Conducting User Experience Interviews

"Talk to customers" is classic startup advice. But not enough folks teach you how to talk to users in a way that gets you actual insights. Since launching Decagon and raising $100M over 3 rounds, we’ve learned a lot, especially about GTM. Here's how we've adapted our customer conversations to go beyond surface-level excitement and uncover real signals of value. We benchmark around dollars when discussing product features. Why? Because it’s easy to run a customer interview where the customer seems thrilled about a new idea we have. But excitement alone doesn’t tell you if a piece of feedback is truly valuable. The only way to find out is to ask the hard questions: → Is this something your team would invest in right now? → How much would you pay for it? → What’s the ROI you’d expect? Questions like these don’t allow for generic answers—they'll give you real clarity into a customer's willingness to pay. For example: say you float a product idea past a potential user. They're stoked by it. Then you ask how much they'd pay for said product—and the answer is $50 per person for a 3-person team. Is that worth building? It might be, depending on the outcome you're shooting for. But if your goal is to build an enterprise-grade product, that buying intent (or lack thereof) isn't going to cut it. If you'd stopped the interview at the surface-level excitement, you might have sent yourself on a journey building a product that isn't viable. By assessing true willingness to pay you can prioritize building what users find valuable versus what might sound good in theory. Get to the dollars as quickly as you can. It’s an approach that has helped us align our roadmap with what customers truly need and ensure we’re building a product that has a measurable impact.

Last week, I coached a product team through a user interview debrief. They were excited! Users had shown enthusiasm for a new feature! 🎉 But when I asked, “What problem does this solve for them?” the room went quiet. 🫣 This happens more often than we’d like to admit. 🧠 The Trap: Mistaking Enthusiasm for Validation When users say, “That sounds great!” we often interpret it as validation. But here's the catch: - Users want to be polite. - They might not fully understand their own needs. - As product teams, we may hear what we want. This is why relying solely on user enthusiasm can lead us astray. 🔍 The Solution: Semi-Structured Interviews We need to dig deeper to understand our users truly. Semi-structured interviews strike the right balance between guidance and flexibility. Key practices include: - Start with hypotheses: Identify what you believe to be true. - Ask open-ended questions: Encourage users to share experiences, not just opinions. - Listen actively: Pay attention to what’s said—and what’s not. - Probe for underlying needs: Seek to understand the 'why' behind their behaviours. This approach helps uncover genuine insights, leading to solutions that truly resonate. 🌟 Imagine the Impact By adopting this method: - Teams build products that solve real problems. - User satisfaction increases. - Resources are invested wisely, reducing wasted effort. It's not just about building features—it's about delivering value. 🦾 Take Action Next time you're planning user interviews: - Prepare a set of hypotheses. - Design questions that explore user experiences. - Remain open to unexpected insights. Remember, the goal is to understand your users, not just confirm your assumptions deeply.

𝟵𝟬% 𝗼𝗳 𝘂𝘀𝗲𝗿 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀 𝗳𝗮𝗶𝗹 𝗯𝗲𝗳𝗼𝗿𝗲 𝘁𝗵𝗲𝘆 𝗲𝘃𝗲𝗻 𝗯𝗲𝗴𝗶𝗻. 🧠 Why? Because most PMs ask surface-level questions and stop at obvious answers. Great user interviews don’t just ask questions. They uncover motivations, break assumptions, and reveal the “why” behind the “what.” 𝗔𝗳𝘁𝗲𝗿 𝗿𝘂𝗻𝗻𝗶𝗻𝗴 𝟮𝟬𝟬+ 𝗶𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄𝘀, 𝗵𝗲𝗿𝗲’𝘀 𝘄𝗵𝗮𝘁 𝗜’𝘃𝗲 𝗹𝗲𝗮𝗿𝗻𝗲𝗱: 🔹Asking the right question is 10% of the job. 🔹Knowing how and when to ask it, that’s what leads to real insight. 🔹And insight is what separates good product decisions from guesswork. 𝗜’𝘃𝗲 𝗱𝗶𝘀𝘁𝗶𝗹𝗹𝗲𝗱 𝗲𝘃𝗲𝗿𝘆𝘁𝗵𝗶𝗻𝗴 𝗶𝗻𝘁𝗼 𝗮 𝗨𝘀𝗲𝗿 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗣𝗹𝗮𝘆𝗯𝗼𝗼𝗸 𝗳𝗼𝗿 𝗣𝗠𝘀 𝘁𝗵𝗮𝘁 𝗰𝗼𝘃𝗲𝗿𝘀: ✔️ Proven question structures ✔️ Conversation flow frameworks ✔️ Bias traps to avoid ✔️ Templates, tools, and real examples This isn’t theory, It’s what I use in real product discovery. 📥 𝗪𝗮𝗻𝘁 𝗮𝗰𝗰𝗲𝘀𝘀? Comment “𝗨𝘀𝗲𝗿” and I’ll share it with you. This guide is for PMs who want to move from taking feedback to shaping strategy.

