Prototyping Tools for Designers

Customer discovery via functional prototypes + PostHog is night & day better than the old school way of asking for feedback on Figma mockups. Here's why: I get to observe actual user behavior instead of asking the user to guess how they might use my product. My favorite example of why this matters comes from a Sony Walkman user study. They asked a bunch of people what they thought about a yellow walkman and they said "so sporty! not boring like the black one!". And yet, when they were given the opportunity to take a walkman home after the study, everyone picked the black one. We learned a lot more from user behavior than we did expressed preferences. Here's my setup for now observing user behavior from prototypes: 1. Create a functional prototype in your favorite prototyping tool (Bolt, Lovable, Reforge Build, Magic Patterns, Claude Code) 2. Ask the prototyping tool to integrate PostHog analytics 3. Ask the prototyping tool to instrument key user actions in PostHog Then you get all of these ways of observing actual behavior: - DAUs \ WAUs \ retention curves - I can actually see if people come back and use my prototype instead of taking their word for it - Action metrics dashboards - I can see what actions people are taking vs not - Post-usage survey - I can add a built-in pop-up survey to ask the user a question about the experience after they have engaged with the prototype - Session replays - I can see exactly where people are clicking and how they are using the product to identify usability issues - Heatmaps - I can see what part of my design is working across all sessions I'd never go back to testing with just a mockup after this.

Designers, I used to think UX research was about talking to users as fast as possible. So I’d jump straight into interviews, surveys, usability tests, whatever felt right at the time. The problem? I’d come out with a lot of insights… and still struggle to make clear decisions. What I learned the hard way: Most research doesn’t fail because of bad tools. It fails because there’s no clear research plan. I made every classic mistake: → Vague research goals → Questions that quietly confirmed my own assumptions → Methods chosen because they sounded impressive → No clear idea of how insights would actually influence design Everything changed when I started planning research properly. Recently, I revisited my process using a guide from Lyssna, and it reinforced what experience had already taught me: a good research plan doesn’t slow you down, it saves weeks of rework. For example, on a checkout redesign project, my original question was: “Why are users dropping off?” Using a structured plan helped me reframe it into: → What assumptions are we testing? → Which user segment matters most right now? → What decision will this research unlock? That shift alone made the research more focused, easier to explain to stakeholders, and far more actionable. One quick tip that’s had the biggest impact on my work: Write research questions that drive decisions, not curiosity. Asking “Do users like this?” rarely helps. Asking “What prevents users from completing this on mobile?” actually does. If your research ever feels messy, hard to justify, or disconnected from design decisions, this is a solid reset. Lyssna’s user research plan guide walks through the process step by step, with real examples, and includes a free, practical template you can use immediately. User research plan guide + free template → https://lnkd.in/dtEB9p7e I hope that this will help you. Like & Repost, If you find this helpful. Share your thoughts in the comments. Enable notification 🔔 Don't forget to follow Abraham John #uiux #design #designgod #uidesign #uiuxdesign #uidesign #ui #uxdesign

The most important thing a product manager can do with a new product is to run frequent usability testing, to see what blockers you have in your product that cause it not to be used. Most important rule of usability testing is that once you state the task to the person taking the test, you let them know that you won't be answering any questions during the test. All you will say is "what are you thinking". It is important to writhe in pain as your users get totally lost in your product. Only by feeling that pain do you prioritize fixing all of those problems. In our recent usability testing of BVS event invitation system https://partyclick.com (led by Kate Tyshchenko 🇺🇦), we found errors like this: a) Users had no idea of all of the controls hidden behind a simple gear icon. We need to better expose important controls. b) We have a mechanism where the party host can message all of the guests, e.g., to tell them about what to bring, where to park, etc. But hosts did not know if this would send one message with everyone copied (usually a bad idea) or individual messages per guest. They also didn't know if the message would come from the host, or, from PartyClick. c) When hosts wanted to check on the RSVPs we have received so far, we have a GUEST RESPONSES button, but the way we designed this, it looks like a table header, not a button. We'll fix all of these issues, and then test again. Rinse and repeat until you have no usability issues with your product. It is always more vital that you perfect the most common user paths through your product than adding more features. Stay tuned for more updates from PartyClick.com, and please try us out for your next event!

