User Experience and Conversion Rates

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 👇

⚡ UX Metrics Flashcards (https://lnkd.in/dTbwBzJU), a helpful guide on how to help UX teams choose the right metrics, align UX measurement with business goals — and show the impact of their work. Put together by Anna Kaley from NN/g. ⚬ Print-ready PDF: https://lnkd.in/duKJzDyE ⚬ Miro board template: https://lnkd.in/d7_7YGrC ⚬ Design KPIs & UX Metrics: https://lnkd.in/dgbJVEWS ⚬ 70+ UX Metrics (by MeasuringU): https://lnkd.in/dBDNDkNb ⚬ UX KPIs Cheatsheet (by Helio): https://lnkd.in/dXqbySTe --- One point I’d like to raise is that design changes rarely have a clear immediate impact on business. It’s difficult to find a causation between how a change in filters UX has increased conversion or improved retention or reduced churn. Typically we need to measure at 2 levels — locally (if people use filters more efficiently) and globally (how successful people are at their journeys). Also, UX metrics that work well in one environment will not be applicable in others. E.g. Time on Task is difficult to measure in products with non-linear workflows since there are no linear journeys that people take repeatedly. Sometimes retention isn’t particularly useful either as employees can’t choose the product they use for work. There, we need to track retention on the level of features, flows, internal tools we are building — and focus our work on how to dial up success moments and dial down frustrations and mistakes. Still, in many products there are central hubs that a lot of users are going through. In fact, every product is like a city. And so if we can improve the experience across most frequent flows, features and tasks, we can have quite an impact — and drive up business metrics as result (over time). No business can be successful without successful customers. If business goals are fluffy and unclear, we have to build up product value from user needs (task analysis). And a way there is to study what users need to do, what would make them successful and where they currently struggle. Then we make a business case from there — and focus on what matters most to the business. A helpful guide by NN/g to get started, but I would highly recommend to customize the kit for your needs — chances are high that you will need a very different and very specific metrics to track success. Thanks to Anna and colleagues for putting it together! --- And if you’d like to dive deeper, I‘m trying to address many of painful challenges around UX metrics in Measure UX (https://measure-ux.com). I’ve tried my best to keep the pricing affordable. But if it’s still expensive, please send me a message and I’ll do my best to make it work. 👏🏽 #ux #design

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.

It’s been four months since we launched Auditzy™ RUM (Real User Monitoring) for websites, aimed at tracking website speed and performance. Today, I’m excited to share some key insights we've gathered from monitoring Indian E-commerce websites and user behaviour's. ▶ We've captured over 1 billion data points across various E-commerce websites to understand how performance impacts user experience. ▶ 60% of visitors access websites from mobile devices using a 4G network. ▶ A whopping 85% of mobile website visitors in India use the Chrome browser. ▶ Approximately 30% of traffic on e-commerce websites comes from in-app browsers (browsers that open when clicking ads on Instagram, Facebook, YouTube, etc.). ▶ In-app browser conversions are 1.5 times lower than native browser conversions, indicating that users are less likely to make purchases directly from in-app browsers. (It's a Big Pain, we are also solving this, announcing Soon! 💪 ) ▶ Bounce rates increase by nearly 10% when visitors use a 3G network compared to a 4G network. ▶ 60% of unique "Add to Cart" actions occur when website speed is less than 3 seconds throughout the user journey. ▶ Operating Systems: In India, 70% of mobile website visitors use Android OS, while around 30% use iOS. ▶ A 3-second improvement in load time led one of our customers to witness an 18% growth in conversions. (Detailed Case Study Coming Soon!) 🔥 ▶ 55% of Indian users have devices with less than 8 GB of RAM when visiting websites from mobile devices. ▶ About 15% of traffic on Indian e-commerce websites comes from desktop browsers. These insights highlight the critical importance of optimising website performance to enhance user experience and conversions. If you found this post insightful, feel free to reshare it! 🙌 Start measuring meaningful web performance metrics rather than chasing a perfect 100/100 on PageSpeed Insights! 😅 #Pagespeed #CoreWebVitals #AuditzyInsights