Let's face it: most user interviews are a waste of time and resources. Teams conduct hours of interviews yet still build features nobody uses. Stakeholders sit through research readouts but continue to make decisions based on their gut instincts. Researchers themselves often struggle to extract actionable insights from their conversation transcripts. Here's why traditional user interviews so often fail to deliver value: 1. They're built on a faulty premise The conventional interview assumes users can accurately report their own behaviors, preferences, and needs. People are notoriously bad at understanding their own decision-making processes and predicting their future actions. 2. They collect opinions, not evidence "What do you think about this feature?" "Would you use this?" "How important is this to you?" These standard interview questions generate opinions, not evidence. Opinions (even from your target users) are not reliable predictors of actual behavior. 3. They're plagued by cognitive biases From social desirability bias to overweighting recent experiences to confirmation bias, interviews are a minefield of cognitive distortions. 4. They're often conducted too late Many teams turn to user interviews after the core product decisions have already been made. They become performative exercises to validate existing plans rather than tools for genuine discovery. 5. They're frequently disconnected from business metrics Even when interviews yield interesting insights, they often fail to connect directly to the metrics that drive business decisions, making it easy for stakeholders to dismiss the findings. 👉 Here's how to transform them from opinion-collection exercises into powerful insight generators: 1. Focus on behaviors, not preferences Instead of asking what users want, focus on what they actually do. Have users demonstrate their current workflows, complete tasks while thinking aloud, and walk through their existing solutions. 2. Use concrete artifacts and scenarios Abstract questions yield abstract answers. Ground your interviews in specific artifacts. Have users react to tangible options rather than imagining hypothetical features. 3. Triangulate across methods Pair qualitative insights with behavioral data, & other sources of evidence. When you find contradictions, dig deeper to understand why users' stated preferences don't match their actual behaviors. 4. Apply framework-based synthesis Move beyond simply highlighting interesting quotes. Apply structured frameworks to your analysis. 5. Directly connect findings to decisions For each research insight, explicitly identify what product decisions it should influence and how success will be measured. This makes it much harder for stakeholders to ignore your recommendations. What's your experience with user interviews? Have you found ways to make them more effective? Or have you discovered other methods that deliver deeper user insights?

Most product decisions are made long before a metric moves. They are shaped in conversations with users, moments of confusion we observe, things people hesitate to say out loud, and patterns that do not neatly fit into dashboards. Qualitative research today is not limited to interviews followed by a few highlighted quotes. There are rigorous, well-established approaches that make interpretation transparent, repeatable, and defensible. Methods like Framework Analysis help teams organize complex interview data in a way that allows real comparison across users and segments. Reflexive Thematic Analysis goes deeper, showing how meaning, emotion, and framing are actively constructed rather than passively extracted. When products behave differently across users, or when success and failure coexist in the same launch, methods like Qualitative Comparative Analysis explain why. Instead of asking what works on average, they reveal which combinations of conditions actually lead to outcomes. When teams need to understand causality rather than correlation, Process Tracing and Realist Evaluation map the mechanisms that connect design decisions to user behavior. Other methods prioritize depth and context. Interpretative Phenomenological Analysis preserves lived experience without flattening it. Video Reflexive Ethnography exposes invisible routines and expert behavior. Multimodal Discourse Analysis treats interfaces as systems of meaning, not just screens. Digital ethnography captures how culture forms and evolves online. Computational Grounded Theory allows qualitative insight to scale while keeping humans firmly in the loop. Qualitative UX is not about intuition versus data. It is about disciplined interpretation. When used thoughtfully, it becomes one of the most powerful tools we have for understanding why products succeed, fail, or surprise us. I wrote a detailed blog that dives into a practical framework for rigorous qualitative UX and market research. You can read more at PUX Lab: https://lnkd.in/gwBJS-UB

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.

I’ve seen a lot of enthusiastic designers and product folks jump into UX interviews with confidence just because they’re good at talking to people. The session feels relaxed, the user seems open, and everyone walks away feeling like they learned something real. The problem is that conversations are not data. Users try to be polite, helpful, agreeable, and socially “reasonable.” Without proper training, a UX interview collects stories that sound insightful but have nothing to do with real behavior. You end up designing for what users said politely, not what they actually do. What makes this funny is that in psychology, interviews are treated as one of the most complex research methods. Students spend semesters learning how to interview. They get observed, corrected, and even graded on how they phrase questions, how they hold their face, and whether they accidentally lead participants. Interviewing is a professional skill you learn and practice, not something you do because you’re friendly or curious. The best interviews don’t feel like conversations at all. The interviewer steps back and lets participants think slowly, sometimes awkwardly. A quiet researcher who listens, waits, and asks “What happened next?” learns a lot more than someone who jumps in to be helpful. Silence reveals truth. Polite conversation reveals performance. A semi-structured guide helps a lot. It keeps things focused without forcing yes/no answers. And asking about specific events beats asking for opinions every time. “Tell me about the last time you dealt with a notification” gives you real behavior. “Do you like notifications?” just gives you nice words. Rigor in UX doesn’t have to slow anything down. It just requires discipline. Document the guide. Write down your assumptions. Pair interviews with observation so you can see if words match actions. These little habits protect the findings from your own influence. And please, the “five users is enough” idea only applies to fictional usability testing, it does not work for uncovering real motivations, values, or decision patterns. You stop interviewing when people stop teaching you something new, not when you hit a magic number. In the end, UX interviews look simple, and that’s why they’re tricky. Anyone can ask questions. Very few people can stay neutral enough to uncover the truth behind the answer. When we treat interviews as investigations rather than conversations, our products get better, users get treated more accurately, and teams stop guessing. That’s the whole point of research: not to gather quotes but to uncover reality.

