User Experience Metrics for Success

🔮 UX Metrics and KPIs Cheatsheet (Figma) (https://lnkd.in/en9MK4MD), a helpful reference sheet for UX metrics, with formulas and examples — for brand score, desirability, loyalty, satisfaction, sentiment, success, usefulness and many others. Neatly put together in one single place by fine folks at Helio Glare. To me personally, measuring UX success is focused around just a few key attributes — how successful users are in completing their key tasks, how many errors users experience along the way and how quickly users get through onboarding to first meaningful success. The context of the project will of course request specific, custom metrics — e.g. search quality score, or brand score, or engagement score or loyalty — but UX metrics are all around delivering value to users through their successes. Here are some examples: 1. Top tasks success > 80% (for critical tasks) 2. Time to complete top tasks < Xs (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 a 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 > 30% (usage of a new feature per user) 10. Feature retention rate > 40% (after 90 days) 11. Time to pricing quote < 2 weeks (for B2B systems) 12. Application processing time < 2 weeks (online banking) 13. Default settings correction < 10% (quality of defaults) 14. Relevance of top 100 search queries > 80% (for top 5 results) 15. Service desk inquiries < 35/week (poor design → more inquiries) 16. Form input accuracy ≈ 100% (user input in forms) 17. Frequency of errors < 3/visit (mistaps, double-clicks) 18. Password recovery frequency < 5% per user (for auth) 19. Fake email addresses < 5% (newsletters) 20. Helpdesk follow-up rate < 4% (quality of service desk replies) 21. “Turn-around” score < 1 week (frustrated users -> happy users) 22. Environmental impact < 0.3g/page request (sustainability) 23. Frustration score < 10% (AUS + SUS/SUPR-Q) 24. System Usability Scale > 75 (usability) 25. Accessible Usability Scale (AUS) > 75 (accessibility) Each team works with 3–4 design KPIs that reflect the impact of their work. 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. [continues in comments ↓] #ux #design

Over the last year, I’ve seen many people fall into the same trap: They launch an AI-powered agent (chatbot, assistant, support tool, etc.)… But only track surface-level KPIs — like response time or number of users. That’s not enough. To create AI systems that actually deliver value, we need 𝗵𝗼𝗹𝗶𝘀𝘁𝗶𝗰, 𝗵𝘂𝗺𝗮𝗻-𝗰𝗲𝗻𝘁𝗿𝗶𝗰 𝗺𝗲𝘁𝗿𝗶𝗰𝘀 that reflect: • User trust • Task success • Business impact • Experience quality    This infographic highlights 15 𝘦𝘴𝘴𝘦𝘯𝘵𝘪𝘢𝘭 dimensions to consider: ↳ 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆 — Are your AI answers actually useful and correct? ↳ 𝗧𝗮𝘀𝗸 𝗖𝗼𝗺𝗽𝗹𝗲𝘁𝗶𝗼𝗻 𝗥𝗮𝘁𝗲 — Can the agent complete full workflows, not just answer trivia? ↳ 𝗟𝗮𝘁𝗲𝗻𝗰𝘆 — Response speed still matters, especially in production. ↳ 𝗨𝘀𝗲𝗿 𝗘𝗻𝗴𝗮𝗴𝗲𝗺𝗲𝗻𝘁 — How often are users returning or interacting meaningfully? ↳ 𝗦𝘂𝗰𝗰𝗲𝘀𝘀 𝗥𝗮𝘁𝗲 — Did the user achieve their goal? This is your north star. ↳ 𝗘𝗿𝗿𝗼𝗿 𝗥𝗮𝘁𝗲 — Irrelevant or wrong responses? That’s friction. ↳ 𝗦𝗲𝘀𝘀𝗶𝗼𝗻 𝗗𝘂𝗿𝗮𝘁𝗶𝗼𝗻 — Longer isn’t always better — it depends on the goal. ↳ 𝗨𝘀𝗲𝗿 𝗥𝗲𝘁𝗲𝗻𝘁𝗶𝗼𝗻 — Are users coming back 𝘢𝘧𝘵𝘦𝘳 the first experience? ↳ 𝗖𝗼𝘀𝘁 𝗽𝗲𝗿 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝗼𝗻 — Especially critical at scale. Budget-wise agents win. ↳ 𝗖𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻 𝗗𝗲𝗽𝘁𝗵 — Can the agent handle follow-ups and multi-turn dialogue? ↳ 𝗨𝘀𝗲𝗿 𝗦𝗮𝘁𝗶𝘀𝗳𝗮𝗰𝘁𝗶𝗼𝗻 𝗦𝗰𝗼𝗿𝗲 — Feedback from actual users is gold. ↳ 𝗖𝗼𝗻𝘁𝗲𝘅𝘁𝘂𝗮𝗹 𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱𝗶𝗻𝗴 — Can your AI 𝘳𝘦𝘮𝘦𝘮𝘣𝘦𝘳 𝘢𝘯𝘥 𝘳𝘦𝘧𝘦𝘳 to earlier inputs? ↳ 𝗦𝗰𝗮𝗹𝗮𝗯𝗶𝗹𝗶𝘁𝘆 — Can it handle volume 𝘸𝘪𝘵𝘩𝘰𝘶𝘵 degrading performance? ↳ 𝗞𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆 — This is key for RAG-based agents. ↳ 𝗔𝗱𝗮𝗽𝘁𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗦𝗰𝗼𝗿𝗲 — Is your AI learning and improving over time? If you're building or managing AI agents — bookmark this. Whether it's a support bot, GenAI assistant, or a multi-agent system — these are the metrics that will shape real-world success. 𝗗𝗶𝗱 𝗜 𝗺𝗶𝘀𝘀 𝗮𝗻𝘆 𝗰𝗿𝗶𝘁𝗶𝗰𝗮𝗹 𝗼𝗻𝗲𝘀 𝘆𝗼𝘂 𝘂𝘀𝗲 𝗶𝗻 𝘆𝗼𝘂𝗿 𝗽𝗿𝗼𝗷𝗲𝗰𝘁𝘀? Let’s make this list even stronger — drop your thoughts 👇

