UX Design For Startups

💎 60 UX Strategy Methods And Activities (Figma) (https://lnkd.in/eCDU-vhR), a large repository of UX methods, templates and activities for ideation sessions and product sprints, from storyboards and brainwriting to 6 thinking hats, journey mapping and concept testing. Neatly put together in one single place by fine folks at Merck. The team has also put together a very thorough overview of their UX Strategy Kit (https://lnkd.in/ek5dEYn4), broken down by categories for strategy, observation, ideation and warm-up, along with detailed video walkthroughs, examples and step-by-step guides. Frankly, most of these methods are unfamiliar to me. And by no means is the point to actually study and apply all of them. What works for you works for you. To strategize, I rely on How Might We but also think about metrics that should be moved once we implement some features or refine some user flows. For event storming and brainstorming, I tend to rely on Bono’s 6 thinking hats to align brainstorming, and (of course) journey mapping. For ideation, I love using storyboards to jump right into the user’s success story, but would also use card sorting with cut-out paper cards to understand user’s mental model. And for almost every project, I’d run concept testing with tree testing or Kano model, or low-fidelity/paper prototyping to understand if we are on the right track. Once you sprinkle a bit of critical thinking, early user testing and strategic planning across the design work, you gain confidence that you are moving in the right direction. And really that’s all you need. A few of my personal bookmarks with UX methods and activities: UX Tools For Better Thinking, by Adam Amran 👏🏽 https://untools.co/ Playbook For Universal Design (+ PDF/Powerpoint templates) https://lnkd.in/ernris4g UX Methods & Projects, by Vernon Fowler https://lnkd.in/eAHaiaSm 18F Method Cards https://methods.18f.gov/ Hyperisland UX Methods Resource Kit 👍 https://lnkd.in/eDTaci7T How To Design Better UX Workshops, by Slava Shestopalov https://lnkd.in/edxqCC-n How To Run UX Workshops With Users, by yours truly https://lnkd.in/ejm7_TsS Happy designing, everyone — I hope you’ll find these guides and resources helpful to get started. Just don’t feel like you have to try out all of them. It might be much more worthwhile to get early feedback from stakeholders and end users, even if your work isn’t really “good” enough. Good luck! #ux #design

💡How to frame problems in product design (7-step guide & tools) Framing problems effectively is a critical skill that can influence the quality of design. 1️⃣ Define the context: Start by establishing the context in which the problem exists. Understanding the environment, user demographics, technological constraints, and business objectives will help shape a comprehensive view of the issue. For example, identifying that users struggle with a mobile app while in areas with low connectivity provides a specific context to focus on. 2️⃣ Identify user needs & pain points: Collect and analyze data from user research such as interviews, surveys, usability testing, and field observations. Highlighting user pain points & needs is essential to framing a problem that is relevant. For instance, noting that users feel frustrated when they cannot quickly navigate through a menu can define a clear problem area. 3️⃣ Frame the problem: Techniques like the "Five Whys," which involves asking "why" five times to get to the root cause of a problem, can help uncover deeper insights. Additionally, considering the problem from different stakeholders' perspectives can open up new avenues for solutions. 4️⃣ Articulate the problem as a "How might we" question: Once you've identified a specific user need or a pain point, articulate the problem as an open-ended question that invites creative thinking. For example, "How might we make the menu navigation more intuitive so that users can find what they need with fewer taps?" 5️⃣ Break down large problems: Complex problems can often be overwhelming and difficult to tackle all at once. Break them down into smaller, manageable components that can be addressed individually. For example, a large problem like "improve the mobile app experience" can be broken down into "improving load times," "simplifying user interactions," and "enhancing visual appearance." 6️⃣ Specify constraints and criteria: Define what constraints must be considered, such as technological limitations, budgetary constraints, and time frames. Also, consider what success looks like for solving the problem. Clear criteria help to keep the problem-solving process focused and measurable. 7️⃣ Validate the problem statement: Before moving forward with solving the problem, validate the problem statement with real users and stakeholders to ensure it truly reflects their needs and the business goals. This may involve revisiting user research or conducting additional interviews. 🔨 Tools ✔ Untools: Curated collection of thinking tools and frameworks to help you solve problems (by Adam Amran)   https://untools.co/ ✔ UX Challenges: practical exercises to train yourself in crucial UX skills (by Tommy Geoco) https://lnkd.in/dZvakiJd ✔ Design thinking toolkit (by IBM) https://lnkd.in/dhV95BTf 🖼 Untools by Adam Amran #design #designthinking #productdesign #UX #userexperience #problemsolving #designprocess