Atomic UX Research Cheatsheet Turn user data into product decisions that actually drive results Where UX research often breaks down 👇 Teams collect data… But fail to turn it into clear actions That’s where impact is lost Step 1: Experiments Start with the right inputs • User interviews & usability tests • Surveys, reviews, feedback loops • Analytics & behavioral data Capture real user signals, not assumptions Step 2: Facts Document what actually happened • Quotes → What users say • Observations → What users do • Metrics → What data proves  Focus on objective evidence only Step 3: Insight Translate data into understanding • Context → Where the issue happens • Cause → Why users struggle • Effect → What it leads to  Turn information into clear problem clarity Step 4: Recommendation Convert insight into action • Action → What to improve • Audience → Who it impacts • Outcome → Expected result • Measurement → How to track success Make every insight decision-ready Data alone doesn’t improve UX Interpretation does If insights aren’t actionable, They're just noise Experiment → Fact → Insight → Action This is how strong teams: • Reduce friction • Improve usability • Increase conversions Build products users actually understand. 🔄 Repost to share this with your team and network! For next, Follow Subash Chandra for UX strategies that drive growth 

In the first company we founded (and exited), we talked to thousands of users. Here at Pivot (YC S22), we just crossed our first 100. We are obsessed about speaking to users. But how do we talk to users effectively? Here are the top 4 tactics that have helped us gain valuable insights: 1/ Spend the first 5 minutes just talking about their lives. Don’t approach user conversations like a sales pitch. I know that it’s tempting to push the call towards your goals, or perhaps you are worried about wasting the other person’s time. But resist that urge! Instead, focus on genuinely getting to know them as if you’re making a new friend. First, this provides valuable context about who they are and what matters to them, helping you better make sense of their insights. Second, this deeper connection fosters genuine care for each user, which is key to building a successful company. 2/ Look for Lightbulb Moments. These rare moments provide unique insights that bring us closer to achieving Product Market Fit. For instance, Brian Chesky went down to Airbnb hosts just to realise that they needed help with photography, and Brian Armstrong phoned up all early Coinbase users just to learn from one guy the importance of a "Buy Bitcoin" button. By staying patient and attentive, a single comment from a user can spark a breakthrough idea. Even if 100 conversations don't yield Lightbulb Moments, the next one just might. It is our job to look out for them. 3/ “Huh! That’s interesting. Tell me more.” This is the go-to statement whenever a user shares something unexpected or unusual. Ask it, then pause and let them respond. While it may catch users off guard initially, it prompts them to reflect on their feelings, often resulting in a more detailed and nuanced explanation. This could just lead to a valuable Lightbulb Moment (as mentioned earlier). 4/ 5 consecutive “whys” when seeking an explanation. The 1st “why” might uncover something interesting, but it’s not until you get to the 5th “why” that you start to unearth their deepest motivations and underlying pain points. These are often things that the user themselves may not even be aware of. This technique helps us move past surface-level feedback to gain deeper insights, guiding our product development and UX from first principles. Ultimately, this helps us create something users truly want. The best founders continue to talk directly to their users even after they've reached $100M+ in ARR. It's crucial that we start making this our superpower today. I’d love to learn about other tactics that have worked for you as well, feel free to drop them in the comments below 👇

Stop asking users if they'd use your product. Most will lie - not on purpose, but to be polite. So many user interviews fail because we ask surface-level questions. Because we confuse feedback with validation. Because we don’t know what we’re listening for. Here’s a simplified approach — one I wish I followed way earlier: 1. Start with moments, not features. Instead of “Would you use X?”, ask “Tell me about the last time you faced [problem].” You’re not hunting for praise — you’re looking for pain. 2. Stay uncomfortable. If a response feels vague, ask why — then ask why again. Dig until you hit the emotion behind the behavior. 3. Review, don’t rely on memory. Our brains are biased. Record your interviews, highlight key moments, and tag patterns. (This is why tools like Inciteful App are extremely valuable — they help you connect dots you didn’t even know were there. Kudos to Brittany Canty!) Remember the goal isn’t to collect quotes. It’s to understand context. Because every “bad” feature started with a misunderstood problem.