🔬 How To Run UX Research In B2B and Enterprise. Practical techniques of what you can do in strict environments, often without access to users. 🚫 Things you typically can’t do 1. Stakeholder interviews ← unavailable 2. Competitor analysis ← not public 3. Data analysis ← no data collected yet 4. Usability sessions ← no users yet 5. Recruit users for testing ← expensive 6. Interview potential users ← IP concerns 7. Concept testing, prototypes ← NDA 8. Usability testing ← IP concerns 9. Sentiment analysis ← no media presence 10. Surveys ← no users to send to 11. Get support logs ← no security clearance 12. Study help desk tickets ← no clearance 13. Use research tools ← no procurement yet ✅ Things you typically can do 1. Focus on requirements + task analysis 2. Study existing workflows, processes 3. Study job postings to map roles/tasks 4. Scrap frequent pain points, challenges 5. Use Google Trends for related search queries 6. Scrap insights to build a service blueprint 7. Find and study people with similar tasks 8. Shadow people performing similar tasks 9. Interview colleagues closest to business 10. Test with customer success, domain experts 11. Build an internal UX testing lab 12. Build trust and confidence first In B2B, people buying a product are not always the same people who will use it. As B2B designers, we have to design at least 2 different types of experiences: the customer’s UX (of the supplier) and employee’s UX (of end users of the product). In customer’s UX, we typically work within a highly specialized domain, along with legacy-ridden systems and strict compliance and security regulations. You might not speak with the stakeholder, but rather company representatives — who regulate the flow of data they share to manage confidentiality, IP and risk. In employee’s UX, it doesn’t look much brighter. We can rarely speak with users, and if we do, often there is only a handful of them. Due to security clearance limitations, we don’t get access to help desk tickers or support logs — and there are rarely any similar public products we could study. As H Locke rightfully noted, if we shed the light strongly enough from many sources, we might end up getting a glimpse of the truth. Scout everything to see what you can find. Find people who are the closest to your customers and to your users. Map the domain and workflows in service blueprints and . Most importantly: start small and build a strong relationship first. In B2B and Enterprise, most actors are incredibly protective and cautious, often carefully manoeuvring compliance regulations and layers of internal politics. No stones will be moved unless there is a strong mutual trust from both sides. It can be frustrating, but also remarkably impactful. B2B relationships are often long-term relationships for years to come, allowing you to make huge impact for people who can’t choose what they use and desperately need your help to do their work better. [continues in comments ↓] #ux #b2b
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Your research findings are useless if they don't drive decisions. After watching countless brilliant insights disappear into the void, I developed 5 practical templates I use to transform research into action: 1. Decision-Driven Journey Map Standard journey maps look nice but often collect dust. My Decision-Driven Journey Map directly connects user pain points to specific product decisions with clear ownership. Key components: - User journey stages with actions - Pain points with severity ratings (1-5) - Required product decisions for each pain - Decision owner assignment - Implementation timeline This structure creates immediate accountability and turns abstract user problems into concrete action items. 2. Stakeholder Belief Audit Workshop Many product decisions happen based on untested assumptions. This workshop template helps you document and systematically test stakeholder beliefs about users. The four-step process: - Document stakeholder beliefs + confidence level - Prioritize which beliefs to test (impact vs. confidence) - Select appropriate testing methods - Create an action plan with owners and timelines When stakeholders participate in this process, they're far more likely to act on the results. 3. Insight-Action Workshop Guide Research without decisions is just expensive trivia. This workshop template provides a structured 90-minute framework to turn insights into product decisions. Workshop flow: - Research recap (15min) - Insight mapping (15min) - Decision matrix (15min) - Action planning (30min) - Wrap-up and commitments (15min) The decision matrix helps prioritize actions based on user value and implementation effort, ensuring resources are allocated effectively. 4. Five-Minute Video Insights Stakeholders rarely read full research reports. These bite-sized video templates drive decisions better than documents by making insights impossible to ignore. Video structure: - 30 sec: Key finding - 3 min: Supporting user clips - 1 min: Implications - 30 sec: Recommended next steps Pro tip: Create a library of these videos organized by product area for easy reference during planning sessions. 5. Progressive Disclosure Testing Protocol Standard usability testing tries to cover too much. This protocol focuses on how users process information over time to reveal deeper UX issues. Testing phases: - First 5-second impression - Initial scanning behavior - First meaningful action - Information discovery pattern - Task completion approach This approach reveals how users actually build mental models of your product, leading to more impactful interface decisions. Stop letting your hard-earned research insights collect dust. I’m dropping the first 3 templates below, & I’d love to hear which decision-making hurdle is currently blocking your research from making an impact! (The data in the templates is just an example, let me know in the comments or message me if you’d like the blank versions).