I built a Claude UX audit skill that mostly relies on heuristics frameworks But there are extra rules that prevent common issues Save this if you're planning to build your own UX skills. They’re three custom checks I added because the same issues kept appearing: ↳ FTU ↳ TRUST ↳ COG They’re not formal frameworks, it's a shared language for recurring UX problems. FTU: First-time user. --- Five checks for what a brand-new user can do on the screen. • FTU.1 Next action obvious Within five seconds, can a first-time user identify what to do next? • FTU.2 No required prerequisite knowledge Does the screen require understanding a concept that hasn’t been introduced yet? • FTU.3 Recoverable mistakes Is the cost of being wrong clear before they commit? FTU.4 Empty states do work • Empty states should teach, not just announce emptiness. • FTU.5 Jargon budget Count product-specific terms. More than two for a first-time user is usually a warning sign. TRUST --- Trust and safety at high-stakes moments. • TRUST.1 Preview before commit Can users see what will happen before it happens? • TRUST.2 Test mode Can they experiment without affecting real customers or data? • TRUST.3 State clarity Is it obvious whether something is draft, live, paused, or scheduled? • TRUST.4 Reversibility How difficult is it to undo? • TRUST.5 Audit trail Can users see what happened, who did it, and when? • TRUST.6 Volume signposting Before high-impact actions, is the scale obvious? • TRUST.7 No dark patterns No forced choice. No hidden cancellation. No guilt copy. No fake scarcity. COG --- Cognitive load. Simple counts that act as warning flags. • COG.1 Decision count More than three decisions before progress is usually a problem. • COG.2 Primary action count There should be one obvious next step. • COG.3 New concept count More than one new concept per screen is often too much. • COG.4 Reading load More than 50 words of body copy is usually worth reviewing. --- It’s surprising how useful it is to have a tool like this available to you whenever you need it. A consistent, objective way to review a product you’ve become too familiar with. After working on the same product for long enough, it’s easy to stop noticing the friction, assumptions, jargon and complexity that new users experience immediately. My hope with these posts is to gently steer the product design AI conversation away from producing more screens faster (and therefore competing with engineers) and focus more on how we can use it to create better experiences for our customers.

How do you figure out what truly matters to users when you’ve got a long list of features, benefits, or design options - but only a limited sample size and even less time? A lot of UX researchers use Best-Worst Scaling (or MaxDiff) to tackle this. It’s a great method: simple for participants, easy to analyze, and far better than traditional rating scales. But when the research question goes beyond basic prioritization - like understanding user segments, handling optional features, factoring in pricing, or capturing uncertainty - MaxDiff starts to show its limits. That’s when more advanced methods come in, and they’re often more accessible than people think. For example, Anchored MaxDiff adds a must-have vs. nice-to-have dimension that turns relative rankings into more actionable insights. Adaptive Choice-Based Conjoint goes further by learning what matters most to each respondent and adapting the questions accordingly - ideal when you're juggling 10+ attributes. Menu-Based Conjoint works especially well for products with flexible options or bundles, like SaaS platforms or modular hardware, helping you see what users are likely to select together. If you suspect different mental models among your users, Latent Class Models can uncover hidden segments by clustering users based on their underlying choice patterns. TURF analysis is a lifesaver when you need to pick a few features that will have the widest reach across your audience, often used in roadmap planning. And if you're trying to account for how confident or honest people are in their responses, Bayesian Truth Serum adds a layer of statistical correction that can help de-bias sensitive data. Want to tie preferences to price? Gabor-Granger techniques and price-anchored conjoint models give you insight into willingness-to-pay without running a full pricing study. These methods all work well with small-to-medium sample sizes, especially when paired with Hierarchical Bayes or latent class estimation, making them a perfect fit for fast-paced UX environments where stakes are high and clarity matters.

One of the most common UX failures I see in today’s fast-paced studies isn’t just bad analysis, but questionnaires that look fine-ish and measure the wrong thing. One technique that consistently fixes this problem is cognitive interviewing. It shifts questionnaire design from guessing what users mean to actually observing how they think while answering your questions. The idea is simple. Instead of launching a survey and hoping respondents interpret each item the way you intended, you sit with a small number of users and walk through the questionnaire with them. After they answer each question, you ask things like: Can you rephrase this in your own words? How did you decide on that answer? What did this phrase mean to you? What shows up is often uncomfortable but extremely useful. - People frequently give the correct answer for the wrong reason. - Seemingly clear terms like at risk, affect, or often are interpreted in very different ways. - True or false formats can hide misunderstanding instead of revealing it. - Response options that look clean on paper do not always match how people think. In practice, this means your survey can look statistically solid while measuring the wrong thing. From a UX perspective, cognitive interviewing strengthens questionnaires at several critical levels. It improves clarity by exposing ambiguous wording immediately. It protects construct validity by showing whether people are answering the concept you care about or a substitute they created on the fly. It reveals how users map their thinking onto response options. It increases confidence in downstream decisions because you know the data reflects real understanding, not lucky guesses. One of the most underrated parts of this technique is that it does not require large samples. A small number of carefully conducted interviews is usually enough to surface the most serious problems before a survey ever goes live. If you design UX questionnaires, this is one of the highest-leverage steps you can add to your workflow. It turns surveys from polished guesswork into instruments that actually measure what you think they measure.

