usability clearly to stakeholders. But don’t stop at the numbers. Performance data tells you what happened. Pair it with observational and qualitative insights to understand why - and what to do about it. That’s how you move from assumptions to evidence. From usability intuition to usability impact. Adapted from Measuring the User Experience: Collecting, Analyzing, and Presenting UX Metrics by Bill Albert and Tom Tullis (2022).

💎 Overview of 70+ UX Metrics Struggling to choose the right metric for your UX task at hand? MeasuringU maps out 70+ UX metrics across task and study levels — from time-on-task and SUS to eye tracking and NPS (https://lnkd.in/dhw6Sh8u) 1️⃣ Task-Level Metrics Focus: Directly measure how users perform tasks (actions + perceptions during task execution). Use Case: Usability testing, feature validation, UX benchmarking. 🟢 Objective Task-Based Action Metrics These measure user performance outcomes. Effectiveness: Completion, Findability, Errors Efficiency: Time on Task, Clicks / Interactions 🟢 Behavioral & Physiological Metrics These reflect user attention, emotion, and mental load, often measured via sensors or tracking tools. Visual Attention: Eye Tracking Dwell Time, Fixation Count, Time to First Fixation Emotional Reaction: Facial Coding, HR (heart rate), EEG (brainwave activity) Mental Effort: Tapping (as proxy for cognitive load) 2️⃣ Task-Level Attitudinal Metrics Focus: How users feel during or after a task. Use Case: Post-task questionnaires, usability labs, perception analysis. 🟢 Ease / Perception: Single Ease Question (SEQ), After Scenario Questionnaire (ASQ), Ease scale 🟢 Confidence: Self-reported Confidence score 🟢 Workload / Mental Effort: NASA Task Load Index (TLX), Subjective Mental Effort Questionnaire (SMEQ) 3️⃣ Combined Task-Level Metrics Focus: Composite metrics that combine efficiency, effectiveness, and ease. Use Case: Comparative usability studies, dashboards, standardized testing. Efficiency × Effectiveness → Efficiency Ratio Efficiency × Effectiveness × Ease → Single Usability Metric (SUM) Confidence × Effectiveness → Disaster Metric 4️⃣ Study-Level Attitudinal Metrics Focus: User attitudes about a product after use or across time. Use Case: Surveys, product-market fit tests, satisfaction tracking. 🟢 Satisfaction Metrics: Overall Satisfaction, Customer Experience Index (CXi) 🟢 Loyalty Metrics: Net Promoter Score (NPS), Likelihood to Recommend, Product-Market Fit (PMF) 🟢 Awareness / Brand Perception: Brand Awareness, Favorability, Brand Trust 🟢 Usability / Usefulness: System Usability Scale (SUS) 5️⃣ Delight & Trust Metrics Focus: Measure positive emotions and confidence in the interface. Use Case: Branding, premium experiences, trust validation. Top-Two Box (e.g. “Very Satisfied” or “Very Likely to Recommend”) SUPR-Q Trust Modified System Trust Scale (MST) 6️⃣ Visual Branding Metrics Focus: How users perceive visual design and layout. Use Case: UI testing, branding studies. SUPR-Q Appearance Perceived Website Clutter 7️⃣ Special-Purpose Study-Level Metrics Focus: Custom metrics tailored to specific domains or platforms. Use Case: Gaming, mobile apps, customer support. 🟢 Customer Service: Customer Effort Score (CES), SERVQUAL (Service Quality) 🟢 Gaming: GUESS (Game User Experience Satisfaction Scale) #UX #design #productdesign #measure

