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?
Common Mistakes In User Experience Interviews
Explore top LinkedIn content from expert professionals.
Summary
Understanding common mistakes in user experience interviews can help professionals avoid pitfalls that undermine decision-making and lead to ineffective design choices. These errors often arise from biases, rushed processes, or a focus on opinions rather than actionable insights.
- Focus on behaviors: Instead of asking users about their preferences or opinions, observe their actions and interactions to gain a clearer picture of their actual needs.
- Ask follow-up questions: Avoid staying at the surface level by diving deeper into unexpected or interesting responses to uncover meaningful insights.
- Capture and share insights: Use structured tools to document findings and communicate them broadly across your team to ensure alignment and informed decisions.
-
-
With research teams shrinking from layoffs, PMs are now expected to do more with less. But without the right approach, PM-led session replays can lead to false insights. Here are the 4 costly mistakes to avoid for real progress: – 𝗖𝗼𝗺𝗺𝗼𝗻 𝗣𝗶𝘁𝗳𝗮𝗹𝗹𝘀 Even experienced teams can fall into these traps. Here’s how to steer clear of them. 𝗠𝗶𝘀𝘁𝗮𝗸𝗲 𝟭 - 𝗙𝗮𝗹𝗹𝗶𝗻𝗴 𝗶𝗻𝘁𝗼 𝘁𝗵𝗲 𝗖𝗼𝗻𝗳𝗶𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗕𝗶𝗮𝘀 𝗧𝗿𝗮𝗽 ➔ What it is Confirmation bias happens when we unknowingly seek out evidence that supports our assumptions. It’s easy to go into session replays with a pre-formed theory about what users will do. ➔ What happens Instead of observing objectively, we end up interpreting every click and pause as “proof” of our theory. ➔ How to fix it Watch sessions with other team members who bring fresh perspectives and uncover what’s really happening. 𝗠𝗶𝘀𝘁𝗮𝗸𝗲 𝟮 - 𝗧𝗵𝗲 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝗮𝗹 𝗦𝗶𝗴𝗻𝗶𝗳𝗶𝗰𝗮𝗻𝗰𝗲 𝗠𝘆𝘁𝗵 ➔ What it is The assumption that only large-scale patterns or trends are meaningful. The classic “But it’s just one user!” trap. ➔ What happens Valuable insights are overlooked simply because they come from one or two users instead of thousands. ➔ How to fix it Focus on depth, not numbers. A single user’s struggle can reveal a critical friction point. Treat each session as a deep dive into the user experience. 𝗠𝗶𝘀𝘁𝗮𝗸𝗲 𝟯 - 𝗧𝗵𝗲 𝗤𝘂𝗶𝗰𝗸-𝗙𝗶𝘅 𝗧𝗲𝗺𝗽𝘁𝗮𝘁𝗶𝗼𝗻 ➔ What it is Product teams are naturally drawn to solving problems, so when we see an issue in a session replay, we want to fix it right away. ➔ What happens By jumping to a solution too quickly, we might miss underlying patterns or broader issues that would have become clearer with a bit more patience. ➔ How to fix it Slow down and watch at least three more sessions before you act. This will give you a better sense of whether you require a more strategic fix. 𝗠𝗶𝘀𝘁𝗮𝗸𝗲 𝟰 - 𝗢𝘃𝗲𝗿𝗹𝗼𝗼𝗸𝗶𝗻𝗴 𝘁𝗵𝗲 𝗗𝗲𝘁𝗮𝗶𝗹𝘀 ➔ What it is Session replays are only as valuable as the data they capture. Small but essential interactions, like mouse movements, and scroll patterns can reveal a lot about user friction. ➔ What happens If these details aren’t captured, you’re left with an incomplete picture of the user’s journey, missing key friction points. ➔ How to fix it Double-check that your session replay tool is configured to capture all critical interactions. – 𝗧𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗠𝗮𝗻𝗮𝗴𝗲𝗺𝗲𝗻𝘁 The future of product management is about combining quantitative insights, qualitative depth (session replays - using tools like LogRocket), direct feedback (user research), and predictive foresight (AI). – If you want to stay ahead of the curve with advanced techniques and strategies for product management and career growth... Check out the newsletter.