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💡 Mapping user research techniques to levels of knowledge about users When doing user research, it's important to choose the right methods and tools to uncover valuable insights about user behavior. It's possible to identify 3 layers of user behavior, feelings, and thoughts: 1️⃣ Surface level - Say & Think This level captures what users say in conversations, interviews, or surveys and what they think about a product, feature, or experience. It reflects their stated opinions, thoughts, and intentions. Example: "I prefer simple products" or "I think this app is easy to use." Methods: Interviews, Questionnaires. These methods capture stated thoughts and opinions. However, insights may be influenced by social norms or biases. 2️⃣ Mid-level - Do & Use This level reflects what users actually do when interacting with a product or service. It emphasizes actions, usage patterns, and observed behaviors, revealing insights that may differ from what users say. Example: Users may claim they enjoy customizing app settings, but data shows they rarely change default options. Methods: Usability Testing, Observation. Observation helps to reveal gaps between what people say and what they actually do. 3️⃣ Deep level - Know, Feel and Dream This level uncovers deep motivations, emotions, desires, and aspirations that users may not be consciously aware of or may struggle to articulate. It also includes tacit knowledge—things people know intuitively but find hard to express. Example: A user might not realize that their preference for a minimalist design comes from the information overload of a current design. Methods: Probes (e.g., participatory design, diary studies). Insights collected using these methods will uncover implicit and emotional drivers influencing behavior. 📕 Practical recommendations for mapping ✅ Triangulate insights by using multiple methods. What people say (interviews/surveys) may differ from what they do (observations) and feel. That's why it's essential to interpret these results in context. For example, start with interviews to learn what users say. Follow up with usability testing to observe real behavior. Use probes for long-term or emotional insights. ✅ Align research with business goals. For product improvements, focus on usability testing to catch interaction issues. For innovation, use probes to generate new ideas from user insights. ✅ Practice iterative learning. Apply surface techniques (like surveys) early to refine assumptions and guide more in-depth research later. Use deep techniques (like probes) for strategic decisions and to foster innovation in long-term projects. 🖼️ UX Research methods by Maze #ux #uxresearch #design #productdesign #uxdesign #ui #uidesign
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UX research is 𝗻𝗼𝘁 losing relevance. It’s entering a golden era with the power of AI. Understanding users is still a key skill for every PM. It reduces guesswork. Reveals real problems. Strengthens decisions across the product lifecycle. Here’s a breakdown of research methods every PM should use: 🔵 𝗤𝘂𝗮𝗹𝗶𝘁𝗮𝘁𝗶𝘃𝗲 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 → Interviews, field studies, contextual inquiry → Understand the why behind user behavior → Use it in early discovery or to explore new problems 🔵 𝗤𝘂𝗮𝗻𝘁𝗶𝘁𝗮𝘁𝗶𝘃𝗲 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 → Surveys, A/B tests, usage analytics → Track what’s happening at scale → Use it to validate direction and measure impact 🔵 𝗠𝗶𝘅𝗲𝗱 𝗠𝗲𝘁𝗵𝗼𝗱𝘀 → Combine qualitative and quantitative → Get context and confidence from both types of data → Strongest when used across the product lifecycle The best PMs don’t skip research. They use it to make every decision sharper. They combine insight and data. And they do it fast. With AI, UX research is now faster, smarter, and easier. 𝗛𝗲𝗿𝗲 𝗮𝗿𝗲 𝗮 𝗳𝗲𝘄 𝗔𝗜 𝘁𝗼𝗼𝗹𝘀 𝘄𝗼𝗿𝘁𝗵 𝗲𝘅𝗽𝗹𝗼𝗿𝗶𝗻𝗴: ⚡ whyser.ai AI-led interviews with real users ⚡ syntheticusers.com Research with AI-generated personas ⚡ maze.co Automated unmoderated testing ⚡ sprig.com Survey and feedback analysis using AI 𝗪𝗵𝗮𝘁'𝘀 𝗻𝗲𝘅𝘁? Research is evolving. AI gives it speed. You bring the context, decisions, and direction. The best product teams don’t guess. They ask, listen, and learn. Then build. 📌 𝗪𝗮𝗻𝘁 𝗮 𝗳𝘂𝗹𝗹 𝗴𝘂𝗶𝗱𝗲? Product Map mapped the UX methods, tools, and templates 👇 https://lnkd.in/easzZpCD ♻️ Repost to help more product teams get closer to users 💙 Like if you’re already bringing UX research into your work 🛎️ Follow Matvey Bryksin for more practical tips 💬 What’s your main UX research method right now? Drop it in the comments!