One of the most common mistakes teams make when evaluating early product features is asking users whether they like an idea and treating the answer as evidence. Decades of behavioral research and very practical product research work show that this is a weak signal. People are generally bad at predicting what they will use, adopt, or pay for in the future, especially when there is no cost, effort, or tradeoff attached to their answer. That is why early feature evaluation should focus on behavior rather than belief. When a feature is only a concept, a smoke test can already tell you a lot. Exposing users to the idea through a landing page, announcement, or waitlist and observing whether they click or sign up answers a very specific question. Is this worth building at all, not whether it sounds good in theory. When an idea becomes clickable, fake door tests bring the decision closer to real behavior. Placing a realistic entry point inside the product and observing who actually tries to use it shows intent in context. The power of this method comes from the fact that users believe the feature is real at the moment of interaction. Transparency afterward is essential, but the action itself is the signal. For complex or technically risky features, especially AI, automation, or recommendation systems, Wizard of Oz prototyping allows teams to observe natural behavior before automation exists. Users interact with what looks like a fully functional system, while a human performs the work behind the scenes. This reveals expectations, decision making, and breakdowns that are invisible in abstract discussions. Concierge MVPs go one step further by making the human involvement explicit. Here, the value is delivered manually, often in a high touch way, to see whether users actually engage, return, and benefit. If people do not use or value the service when friction is low and quality is high, automation will not fix the underlying problem. Across all of these approaches, the principle is the same. Early feature evaluation should not ask people what they like. It should watch what they do when a real opportunity to engage is placed in front of them.

“I don’t like it.” “Ok, so what would you like instead?” “…I don’t know.” Real conversation from one of my recent sessions. My first instinct was frustration. My second was: wait, this is actually the whole point! Because here’s the truth we sometimes forget: users are excellent at recognizing what doesn’t work, and genuinely bad at articulating what would. That’s not a flaw in your participants. That’s just how humans work. So how do you find “the version that works” when users can’t tell you? The research is actually pretty clear on this: 🔹 Pairwise comparisons over open questions. Studies show people perform significantly better when comparing two options side by side than when asked to define their preferences from scratch, especially when they’re unsure what their criteria even are. Show A vs. B, not a blank canvas. 🔹 Think-aloud protocols. Don’t ask what they want. Watch what they struggle with. Research on usability methods found think-aloud testing was significantly associated with products actually getting iterated and improved afterward. Behavior beats opinion. 🔹 Triangulate your methods. studies found user testing, interviews, and surveys each caught usability problems the others missed. User testing alone found just over half. No single method gives you the full picture. 🔹 Iterate, don’t interrogate. Usability testing isn’t about extracting the answer from users in one session. It’s about creating enough versions and enough contrast that the right direction reveals itself. “I don’t like it” isn’t a dead end, It’s data.

Figma is now native in Outset . It changes what prototype testing can actually produce. The insight that changes a design decision usually disappears in seconds. A participant hesitates on step 3 and finds a workaround. Someone clicks a field three times expecting a response and moves on. The signal was real. By the time a follow-up question arrives, they've already rationalized it away. That's something I've thought about a lot building this company. We're trying to understand why people do what they do. Prototype testing, where the most consequential design decisions get made, has always captured whether people completed the task. Not what happened while they did. Now it captures both. Figma prototype testing runs natively inside Outset. The AI observes what participants do during a session in real time and probes based on what it actually saw, while the participant is still in the moment. Not from a recording reviewed afterward. While it's happening. When the study closes, Figma's interaction data flows into Outset's synthesis alongside everything participants said. Behavioral signals, qualitative depth, and granular interaction analytics in one place. No stitching. No reconciling three data sources after the fact. No other tool does both. The combination of real-time behavioral probing and post-study Figma analytics in a single synthesis is the most complete research output prototype testing has ever produced. We built Outset to close the gap between what people say and what they actually do. More here: https://lnkd.in/gitAEhz9

The key to effective usability testing? Approaching it with a Human-Obsessed mindset. This is crucial. It determines whether your improvements are based on assumptions or real user insights. It guides how you engage with: → User needs → Common tasks → Pain points → and Preferences throughout their journey on your site. Usability testing isn’t straightforward. It requires a deep understanding of user behavior and continuous refinement. How do you start a Human-Obsessed usability testing approach? Follow these steps: 1. Set Specific Goals — Focus on areas like navigation and checkout.  — Know what you aim to improve. 2. Match Test Participants to Users — Ensure your participants reflect your actual user base.  — Diverse feedback is key. 3. Design Realistic Tasks — Reflect common user goals like finding a product or making a purchase.  — Keep it real. 4. Choose the Right Method — Decide between moderated (in-depth) and unmoderated (scalable) tests.  — Pick what suits your needs. 5. Use Effective Tools — Leverage tools like UserTesting or Lookback.  — Integrate analytics for comprehensive insights. 6. Create a True Test Environment — Mirror your live site.  — Ensure participants are focused and undistracted. 7. Pilot Testing — Run a pilot test to refine your setup and tasks.  — Adjust before full deployment. 8. Collect Qualitative and Quantitative Data — Gather user comments and behaviors.  — Measure task completion and errors. 9. Report Clearly and Take Action — Use visuals like heatmaps to present findings.  — Prioritize issues and recommend improvements. 10. Keep Testing Iteratively — Usability testing should be ongoing.  — Regularly test changes to continuously improve. Human-Obsessed usability testing is powerful. It’s how Enavi ensures exceptional user experiences. Always. Use it well. Thank us later.