Fixing Frustrating UX Patterns for 2026 UX problems aren’t visual They’re behavioral If you ignore how users scan, you create friction Heatmap Insight Users don’t read They scan Heatmaps show: → Uneven focus → Fast drop-off → Missed content Guide attention or lose it F Pattern: For content-heavy pages Scan: → Top → Left → Across Fix: Strong headlines. Clear hierarchy Z Pattern: For landing pages Scan: → Top → diagonal → bottom Fix: Align CTAs with eye flow Layer-Cake Pattern: Users skim headings They skip the rest Fix: → Strong titles → Clear sections → Easy scanning Spotted Pattern: Attention jumps Users look for: → Keywords → Icons → Visual cues Fix: Highlight key elements Marking Pattern: Focus = one area Everything else is ignored Fix: One focal point Less clutter Bypassing Pattern: Users skip weak content Especially generic intros Fix: Start with value Cut fluff Commitment Pattern: Users engage when it matters Relevance drives depth Fix: Build trust fast Be clear Good design looks nice Great design guides behavior If users can’t find value fast, they won’t stay long enough to care

My approach to addressing user experience challenges involves several steps ⤵️ 1. Understanding User Needs: Conduct user research to understand the goals and pain points of the target audience. Utilize interviews, surveys, and usability testing to gather insights. 2. Collaboration and Alignment: Work closely with cross-functional teams such as product management, engineering, and customer support to align on user goals and prioritize UX issues. 3. Data Analysis: Analyze user data to understand behavior patterns. Look at analytics, feedback, and support tickets to identify areas where users are struggling. 4. Ideation and Sketching: Encourage brainstorming sessions and sketching to come up with creative solutions. Focus on solving the real problems and not just the symptoms. 5. Creating User Journeys and Wireframes: Develop user flows to understand how users will interact with the product. Create wireframes to visualize the structure of the interface. 6. Prototyping and Testing: Create high-fidelity prototypes that simulate the final product. Conduct usability testing to validate design decisions and uncover issues. 7. Iterative Design: Use feedback from usability testing to refine the design. UX is an ongoing process; be prepared to iterate based on user feedback and changing needs. 8. Implementation Support: Assist the development team during implementation to ensure that the design is translated accurately into the final product. 9. Post-Release Analysis: Once the product is released, continue to monitor user feedback and analytics. Be proactive in identifying new challenges and opportunities for improvement. 10. Educate and Advocate: Constantly educate stakeholders on the importance of UX and advocate for resources and prioritization of UX initiatives. This cyclical approach helps in creating a product that not only meets user needs but also adapts to changes and continuously improves over time. #ux #strategy #userexperience #innovations

Find the shape of your design decision. Fix the constraint, then scale the problem space. Most teams argue about design because they don’t know what kind of UX problem they’re in. Once you can read the UX metric stack, the next decision becomes obvious. In many of my work sessions with customers, we’re trying to make a call using constraints and UX metrics to understand where users actually are. These meetings can be groups of five to ten people, and there’s rarely time for deep analysis. Teams often need orientation to ideate. Not a full answer, but clarity on what the design signals mean and how to move forward. Iteration can always come later. In the moment, people want to know: what does this tell us, and what should we do next? Over time, I started noticing a pattern in how I frame design decisions and recommendations. With a small set of UX metrics in a stack, you can orient a team in about 30 seconds. You can quickly see which problems matter most. This is where design leverage starts. You cannot earn trust if people are not clear on what you are presenting to them. I often sit at the front end of fast, million dollar decisions at ZURB that compound over the life of an initiative. These decisions tend to fall into the same few shapes. Think of UX metrics as four layers that sit on top of each other. 1. Clarity Do people understand what this is and what to do next? 2. Ability Can they do it quickly and without mistakes? 3. Confidence Do they feel safe, in control, and willing to continue? 4. Commitment Do they come back, adopt it, recommend it, and rely on it? Here are the four common shapes of design problems. These patterns show up again and again. Each one tells you what kind of problem you actually have. → Confusion Trap Clarity is low. Everything above it becomes noisy or misleading. Users are not oriented. They guess, hesitate, and click around. The job here is to fix comprehension before touching polish, new features, or conversion tactics. →  Friction Wall Clarity is solid, but ability is low. Time is high, errors increase, and drop-offs appear. Users get it, they just cannot do it. The move is to remove steps, simplify flows, reduce cognitive load, tighten IA, and improve affordances. → Trust Gap Clarity and ability look fine, but confidence is low. Doubt, anxiety, perceived risk. The experience works, but it does not feel safe. This is common in fintech, healthcare, and AI. Teams need to focus on building reassurance. Transparency, guardrails, explanations, error prevention, and clear feedback about what happens next. → Adoption Leak The top of the stack is healthy, but commitment is weak. The design works, but there is no habit. The move is to focus on the value loop. Activation timing, defaults, reminders, integrations, onboarding sequence, and ongoing use cases. Finding the shape of your decision helps orient everyone on a team. You fix the lowest broken layer…and everything above it gets easier!