Everyone’s excited to launch AI agents. Almost no one knows how to measure if they’re actually working. Over the last year, we’ve seen brands launch everything from GenAI assistants to support bots to creative copilots but the post-launch metrics often look like this: • Number of chats • Average latency • Session duration • Daily active users Useful? Yes. But sufficient? Not even close. At ALTRD, we’ve worked on AI agents for enterprises and if there’s one lesson it’s this: Speed and usage mean nothing if the agent isn’t solving the actual problem. The real performance indicators are far more nuanced. Here’s what we’ve learned to track instead: 🔹 Task Completion Rate — Can the AI go beyond answering a question and actually complete a workflow? 🔹 User Trust — Do people come back? Do they feel confident relying on the agent again? 🔹 Conversation Depth — Is the agent handling complex, multi-turn exchanges with consistency? 🔹 Context Retention — Can it remember prior interactions and respond accordingly? 🔹 Cost per Successful Interaction — Not just cost per query, but cost per outcome. Massive difference. One of our clients initially celebrated their bot’s 1 million+ sessions - until we uncovered that less than 8% of users actually got what they came for. That 8% wasn’t a usage issue. It was a design and evaluation issue. They had optimized for traffic. Not trust. Not success. Not satisfaction. So we rebuilt the evaluation framework - adding feedback loops, success markers, and goal-completion metrics. The results? CSAT up by 34% Drop-off down by 40% Same infra cost, 3x more value delivered The takeaway: Don’t just measure what’s easy. Measure what matters. AI agents aren’t just tools - they’re touchpoints. They represent your brand, shape user experience, and influence business outcomes. P.S. What’s one underrated metric you’ve used to evaluate AI performance? Curious to learn what others are tracking.