Sometimes QA teams skip this test type. Yet it’s the one that impacts users the most. Here’s your quick Usability Testing Mini Guide: ✅ 1. Define clear usability goals Decide what “good” looks like. Measure task success rate, completion time, and satisfaction. ✅ 2. Pick the right method Moderated, unmoderated, or remote. Match the test to your goals and resources. ✅ 3. Use realistic user scenarios Focus on actual workflows like “checkout,” “apply filter,” or “create account.” ✅ 4. Recruit real users Get both new and experienced users to uncover different challenges. ✅ 5. Let them think aloud Silence speaks volumes. Watch where users hesitate or get stuck. ✅ 6. Track key metrics Completion time, number of retries, and error rates show real patterns. ✅ 7. Capture quotes and emotions A comment like “I can’t find the button” is pure gold for UX improvement. ✅ 8. Watch sessions back Tools like Hotjar or Lookback help you see recurring pain points. ✅ 9. Prioritize issues by impact Fix blockers in navigation, content, or layout first. ✅ 10. Retest fixes Validate that your changes actually solved the problem before closing it. A technically perfect product can still fail if users find it confusing. Usability testing ensures your product feels as good as it functions.

To my non-UXR product friends: Giving a researcher mocks or a prototype and saying “test this” means nothing. We need to know what you want to assess (“test”) or learn. Do you want to know: 🧐 Can users accomplish a specific task? 🧐 Do users run into blockers or usability issues? 🧐 Can users discover the entry point? 🧐 Can users intuit the purpose of the feature from the icon or label? 🧐 Do users understand what the feature is doing? 🧐 Do users see this feature as useful? 🧐 Do users see the feature as easy-to-use? 🧐 What are users’ general first impressions (likes, dislikes, suggestions for improvement)? 🧐 Is one entry point design associated with a different behavior than another entry point design? There are a million things we can test using a mock or prototype, and we don’t know what your goals are until you tell us. Once you tell us what you want to learn, that’s when we can make research magic happen ✨ ❓❓ UXRs, if someone hands you a mock or prototype and says “test this,” what’s your first assumption about what they want to learn? #UXResearch #ProductDesign #UserExperienceResearch

Usability testing is the ultimate insurance policy for your product—protecting you from wasting time, money, and effort on features that users don’t need, won’t use, or might outright hate. Being a UX Designer, Product Owner, or SME might make you knowledgeable about a product, but it does NOT automatically make you a good User Researcher. 1. You’re Too Close to the Product (a.k.a. Designer’s Curse) 2. You Think You Know What Users Want (But You Don’t)  3. You’re Looking for Validation, Not Truth  4. You Can’t Turn Off “Problem-Solving Mode 5. You Don’t Have the Right Research Methods I’ve watched the slow decline of proper user testing, and the consequences are costly—bad or misleading data will steer your software product down the wrong (and very expensive) path. First let's start with: Usability / User Testing: What it is and What it isn't. What IS usability testing? ✅ Observing real users in action without interfering, so you can learn what’s working (and what’s painful). ✅ Asking open-ended “why” questions to uncover real usability issues, not just surface opinions. ✅ Testing with one user at a time to avoid bias, influence, and groupthink disasters. ✅ Encouraging users to think out loud so you understand their decision-making process. ✅ Creating realistic tasks that match how users would naturally interact with your product. ✅ Letting the data speak for itself—not defending design choices in real-time. What ISN’T usability testing? ❌ Running a focus group where one outspoken person shapes the entire narrative. (This happens often and is NOT User Testing and leads to Groupthink - the quietest person may have the best ideas but won't share it). ❌ Asking leading questions like “Wouldn’t this be easier if we just added more buttons?” ❌ Turning the test into a tutorial—if you have to explain how to use it, it’s already broken. ❌ Looking for validation instead of insights—“Do you like this?” is not a usability test. ❌ Gathering opinions instead of behaviors—what people say they’ll do ≠ what they actually do. ❌ Ignoring uncomfortable feedback because “they just don’t get it”—users are always right (even when it hurts). Tune in later for Part 2...