User Experience for SaaS Products

🎡 How To Run UX Workshops With Users (Scripts + Templates) (https://lnkd.in/evqDZSFe), a helpful overview of practical techniques to turn a verbal-only interview into a collaborative UX workshop — with sticky note mapping, solution drag’n’drop and voting. Put together by Laura Eiche-Laane. 👏🏽 🤔 Users and designers often a speak a different language. ✅ Insights are clearer when you see users performing tasks. ✅ Switch question-answer sections with small visual tasks. ✅ Sticky note mapping: for user flows, journeys, org maps. ✅ Card sorting: organize data, filters, menu items into groups. ✅ Feature location: ask users where they’d expect a new feature. ✅ Drag’n’drop: ask users to design their own UI or page layout. ✅ Solution voting: get feedback on many design directions. ✅ When explaining a task, show what you’d like them to do. ✅ Track where users are undecided, and follow up in a debrief. When I jump in a new project, I like to run walkthroughs with actual users as a way to understand the domain and the product. I simply ask them what the product does and how it helps them in their daily work. And then I invite them to show and explain it to me. I ask them to show how it works, the features they use, the quirks they’ve discovered and the shortcuts and loopholes they rely on daily. Perhaps there is something where the product fails on them, or something they wish was better, or something that is too fragile, confusing, complex or irrelevant. That’s when insights emerge, and that’s when you might notice that the things said and the things done are not necessarily the same thing. Of course users sometimes exaggerate their struggles, but they rarely complain lividly about something that isn’t really an issue for them. 🗃️ Useful resources: How And Why To Include Users In UX Workshops, by Maddie Brown https://lnkd.in/eKdd5GXp UX Workshop Activities With Users, by Jonathon Juvenal https://lnkd.in/eJjpcibR Remote UX Workshop Activities, by Jordan Bowman https://lnkd.in/e8wSMVwC Usability Testing Templates (Scripts), by Slava Shestopalov https://lnkd.in/gZyBtK6u UX Workshop Scripts + Templates https://theuxcookbook.com UX Research Templates, by Odette Jansen https://lnkd.in/eqpXyGHH --- 🧲 Miro and Notion templates: UX Research Templates (Miro), by ServiceNow https://lnkd.in/e48nKzKA Miro Templates For Designers https://lnkd.in/e8Hkp-ws Notion Templates For Designers https://lnkd.in/en_VBc6r #ux #design

Getting the right feedback will transform your job as a PM. More scalability, better user engagement, and growth. But most PMs don’t know how to do it right. Here’s the Feedback Engine I’ve used to ship highly engaging products at unicorns & large organizations: — Right feedback can literally transform your product and company. At Apollo, we launched a contact enrichment feature. Feedback showed users loved its accuracy, but... They needed bulk processing. We shipped it and had a 40% increase in user engagement. Here’s how to get it right: — 𝗦𝘁𝗮𝗴𝗲 𝟭: 𝗖𝗼𝗹𝗹𝗲𝗰𝘁 𝗙𝗲𝗲𝗱𝗯𝗮𝗰𝗸 Most PMs get this wrong. They collect feedback randomly with no system or strategy. But remember: your output is only as good as your input. And if your input is messy, it will only lead you astray. Here’s how to collect feedback strategically: → Diversify your sources: customer interviews, support tickets, sales calls, social media & community forums, etc. → Be systematic: track feedback across channels consistently. → Close the loop: confirm your understanding with users to avoid misinterpretation. — 𝗦𝘁𝗮𝗴𝗲 𝟮: 𝗔𝗻𝗮𝗹𝘆𝘇𝗲 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 Analyzing feedback is like building the foundation of a skyscraper. If it’s shaky, your decisions will crumble. So don’t rush through it. Dive deep to identify patterns that will guide your actions in the right direction. Here’s how: Aggregate feedback → pull data from all sources into one place. Spot themes → look for recurring pain points, feature requests, or frustrations. Quantify impact → how often does an issue occur? Map risks → classify issues by severity and potential business impact. — 𝗦𝘁𝗮𝗴𝗲 𝟯: 𝗔𝗰𝘁 𝗼𝗻 𝗖𝗵𝗮𝗻𝗴𝗲𝘀 Now comes the exciting part: turning insights into action. Execution here can make or break everything. Do it right, and you’ll ship features users love. Mess it up, and you’ll waste time, effort, and resources. Here’s how to execute effectively: Prioritize ruthlessly → focus on high-impact, low-effort changes first. Assign ownership → make sure every action has a responsible owner. Set validation loops → build mechanisms to test and validate changes. Stay agile → be ready to pivot if feedback reveals new priorities. — 𝗦𝘁𝗮𝗴𝗲 𝟰: 𝗠𝗲𝗮𝘀𝘂𝗿𝗲 𝗜𝗺𝗽𝗮𝗰𝘁 What can’t be measured, can’t be improved. If your metrics don’t move, something went wrong. Either the feedback was flawed, or your solution didn’t land. Here’s how to measure: → Set KPIs for success, like user engagement, adoption rates, or risk reduction. → Track metrics post-launch to catch issues early. → Iterate quickly and keep on improving on feedback. — In a nutshell... It creates a cycle that drives growth and reduces risk: → Collect feedback strategically. → Analyze it deeply for actionable insights. → Act on it with precision. → Measure its impact and iterate. — P.S. How do you collect and implement feedback?