🔎 ICYMI: We talk about #trust all the time. But do we really understand it? And more importantly, can we measure it? 👉 Trust provides a license to operate for institutions. It drives participation, compliance, and collective problem-solving. Yet for too long, trust has remained an abstract ideal — hard to define, harder to act on. We partnered with the NYC Civic Engagement Commission to change that. 📘 Our new report offers a practical framework for making trust measurable and actionable. Instead of vague notions, we focus on: ✔️ Observable manifestations — how trust shows up in emotions and behaviors (like confidence, belonging, or civic engagement) ✔️ Drivers of trust — the direct experiences and institutional interventions that shape it ✔️ A 3-phase approach — to baseline, analyze, and strengthen trust through targeted, measurable interventions 🚸 We apply this framework to real-world settings — from participatory budgeting to parks departments — showing how public institutions can measure, earn and sustain trust. 👉 Read the full report here: https://lnkd.in/eg4iV_hV (new URL!) (✍️co-authored with Andrew Zahuranec and Oscar Romero) #CivicTrust #PublicSectorInnovation #DataForGood #TrustMetrics #GovLab #NYC #CivicEngagement #MeasurementMatters

If your site is slow, you’re leaving traffic and revenue on the table. Core Web Vitals are no longer optional. Google has made them a ranking factor, meaning publishers that ignore them risk losing visibility, traffic, and user trust. For those of us working in SEO and digital publishing, the message is clear: speed, stability, and responsiveness directly affect performance. Core Web Vitals focus on three measurable aspects of user experience: → Largest Contentful Paint (LCP): How quickly the main content loads. Target: under 2.5 seconds. → First Input Delay (FID) / Interaction to Next Paint (INP): How quickly the page responds when a user interacts. Target: under 200 milliseconds. → Cumulative Layout Shift (CLS): How visually stable a page is. Target: less than 0.1. These metrics are designed to capture the “real” experience of a visitor, not just what a developer or SEO sees on their end. Why publishers can't ignore CWV in 2025 1. SEO & Trust: Only ~47% of sites pass CWV assessments, presenting a competitive edge for publishers who optimize now. 2. Page performance pays off: A 1-second improvement can boost conversions by ~7% and reduce bounce rates—benefits seen across industries 3. User expectations have tightened: In 2025, anything slower than 3 seconds feels “slow” to most users—under 1 s is becoming the new gold standard, especially on mobile devices. 4. Real-world wins: a. Economic Times cut LCP by 80%, CLS by 250%, and slashed bounce rates by 43%. b. Agrofy improved LCP by 70%, and load abandonment fell from 3.8% to 0.9%. c. Yahoo! JAPAN saw session durations rise 13% and bounce rates drop after CLS fixes. Practical steps for improvement • Measure regularly: Use lab and field data to monitor Core Web Vitals across templates and devices. • Prioritize technical quick wins: Image compression, proper caching, and removing render-blocking scripts can deliver immediate improvements. • Stabilize layouts: Define media dimensions and manage ad slots to reduce layout shifts. • Invest in long-term fixes: Optimizing server response times and modernizing templates can help sustain improvements. Here are the key takeaways ✅ Core Web Vitals are measurable, actionable, and tied directly to SEO performance. ✅ Faster, more stable sites not only rank better but also improve engagement, ad revenue, and subscriptions. ✅ Publishers that treat Core Web Vitals as ongoing maintenance, not one-time fixes will see compounding benefits over time. Have you optimized your site for Core Web Vitals? Share your results and tips in the comments, your insights may help other publishers make meaningful improvements. #SEO #DigitalPublishing #CoreWebVitals #PageSpeed #UserExperience #SearchRanking

If your PR report looks impressive with big numbers but still feels empty, this post is for you. Most agencies still sell visibility KPIs — impressions, mentions, share of voice, AVE, reach. These agencies aren't wrong in doing it, as these metrics are can be measured with ease. But these metrics lack meaning for clients. These numbers tell you how often your name showed up, not whether your story landed or your reputation strengthened. What you should be tracking instead are Trust Signals — the real indicators of reputation movement. Trust Signals look like this: - A journalist quoting you without you pitching them. - A client repeating your messaging unprompted. - An investor referencing your thought piece in a meeting. - Employees sharing company news with pride. These are lagging indicators of belief. They don’t fit neatly in a dashboard and that's why most agencies avoid them. But if your PR work doesn’t move trust, it’s just paid noise management. PR done right builds confidence in your name, not just coverage reports. So next time you get your monthly report, ask one simple question: “Which of these numbers tells me people trust us more than last month?” Which metric did your PR agency report last month?