Align your UX metrics to the business KPIs. We've been discussing what makes a KPI in our company. A Key Performance Indicator measures how well a person, team, or organization meets goals. It tracks performance so we can make smart decisions. But what’s a Design KPI? Let’s take an example of a design problem. Consider an initiative to launch a new user dashboard to improve user experience, increase product engagement, and drive business growth. Here might be a few Design KPIs with ways to test them: →  Achieve an average usability of 80% within the first three months post-launch. Measurement: Conduct user surveys and collect feedback through the dashboard's feedback feature using the User Satisfaction Score. →  Ensure 90% of users can complete key tasks (e.g., accessing reports, customizing the dashboard) without assistance. Measurement: Conduct usability testing sessions before and after the launch, analyzing task completion rates. →  Reduce the average time to complete key tasks by 20%. Measurement: Use analytics tools to track and compare time spent on tasks before and after implementing the new dashboard. We use Helio to get early signals into UX metrics before coding the dashboard. This helps us find good answers faster and reduces the risk of bad decisions. It's a mix of intuition and ongoing, data-informed processes. What’s a product and business KPI, then? Product KPI: →  Increase MAU (Monthly Active Users) by 15% within six months post-launch. Measurement: Track the number of unique users engaging with the new dashboard monthly through analytics platforms. →  Achieve a 50% feature adoption rate of new dashboard features (e.g., customizable widgets, real-time data updates) within the first quarter. Measurement: Monitor the usage of new features through in-app analytics. Business KPI: → Drive a 5% increase in revenue attributable to the new dashboard within six months. Measurement: Compare revenue figures before and after the dashboard launch, focusing on user subscription and upgrade changes. This isn't always straightforward! I'm curious how you think about these measurements. #uxresearch #productdiscovery #marketresearch #productdesign

Most companies see business, customer, and UX metrics as separate stories. I had Bruno M. (JP Morgan Chase, HealthEquity), who led the journey-centric transformation to make these separate layers work together. I love the simplicity of the approach, when every job to be done or journey get structured with 3 layers of metrics. That way, every level of the journey framework is consistent: 1️⃣ Business Layer (Top Layer) This layer focuses on traditional KPIs that matter most to executives — the metrics that indicate how the journey contributes to overall business performance. Examples include: - Revenue - Conversion rates - Cost savings (e.g., shorter average handle time) - Retention / Churn rates These help executives and general managers see how customer experience links directly to financial and operational performance. 2️⃣ Customer Experience Layer (Middle Layer) Here, Bruno connects business KPIs to customer sentiment using metrics like: - NPS (Net Promoter Score) - CSAT (Customer Satisfaction) While he’s critical of NPS (“hard to know what’s really broken just from NPS”), he acknowledges it remains a key business-facing metric that helps secure buy-in from leadership. However, he stresses that NPS alone is meaningless — its value emerges only when overlaid with other measures like completion rates or drop-off data. 3️⃣ UX / Behavioral Layer (Bottom Layer) The third layer goes deeper into the user experience where the actual friction or success of the journey can be observed. Examples include: - Task completion rates - Time on task - Error rates - Drop-offs or conversion funnels These granular metrics help teams act quickly and connect customer behaviors directly to business outcomes. 🤝 How It All Connects Bruno envisions a single dashboard where you can: - Click into a “job to be done” or journey. - See the KPI layer, CX layer, and UX layer all linked together. This way: - Executives can see how journeys drive business. - CX teams can track satisfaction and loyalty. - Product and design teams can pinpoint usability and behavioral issues. He calls this layered approach the core of accountability in journey management. Making sure everyone from the CEO to the UX designer looks at the same truth through their own lens. Check out the Episode for a deep dive, this one is 🔥🔥🔥

🚀 Did you know that improving your UX can increase conversion rates by up to 400%? As a founder of multiple tech startups and a design agency, I've learned that measuring the right UX metrics can make or break your product's success. → Here are the top 5 KPIs every startup founder should be tracking: ▸ Task Success Rate: Are users accomplishing what they came for? ▸ Time on Task: How efficiently can users navigate your product? ▸ User Error Rate: Where are users getting stuck? ▸ Net Promoter Score (NPS): Will your users recommend your product? ▸ Customer Satisfaction Score (CSAT): How happy are your users overall? But why do these matter? Well, companies that invest in UX see a lower cost of customer acquisition, lower support cost, increased customer retention and market share. Want to dive deeper? Check out Nielsen Norman Group's article on UX Metrics: https://lnkd.in/gYSf8rMA What UX metrics have you found most valuable for your startup? Share in the comments below! 👇 #StartupMetrics #UXDesign #ProductSuccess #FounderTips #UX