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Confused about which UX research method to use? You’re not bad at UX You’re just asking the wrong question Every UX research method answers one thing: 👉 What’s the problem? 👉 Which solution works? Miss this, and research turns into noise The simple framework Think in 2 axes: Why vs What Problem vs Solution That’s it Everything fits here 👇 Qualitative × Problem Understand behavior and pain points Methods: User interviews, field studies → Best for uncovering why Qualitative × Solution Validate ideas early Methods: Concept testing, prototypes → Best before you build too much Quantitative × Problem Find patterns at scale Methods: Surveys, analytics → Best for prioritization Quantitative × Solution Measure performance Methods: A/B tests, usability benchmarks → Best for optimization Most UX failures happen when teams jump to solutions too early 👉 Match the method to the question. Good UX isn’t guesswork. It’s clarity, backed by intent. 📌Save this for your next research decision
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Ever looked at a UX survey and thought: “Okay… but what’s really going on here?” Same. I’ve been digging into how factor analysis can turn messy survey responses into meaningful insights. Not just to clean up the data - but to actually uncover the deeper psychological patterns underneath the numbers. Instead of just asking “Is this usable?”, we can ask: What makes it feel usable? Which moments in the experience build trust? Are we measuring the same idea in slightly different ways? These are the kinds of questions that factor analysis helps answer - by identifying latent constructs like satisfaction, ease, or emotional clarity that sit beneath the surface of our metrics. You don’t need hundreds of responses or a big-budget team to get started. With the right methods, even small UX teams can design sharper surveys and uncover deeper insights. EFA (exploratory factor analysis) helps uncover patterns you didn’t know to look for - great for new or evolving research. CFA (confirmatory factor analysis) lets you test whether your idea of a UX concept (say, trust or usability) holds up in the real data. And SEM (structural equation modeling) maps how those factors connect - like how ease of use builds trust, which in turn drives satisfaction and intent to return. What makes this even more accessible now are modern techniques like Bayesian CFA (ideal when you’re working with small datasets or want to include expert assumptions), non-linear modeling (to better capture how people actually behave), and robust estimation (to keep results stable even when the data’s messy or skewed). These methods aren’t just for academics - they’re practical, powerful tools that help UX teams design better experiences, grounded in real data.
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User research is great, but what if you do not have the time or budget for it........ In an ideal world, you would test and validate every design decision. But, that is not always the reality. Sometimes you do not have the time, access, or budget to run full research studies. So how do you bridge the gap between guessing and making informed decisions? These are some of my favorites: 1️⃣ Analyze drop-off points: Where users abandon a flow tells you a lot. Are they getting stuck on an input field? Hesitating at the payment step? Running into bugs? These patterns reveal key problem areas. 2️⃣ Identify high-friction areas: Where users spend the most time can be good or bad. If a simple action is taking too long, that might signal confusion or inefficiency in the flow. 3️⃣ Watch real user behavior: Tools like Hotjar | by Contentsquare or PostHog let you record user sessions and see how people actually interact with your product. This exposes where users struggle in real time. 4️⃣ Talk to customer support: They hear customer frustrations daily. What are the most common complaints? What issues keep coming up? This feedback is gold for improving UX. 5️⃣ Leverage account managers: They are constantly talking to customers and solving their pain points, often without looping in the product team. Ask them what they are hearing. They will gladly share everything. 6️⃣ Use survey data: A simple Google Forms, Typeform, or Tally survey can collect direct feedback on user experience and pain points. 6️⃣ Reference industry leaders: Look at existing apps or products with similar features to what you are designing. Use them as inspiration to simplify your design decisions. Many foundational patterns have already been solved, there is no need to reinvent the wheel. I have used all of these methods throughout my career, but the trick is knowing when to use each one and when to push for proper user research. This comes with time. That said, not every feature or flow needs research. Some areas of a product are so well understood that testing does not add much value. What unconventional methods have you used to gather user feedback outside of traditional testing? _______ 👋🏻 I’m Wyatt—designer turned founder, building in public & sharing what I learn. Follow for more content like this!