💡Measuring UX using Google HEART HEART is a framework developed by Google for evaluating the user experience of a product. It provides a holistic view of the UX by considering both qualitative & quantitative metrics. HEART stands for ✅ Happiness: How satisfied users are with using your product. It can be measured through surveys and ratings (quantitative) and reviews and user interviews (qualitative). Tracking happiness is right when you analyze the general performance of your product. ✅ Engagement: How actively users are interacting with the product. This includes metrics like the number of visits, time spent on the product, frequency of interactions, and the depth of interactions (e.g., the number of features used). Analyzing engagement will help you understand how compelling & valuable the product is to users. ✅ Adoption: How effectively the product attracts new users and converts them into active users. Key metrics include user sign-ups, onboarding completion rates, and activation rates (e.g., the percentage of users who perform a key action after signing up). Understanding adoption helps identify barriers during product onboarding. ✅ Retention: How well the product retains its users over time. It focuses on reducing churn and keeping users engaged over the long term. Metrics like retention rate and cohort analysis are used to measure retention. Improving retention involves addressing pain points, providing ongoing value, and fostering a sense of loyalty among users. ✅ Task success: How effectively users can accomplish their goals or tasks using the product. This includes metrics like task completion rate, error rate, and time to complete tasks. User journey mapping, user interviews, and usability testing can help identify usability issues and optimize the user flow to enhance task success. ❗ Top 3 mistakes when using HEART 1️⃣ Placing too much emphasis on quantitative metrics at the expense of qualitative insights. While quantitative data is valuable for analysis, it's essential to complement this with qualitative data, such as user feedback and observations, to gain a deeper understanding of user behavior and preferences. 2️⃣ Ignoring the context of interaction: Failing to consider the context in which users interact with the product can lead to misleading interpretations of the data.  3️⃣ Lack of user segmentation: Not segmenting users based on relevant factors such as demographics, behavior, or usage patterns can obscure important insights and lead to generic conclusions that may not apply to all user groups. 📺 Guide to using Google HEART: https://lnkd.in/dhkwy_jN 🚨 Live session "How to measure design success" 🚨 I will run a live session on measuring design success in February. Will talk about how to choose the right metrics for your product & how to measure product's success in meeting business goals   https://lnkd.in/dgm6t_jf #UX #design #productdesign #metrics #measure

🧵 How Do You Measure a Relationship? In neighbourhood health and cross-sector work, we often ask: How do we know it's working? Not just the outputs, but the relational glue that holds it together. I’ve been in projects where a cohesive team just gets stuff done. No fanfare. Just trust, understanding, and movement. It’s something I believe I bring as a neurodivergent dyslexic wired to read people, respond communicatively, and know when to act or step back. But how do we measure that? 📊 Emerging practice across BNSSG suggests: 1)Trust & engagement indices between citizens and services 2)Narrative interviews and storytelling-based reflections 3)Social network mapping to track who connects with whom 4)Developmental evaluation that measures learning, not just outcomes 5)Ethnographic observations of service interactions These aren’t just metrics, they’re lifelines. They surface subconscious bias, adaptive capacity, and the human messiness that makes collaboration real. 🧠 Leadership in Cross-Sector Teams: Top 5 Conditions for Collaboration i) Psychological safety – people must feel safe to speak, challenge, and be vulnerable ii)Shared purpose – not just aligned goals, but co-owned meaning iii)Adaptive space – the “in-between” zone where ideas move from periphery to core iv) Enabling leadership – catalysing conditions, removing barriers, connecting people v)Relational infrastructure – time, tools, and rituals that allow trust to grow This is the work. Messy, human, and deeply creative. If you’re working in neighbourhoods, systems, or cross-sector spaces, how do you measure trust and relational glue? Let’s build the evidence and the story. #AdaptiveSpace #CreativeHealth #NeighbourhoodLeadership #RelationalGlue #ComplexSystems #DYCP #BNSSG #CultureAndCare