I used to wonder how to make my UX work more impactful. I saw designers getting astonishing results for their clients/stakeholders so I knew it was possible. I just didn’t know how to actually do it. I knew the standard processes and tools. So I thought I should hit my stakeholders over the head with how they’re doing it wrong and be the guy always fighting for users. That should do the trick, right? Wrong. Turns out I needed to: → Listen more → Follow my gut → Break the rules That’s when things started clicking. I pieced this together a long time ago in the tech world. Now I apply it to client projects. And it works... We’ve helped our clients: → 3.5x their conversion (eCommerce) → Oversubscribe their A round by 55% (health tech) → Rack up 8 awards for innovation (education) Here’s exactly how we did it: 1. Understand goals and constraints: - How is success measured? - What time pressure exists? - What have they already tried? - What are the biggest challenges? - Who are their customers or users? - What unique assets or data do they have? Literally everything depends on this. Asking the right questions upfront means better insights, better design recommendations, and better collaboration. 2. Audit the current product: - Review every screen, state, and flow - Gather screencaps and recordings - Identify opportunities, risks, problems Step 1 was the big picture. This is about details. Experience, intuition, and judgement matter here. 3. Make recommendations: - Prioritize by impact - Call attention to the top 3 issues - Present findings clearly. We use slides. Show what's happening with the current product—and how to transform it. 4. Agree on priorities, timelines, and process: - What’s the most important thing to do next? - How will we execute the work? Too many designers get caught up on "right" process. Right depends on context. There are lots of ways to succeed. 5. Execute the work: - Research, design, prototyping, testing - Every decision or finding gets tied to goals or risks AI is speeding this part up. It's a wild time. 6. Communicate & collaborate throughout: - Design is a team sport—we win together - The whole team knows what’s happening, and why - Nobody's left guessing Pro tip: Clarity is a gift designers are well positioned to give product teams. Capture roadmap, process, and status in a single visual to do this. Not sure how? DM me. 7. Ship product: “Everyone has a plan until they get punched in the face”—Mike Tyson. Things get real when they're put in front of users. Do that fast, but not so fast that you don’t get a good signal from the market. – I love helping clients succeed. Over time, I found these traits help: Teamwork Pragmatism Bias for action Lightheartedness Commitment to quality Find your own way. Break the rules when needed. Stay focused on impact. That’s what makes the work meaningful—and what makes for truly successful products (and design careers).

The product discovery framework we use before every project. Free. Takes 2 hours. Prevents 2-month reworks. We call it the Problem Stack Canvas. Here's how it works: Layer 1: Who exactly? Not 'our users.' Describe one specific person. Their role. Their day. The exact moment the problem occurs. The more specific, the more useful. Layer 2: What are they doing now? How is this problem currently being solved? Spreadsheet? WhatsApp group? No solution at all? Understanding the current workaround tells you the real pain level. Layer 3: What does 'done' look like? Define success in one sentence from the user's perspective. Not from the product's perspective. Layer 4: What's the cost of NOT solving it? In money, time, or risk. If there's no cost, it's not a real problem. Layer 5: What's the minimum feature set that solves 80% of the pain? Not the full vision. The smallest possible thing that delivers real value. This is your MVP scope. Every project we start with this framework produces a tighter spec, fewer mid-project changes, and better outcomes. Save this. Use it before your next product conversation. #ProductDiscovery #UXResearch #StartupFramework #ProductManagement #MVPDesign