The Monday Morning Test Every training program feels successful on Friday afternoon. Participants are engaged, the discussions are rich, and the feedback is encouraging. But over the last few years, I’ve come to believe that the real test begins on Monday morning. I’ve had the opportunity to design learning experiences, facilitate programs, and partner with business leaders to build capability. Looking back, the biggest lesson I learned wasn’t about creating better content. It was about understanding what actually changes behavior. Like many learning professionals, I used to believe that if we designed engaging content and facilitated a great program, the results would naturally follow. Then something interesting started happening. Whenever I happened to reconnected with people who had attended those programs, they rarely spoke about the program itself. Instead, they would say, “I still remember that story you shared.” “I’ve been using that coaching question ever since.” “That conversation changed the way I lead my team.” Reading some of the comments on my recent LinkedIn posts reminded me of this once again. People rarely remember the program itself. They remember the story, the conversation, or the idea that changed the way they think or lead. Then Monday morning arrives. A leader walks back into work. The inbox is full. A team member calls in sick. Customers need attention. Priorities compete. Deadlines don’t move. In that moment, what usually wins? The new behavior learned during the program… Or the habits built over the last five years? That’s when my perspective changed. Training doesn’t fail. Habits simply win more often than we think. Behavior change doesn’t happen because of a single learning event. It happens when learning is connected to a real business problem, made relevant to the role, practised consistently, and reinforced through coaching, feedback, and everyday conversations. I’ve also noticed that the business conversation is evolving. A few years ago, success was often measured through completion reports, attendance, and learning hours. Today, leaders are asking better questions. Did customer experience improve? Did leaders coach differently? Did team performance improve? Did behaviour actually change? I think those are the questions Learning & Development should be helping answer. Because our role isn’t just to create memorable programs. It’s to help create lasting behavior change. Today, whenever someone asks me to design a learning program, my first question is no longer, “What do we want people to know?” It’s, “What do we want people to do differently on Monday morning?” Because that’s where the real test begins. #Leadership #LearningAndDevelopment #LeadershipDevelopment #CapabilityBuilding #BehaviorChange #LearningCulture #Coaching #PeopleDevelopment #BusinessTransformation #FrontlineLeadership

In customer experience (CX), the closed-loop feedback (CLF) model has been a cornerstone for over two decades, originally designed to ensure responsiveness and adaptation. It's time for a change. With the advent of artificial intelligence, it's clear that merely adapting this model isn't enough. It's old tapes. It needs to evolve. Here's what's next: Real-time Interaction Management: Traditional CLF reacts to feedback after the fact. And, traditionally, closing the "inner loop" requires a human to follow up. AI turns this on its head. Imagine a system that adjusts the customer journey in real-time based on predictive analytics, reducing friction points before they affect the customer experience. Large Action Models: We all know that AI can dive deep into data lakes to instantly identify patterns and root causes of customer dissatisfaction. This rapid analysis allows companies to not only close the feedback loop faster, but also implement more effective solutions. This will come in the evolution of Large Language Models, or LLMs, to LAMs, or Large Action Models. Continuous Learning Systems: AI transforms CLF from a loop that ends into continuous cycle of improvement. These systems learn from each interaction, constantly updating and refining strategies to enhance the customer experience. This means that the feedback loop is ever-evolving, driven by AI's ability to adapt to new information and complex variables, seamlessly. CX leaders have to embrace AI's potential to redefine our foundational practices. It's time to innovate beyond the traditional CLF and leverage AI to deliver personalized experiences, and at scale. How are you thinking about adaptive, predictive, and personalized CX strategies? Your answer can't be to hire more people to close more loops. #customerexperience #ai #journeymanagement #survey #CLF