Conversion optimization pros won't like this: but listening to your users is more valuable than 90% of the experiments I review. I've made this mistake too. My teams spent years running dozens of "high-impact" experiments to improve our signup rate. It helped, but we knew something was missing. Then, we started running a survey on the high-intent pages of our site that changed everything... The question was simple: "Hey, thanks for visiting the site. Mind sharing what's stopping you from creating a free account today?" But the answers were super helpful. "I don't understand the product" "Not sure if I'm your ICP" "The pricing model is confusing" "I need to see what it looks like first" "Can't figure out if you solve for [specific use case]" Some were painful to read. But they refocused us on solving the right problems for our users. Instead of running blind experiments based on what WE thought the problem was, we started brainstorming new impactful ways to improve our conversions: copy changes, video updates, image adjustments, page layout changes - based on the THEIR feedback. Not sure how to take your signup rate to the next level? Try asking some flavor of this question. You’ll get some incredible insights. PS we used Hotjar | by Contentsquare to run the survey, but there's plenty of other tools out there to do this. It's about getting input from real people. That's where the magic happens.

"Most apps lose 80% of users before they experience any value." Here's the interesting part: It's not because the product is bad. It's because we're measuring the wrong things. After studying successful onboarding flows, I discovered 3 hidden metrics that actually matter: 1. Time to "Aha!" Not just first value - but first MEANINGFUL value. The psychology behind it: • Users form judgments in seconds • Each extra step builds frustration • Value needs to beat skepticism 2. The "Cliff Points" Those moments where users suddenly vanish. What to watch: • Which screen sees sudden exits • When motivation drops • Where confusion peaks 3. The Patience Threshold Not just how long onboarding takes. But how long users THINK it takes. The counterintuitive truth: A 5-minute onboarding that feels smooth beats a 2-minute one that feels confusing. Want to see exactly how to measure and optimize these metrics? Watch our latest Behind The Feature episode where I break down real examples [Link in comments] The brutal reality? Users don't care about your features. They care about getting to their goal. What's your biggest onboarding challenge? Drop it below 👇 #ProductStrategy #UserExperience #ProductGrowth #BehindTheFeature

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

We increased Conversion Rate by 88% Wanna know how? We exposed Search on Mobile (instead of hiding it behind a search icon). How did we know to test this? During our comprehensive CRO Insights Service, we analysed heatmaps and session recordings, along with Shopify and GA4 data to understand user behaviour. And we uncovered two key insights: 1. Mobile sessions were higher than desktop 2. Users who engaged with the search bar showed a strong intent to purchaseBased on this, we hypothesised that making the search bar more accessible on mobile, we would create a smoother user experience, leading to higher conversion rates. Then we A/B tested it.And the results: ✅ 126% increase in search trigger clicks ✅ 23% increase in engagement with 'Looking for any of these' ✅ 109% increase in Average Purchase Revenue per User ✅ 30% increase in Add to Cart per sessionAnd of course, 88% increase in Conversion Rate.

We didn’t fail because the product sucked. We failed because we were looking at the wrong numbers. One of our best-looking product launches quietly started leaking cash within 3 months. Sales were good. Reviews were solid. Site traffic was up. But under the surface? Margins shrinking Return rates rising Repeat purchases… flat Turns out we were too busy watching vanity metrics the ones that make you feel good in a pitch deck and ignoring the ones that actually shape the health of the business. So we rebuilt our dashboard. And I now swear by these 4 KPIs 👇 1. Product-Specific NPS Not general CSAT. Not site feedback. We track NPS per product, every 90 days. If it dips, we investigate. FAST. 2. Warranty Claims per 1,000 Units It’s the quietest indicator of product quality. We aim for <5%. Above that, your cost of support and margin pain kicks in. 3. 60-Day Repurchase Rate 20–40% is solid in most DTC categories. We’ve seen how this drives word-of-mouth, not just retention. If people love it, they’ll buy again (or send friends). 4. Checkout Completion % by Device This helped us uncover a massive drop-off on mobile. Fixing that UX bump raised conversions by 14% in a week. These aren’t always the sexiest metrics. But they tell the truth. And when you're scaling, the truth is more useful than dopamine. What 3–4 KPIs do you actually look at every week? ♻️Repost if you think more founders should obsess over the right metrics, not just the pretty ones.