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🔍 User Testing: Turning Insights into Innovation 💡 🔍 Introduction: User testing is the cornerstone of great design, providing real-world insights that help refine and improve products. It’s the process where assumptions meet reality, allowing designers to understand how users interact with their creations and where adjustments are needed. 📈 Case Study: The Power of User Feedback: Take the example of a popular mobile app that struggled with low user retention. After conducting thorough user testing, the design team discovered that the navigation was confusing for new users. By simplifying the user flow and making key features more accessible, they saw a dramatic increase in engagement and retention. This transformation highlights the impact that user testing can have on a product's success. 🔬 Methods of User Testing: There are several effective methods for gathering user feedback: A/B Testing: Compare two versions of a design to see which performs better. Usability Studies: Observe users as they interact with your product to identify pain points and areas for improvement. Surveys and Interviews: Collect direct feedback from users about their experiences and preferences. Remote Testing: Leverage online tools to gather feedback from a diverse user base, no matter where they are. ⚠️ Common Pitfalls and How to Avoid Them: One common mistake in user testing is not testing with a diverse group of users. Ensure you have a varied testing pool to get a holistic view of your product’s performance. Another pitfall is ignoring qualitative feedback in favor of quantitative data. Both types of feedback are crucial in understanding the full picture of user experience. 🔍 Conclusion: User testing isn’t just a step in the design process—it’s the heartbeat that keeps your product alive and thriving. By incorporating user feedback early and often, you can create designs that truly meet user needs and expectations. Don’t skip this critical process; it’s key to turning insights into innovative, user-friendly designs. Ready to take your design to the next level? Start prioritizing user testing today! #UserTesting #UXDesign #Innovation #UserExperience #DesignThinking
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Your UX research is lying to you. And no, I'm not talking about small data inconsistencies. I've seen founders blow $100K+ on product features their users "desperately wanted" only to face 0% adoption. Most research methods are fundamentally flawed because humans are terrible at predicting their own behavior. Here's the TRUTH framework I've used to get accurate user insights: T - Test with money, not words • Never ask "would you use this?" • Instead: "Here's a pre-order link for $50" • Watch what they do, not what they say R - Real environment observations • Stop doing sterile lab tests • Start shadowing users in their natural habitat • Record their frustrations, not their feedback U - Unscripted conversations • Ditch your rigid question list • Let users go off on tangents • Their random rants reveal gold T - Track behavior logs • Implement analytics BEFORE research • Compare what users say vs. what they do • Look for patterns, not preferences H - Hidden pain mining • Users can't tell you their problems • But they'll show you through workarounds • Document their "hacks" - that's where innovation lives STOP: • Running bias-filled focus groups • Asking leading questions • Taking feedback at face value • Rushing to build based on opinions START: • Following the TRUTH framework • Measuring actions over words • Building only what users prove they need PS: Remember, Henry Ford said if he asked people what they wanted, they would have said "faster horses." Don't ask what they want. Watch what they do. Follow me, John Balboa. I swear I'm friendly and I won't detach your components.
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Strong signals bring user needs into focus. Over the years, I’ve worked with many teams that create user personas, giving them names like “Cindy” and saying things like “She needs to find this feature” to guide their design decisions. That’s a good start. But user needs are more complex than a few traits or surface-level goals. They include emotions, behaviors, and deeper motivations that aren’t always visible. That’s why we’re building Glare, our open framework for data-informed design. We've learned a lot using Helio. It helps teams create clear, measurable signals around user needs. UX metrics help turn user needs into real data: → What users think → What users do → What users feel → What users say When you define the right audience traits and pick the helpful research methods, you can turn vague assumptions into specific, actionable signals. Let’s take a common persona example: Your team says, “Cindy can’t find the new dashboard feature.” Instead of stopping there, create signals using UX metrics to define usefulness better: → Attitudinal Metrics (how Cindy feels) Usefulness ↳ 42% of users say the dashboard doesn’t help them complete their tasks Sentiment ↳ Users overwhelmingly selected: Confused, Frustrated, Overwhelmed Only 12% chose Clear or Confident Post-Task Satisfaction ↳ 52% of people are satisfied after completing key actions → Behavioral Metrics (what Cindy does) Frequency ↳ Only 18% of users revisit the dashboard weekly, down from 35% last quarter → Performance Metrics (how the product supports Cindy) Helpfulness ↳ 60% of users say they needed help materials to complete a task, suggesting the experience is unclear With UX data like this, your team can stop guessing and start aligning around the real needs of users. UX metrics turn assumptions into signals… leading to better product decisions. Reach out to me if you want to learn how to incorporate UX metrics into your team workflows. #productdesign #productdiscovery #userresearch #uxresearch