Not every design principle should make your product more engaging. Some should protect people. You’ve probably seen Laws of UX, but its creator, Jon Yablonski also runs another brilliant project: humanebydesign.com It’s a framework for building digital products that respect users, not just attract them. Core principles: 1. Resilient → Design for the most vulnerable and anticipate misuse 2. Empowering → Centre on the value products provide to people  3. Finite → Respect people’s time and focus on meaningful content 4. Inclusive → Reflect the full range of human diversity 5. Intentional → Add friction where needed and favour long-term well-being 6. Respectful → Protect attention and digital health 7. Transparent → Be honest, clear, and free of dark patterns Honestly, I teach and implement this way too little myself, still stuck very much in the optimisation game. So this isn’t preaching, it’s sharing. And as usual with Yablonski’s work, the site is beautifully crafted, full of thoughtful illustrations and links to in-depth articles and research on each principle. So dive in, enjoy, just as I will!

Every company says they listen to customers. But most just hear them. There's a difference. After spending years building feedback loops, here's what I've learned: Feedback isn't about collecting data. It's about creating change. Most companies fail at feedback because: - They send random surveys - They collect scattered feedback - They store insights in silos - They never close the loop The result? Frustrated customers. Missed opportunities. Lost revenue. Here's how to build real feedback loops: 1. Gather feedback intelligently - NPS isn't enough - CSAT tells half the story - One channel never works Instead: - Run targeted post-interaction surveys - Conduct deep-dive customer interviews - Analyze product usage patterns - Monitor support conversations - Build customer advisory boards - Track social mentions 2. Create a single source of truth - Consolidate feedback from everywhere - Tag and categorize insights - Track trends over time - Make it accessible to everyone 3. Turn feedback into action - Prioritize based on impact - Align with business goals - Create clear ownership - Set implementation timelines But here's the most important part: Close the loop. When customers give feedback: - Acknowledge it immediately - Update them on progress - Show them implemented changes - Demonstrate their impact The biggest mistakes I see: Feedback Overload: - Collecting too much data - No clear action plan - Analysis paralysis Biased Collection: - Listening to the loudest voices - Ignoring silent majority - Over-indexing on complaints Slow Response: - Taking months to act - No progress updates - Lost customer trust Remember: Good feedback loops aren't about tools. They're about trust. Every piece of feedback is a customer saying: "I care enough to help you improve." Don't waste that trust. The best companies don't just collect feedback. They turn it into visible change. They show customers their voice matters. They build trust through action. Start small: 1. Pick one feedback channel 2. Create a clear process 3. Act quickly on insights 4. Show results 5. Scale what works Your customers are talking. Are you really listening? More importantly, are you acting? What's your approach to customer feedback? How do you close the loop? ------------------ ▶️ Want to see more content like this and also connect with other CS & SaaS enthusiasts? You should join Tidbits. We do short round-ups a few times a week to help you learn what it takes to be a top-notch customer success professional. Join 1999+ community members! 💥 [link in the comments section]

Designing training programs that actually transform learners? Start with this timeless truth: People don’t learn just by listening. They learn by doing. One of the models I often use while designing development interventions is the 70-20-10 model of learning. Originally developed by McCall, Eichinger, and Lombardo, this framework continues to remain relevant — even in an age of AI-driven learning and digital platforms. Here’s how it breaks down: 1) 70% – Experiential Learning - Learning by doing. On-the-job tasks, stretch assignments, simulations, and real-life decision-making. This is where actual transformation happens. It’s the space where knowledge turns into capability. 2) 20% – Social Learning - Learning from people. Through feedback, coaching, mentoring, peer discussions — we learn by observing, reflecting, and engaging with others. It deepens context and creates community. 3) 10% – Formal Learning - Learning from structured content. Workshops, courses, textbooks, instructional videos. Still important — but only a small piece of the bigger puzzle. When I design workshops, I treat this model not as a formula — but as a design principle. The formal workshops (10%) introduce key concepts. The social components (20%) reinforce it through feedback and peer exchange. But it’s the on-the-job application (70%) that brings the real shift. Because people don’t remember slides — they remember experiences. The 70-20-10 model is a reminder that learning isn’t an event. It’s a process. Transformation doesn’t come from knowing… it comes from doing. If you're building learning programs for your organization, start by asking: “Where will this show up in their real work?” That’s where learning becomes meaningful. #LearningAndDevelopment #CorporateTraining #ManishKhanolkar