Funders want to support journalism. But many aren't convinced hiring a youth reporter will get them there. And they might be right. Not because youth reporters aren't valuable. They are. But one hire won't shift who feels seen or change who shows up for our journalism. Not without real influence (🔗https://lnkd.in/e6NFWG9b). So what does real youth influence in local news look like? It's bigger than a beat, and the scope is wider than you think. How might we support youth agency through local journalism? Let me count the ways. 👇 𝗠𝗘𝗔𝗦𝗨𝗥𝗘𝗠𝗘𝗡𝗧 & 𝗟𝗘𝗔𝗥𝗡𝗜𝗡𝗚 📊 Baseline and post-engagement surveys track shifts in trust, news habits, and civic attitudes. Not just "did they attend" but "did something change?" 📈 Behavior change tracking asks: Are young people voting, attending public meetings, sharing local news, bringing a friend? Fund the capacity to measure civic action. 🔍 Youth-informed success metrics let young people define what "working" looks like. Their measures may differ from ours. 🧪 Learning cohorts fund newsrooms to learn together, share data, and iterate. Impact isn't a one-org problem. 💻 Digital engagement analytics go beyond pageviews: comment quality, sharing patterns, community referrals. 𝗦𝗞𝗜𝗟𝗟𝗦 & 𝗘𝗫𝗣𝗥𝗘𝗦𝗦𝗜𝗢𝗡 🎭 Improv training builds confidence and agency before young people ever touch a mic, hit record or ask a question. 📖 Zine-making courses offer low-barrier, high-expression storytelling. 💬 Discourse and dialogue training teaches young people to engage across difference. (See: Sustained Dialogue Institute) 𝗖𝗢𝗡𝗡𝗘𝗖𝗧𝗜𝗢𝗡 & 𝗦𝗣𝗔𝗖𝗘 🏠 Third spaces address youth disconnection through gathering spots that aren't home, school, or work. (See: New_ Public, Listening Post Collective) 🏛️ Civic institution partnerships ��� libraries, museums, history centers, even restaurants — fund the infrastructure of collaboration. (History:Collab gets this.) 🎙️ Live event series put student voices on public stages alongside community journalism. This list isn't exhaustive, but I hope it's an invitation. Bc I've been thinking about it since the American Press Institute Youth Trust Summit in March. The upswing is real. The desire from news leaders is real. But when capacity is the #1 barrier to execution, reality requires more than a one-off project or a program. It needs commitment from ideation to an mvp through launch to sustained impact. Youth empowerment through local journalism is a long game. How do you wanna play? What would you add? What do you wish you could get funded? 📣 #LocalNews #YouthEngagement #CivicTrust

👀 What signals are you tracking this year—beyond test scores and budgets? Here are 3 system indicators superintendents should be watching closely. Each one points to deeper system health and long-term sustainability: 🔹 1. Student Engagement & Belonging Why it matters: Chronic absenteeism and disengagement quietly erode both achievement and culture. Attendance, behavior, and student voice are early indicators that your system is (or isn’t) resonating with kids. What to watch: Daily attendance trends (especially the “first 20 days runway”) Survey data on belonging, safety, and relationships Early-warning systems flagging participation drops or behavior spikes 🔹 2. Workforce Stability & Morale Why it matters: Teacher and principal turnover, plus classified staff shortages, put strain on daily operations. Burnout often surfaces before resignations. What to watch: Retention and vacancy rates by role and school Mid-year feedback loops (pulse surveys, focus groups) Sub fill rates + overtime costs = early burnout signals 🔹 3. Community Trust & Public Confidence Why it matters: In a polarized climate, trust is a protective factor and a driver of change. What to watch: Parent/caregiver satisfaction + communication feedback Participation in board meetings, advisory groups, and school events Media narratives and social sentiment about your district ✅ Takeaway for leaders: The most effective superintendents this year will treat these as more than just metrics—they’ll read them as stories about system health. When engagement, workforce stability, and trust are moving in the right direction, academic and operational outcomes follow. #K12Leadership #Superintendents #EducationalLeadership #SchoolCulture #StrategicLeadership #WholeChild #SystemsThinking #EdLeadership