Engaging workshops are highly misconceived these days Audience engagement has been redefined in 2026 We feel we are speaking to the audience, and their responses are doing the job in the background But what gets missed is the relevance to their goal behind sitting for that 2-4 hour session with questions in their mind That’s where most corporate training quietly breaks down. Not because of poor delivery But because of a disconnect between the training room and real work. Here’s what actually goes wrong: - People sit through content that sounds good but doesn’t reflect their day-to-day reality. - They follow structured activities but don’t get space to question, challenge, or relate. - They participate but not honestly because the room doesn’t feel safe enough. And once they’re back at work, the learning feels distant. So they default to what they’ve always done. If you want training to actually translate into behaviour, here’s what needs to shift: 1. Start with their reality, not your framework Use their language, their challenges, their context. Relevance drives attention. 2. Loosen the structure to allow real conversations Not every moment needs an activity. I focus more on unscripted discussions personally because they reveal much more than planned activities 3. Create space for honest participation People need to feel safe to disagree, admit gaps, and share what’s actually happening at work. 4. Co-create learning instead of delivering it The more participants shape the discussion, the more ownership they feel towards applying it. 5. Prioritise applicability over completeness It’s better to use one idea well than to understand ten concepts superficially. Training doesn’t fail because people don’t understand. It fails because they don’t see themselves in it. The shift is simple: Move from designing a perfect program → designing conversations that are reflective and eye-opening #learninganddevelopment #facilitation #softskillstraining #corporatetraining #corporatefacilitation

User Feedback Loops: the missing piece in AI success? AI is only as good as the data it learns from -- but what happens after deployment? Many businesses focus on building AI products but miss a critical step: ensuring their outputs continue to improve with real-world use. Without a structured feedback loop, AI risks stagnating, delivering outdated insights, or losing relevance quickly. Instead of treating AI as a one-and-done solution, companies need workflows that continuously refine and adapt based on actual usage. That means capturing how users interact with AI outputs, where it succeeds, and where it fails. At Human Managed, we’ve embedded real-time feedback loops into our products, allowing customers to rate and review AI-generated intelligence. Users can flag insights as: 🔘Irrelevant 🔘Inaccurate 🔘Not Useful 🔘Others Every input is fed back into our system to fine-tune recommendations, improve accuracy, and enhance relevance over time. This is more than a quality check -- it’s a competitive advantage. - for CEOs & Product Leaders: AI-powered services that evolve with user behavior create stickier, high-retention experiences. - for Data Leaders: Dynamic feedback loops ensure AI systems stay aligned with shifting business realities. - for Cybersecurity & Compliance Teams: User validation enhances AI-driven threat detection, reducing false positives and improving response accuracy. An AI model that never learns from its users is already outdated. The best AI isn’t just trained -- it continuously evolves.

The biggest mistake I made as a 10-months old SaaS founder (so far) 👇 → Not trying to spend more time with users who churned from Scalelist and understand in details why they churned. It sounds stupidly obvious, But this is something I didn’t do well. I spent the last 4 days in the USA with Youssef and 50 other B2B SaaS founders. 3 key elements that constantly came back from the discussions we had there were: 1- If you feel stuck, talk to your users, 2- If you need answers, talk to your users, 3- If you want to satisfy your clients, talk to your users and those who churned, Long story short, No matter what, communicate with your current and previous users. Get information from them will help you avoid taking stupid decisions based on gut feelings. Yesterday, Youssef and I met with Dominic, a former customer. Here’s what I discovered during our conversation: - He canceled Scalelist because of Sales Navigator’s limitations - He decided to stop any form of automation for a while - His outreach process was painfully time-consuming - Automation often lacks the personal touch he values and solves him a lot of time - Switching between prospects is exhausting. But most importantly: We weren’t solving his real problems. Dominic told us he sometimes spent 6 hours reaching out to 200 prospects. He dreams of doing that process by just talking to a software or his phone and ideally in a few minutes each day. Talking to Dominic gave me clarity. It’s not just about building features. It’s about understanding and potentially solving the frustrations of real people. - - Lesson learned: Churn isn’t failure. It’s feedback in disguise. Would love to hear your thoughts—what’s your biggest SaaS lesson (Comment below) 👇 ?