A pet care app team was convinced they'd cracked the code on user engagement. They'd spent months asking dog owners "Would you like our app to send you daily health tips for your pet?" Nearly everyone said yes. Brilliant, right? They built the feature, launched it, and watched their uninstall rates skyrocket. Turns out, people hate being bombarded with notifications they thought sounded nice in theory. The problem wasn't their app—it was their research questions.
User research can make or break your mobile app, but asking the wrong questions is worse than doing no research at all. I've seen teams waste months building features based on misleading feedback because they didn't know how to ask proper questions. The thing is, most people want to be helpful during research sessions; they'll tell you what they think you want to hear rather than what they actually think.
Bad research questions don't just waste time and money—they actively mislead you into building the wrong product for the wrong reasons
Getting user research right isn't about asking more questions; its about asking the right ones. Leading questions, hypothetical scenarios, and jargon-filled queries can completely derail your research efforts. Even experienced teams fall into these traps because the questions seem reasonable on the surface.
This guide covers the specific types of questions that will sabotage your research efforts. We'll look at real examples of questions that seem helpful but actually bias your results, and show you how to spot these problems before they damage your app development process. Because honestly? Your users deserve better than an app built on faulty assumptions.
Leading Questions That Bias Your Results
Right, let's talk about one of the biggest mistakes I see teams make during user research—asking leading questions. I mean, it's so easy to do without realising it, but honestly, it can completely wreck your research results.
A leading question is basically one that pushes users towards a specific answer. Instead of asking "How did you find the checkout process?" you might accidentally ask "Wasn't the checkout process really smooth and easy?" See the difference? The second question is practically begging for a positive response, even if the user actually struggled with it.
The Subtle Ways We Lead Users Astray
The thing is, leading questions aren't always obvious. Sometimes they're sneaky little devils that slip into our research without us noticing. Questions like "What did you love about this feature?" assume the user loved something in the first place. Maybe they didn't love anything about it—maybe they found it confusing or unnecessary.
I've seen research sessions where teams asked things like "How much faster did this new design feel?" when they should have been asking "How did the speed of this new design compare to what you're used to?" The first question assumes it felt faster; the second actually lets the user tell you what they experienced.
Why This Matters for Your App
When you lead users towards certain answers, you're not getting honest feedback—you're getting confirmation of what you want to hear. That means you might launch an app feature thinking its brilliant when users actually find it frustrating. The result? Poor user retention, negative reviews, and wasted development time fixing problems you could have caught early on.
Always let users form their own opinions and express them naturally. Your job is to listen, not to guide them towards the answers you're hoping for.
Open vs Closed Questions Getting It Wrong
Right, let's talk about one of the biggest mistakes I see teams make during user research—mixing up when to use open versus closed questions. It's a bit mad really how this simple distinction can completely change your results, but I've watched countless research sessions go sideways because of it.
Here's the thing: closed questions give you yes/no answers or force people to pick from a limited set of options. "Do you like this feature?" or "Would you use this daily, weekly, or monthly?" These are fine when you need specific data points, but they're terrible when you're trying to understand the why behind user behaviour.
Open questions, on the other hand, let people tell their story. "How do you currently handle this task?" or "What's frustrating about your existing workflow?" These give you the gold—the insights that actually help you build better apps.
The mistake? Using closed questions when you should be exploring. I've seen researchers ask "Is the navigation confusing?" instead of "How did you find moving around the app?" The first question basically puts words in the user's mouth and limits their response to a simple yes or no. The second one? That's where the real insights live.
Start your research sessions with broad, open questions to understand the full context, then gradually narrow down to specific closed questions for confirmation.
When to Use Each Type
- Open questions: Early discovery, understanding problems, exploring workflows
- Closed questions: Validating specific features, gathering quantitative data, final confirmation
- Mixed approach: Follow up closed questions with "Can you tell me more about that?"
The biggest trap is using closed questions because they feel safer and easier to analyse. But honestly, if you're not getting messy, complicated answers that make you think differently about your product, you're probably asking the wrong questions.
Hypothetical Scenarios That Don't Help
I've lost count of how many times I've heard someone ask users: "If we added a feature that could read your mind, would you use it?" Okay, maybe not quite that extreme, but you get the idea. These what-if questions might seem clever, but they're actually one of the worst ways to understand what your users really need from your app.
The problem with hypothetical questions is that people are terrible at predicting their own behaviour. They'll tell you they'd absolutely use a feature that tracks their daily water intake, but when you actually build it? Crickets. I've seen this happen so many times—clients get excited about features based on hypothetical responses, then wonder why nobody uses them once the app launches.
Here's the thing though; hypothetical scenarios pull people away from their real experiences and into fantasy land. Instead of asking "What would you do if our app could automatically sync with your calendar?" try asking "Tell me about the last time you struggled to keep track of your appointments." See the difference? One gets you real insight, the other gets you wishful thinking.
Focus on Past Behaviour Instead
Past behaviour is the best predictor of future behaviour. When you ask someone "What apps did you delete from your phone last week and why?" you're getting genuine data about their decision-making process. But when you ask "Would you delete an app if it sent too many notifications?" you're getting a guess at best.
The most successful apps I've worked on were built using research that focused on actual user struggles, not imagined scenarios. Real problems lead to real solutions—and that's what keeps users coming back.
Questions About the Future That Mislead
Here's something that catches out loads of researchers—asking people to predict what they'll do in the future. It sounds logical, right? You want to know if users will adopt your feature, so you ask them directly. But honestly, people are terrible at predicting their own behaviour.
I've seen countless user research sessions where teams ask questions like "Would you use this feature regularly?" or "How often would you open this app?" The answers sound promising in the room, but when the app launches, the usage patterns are completely different. Users genuinely believe they'll behave one way, but their actual behaviour tells a different story entirely.
The problem is that future predictions are based on current emotions and ideal scenarios. When someone's sitting in a research session, they're focused and engaged; they can see the value in your app clearly. But in real life? They're distracted, busy, and have dozens of other apps competing for their attention. That changes everything.
What people say they'll do and what they actually do are often two completely different things—especially when you're asking them to imagine future scenarios they haven't experienced yet
Instead of asking about future behaviour, focus on current pain points and past experiences. Ask questions like "Tell me about the last time you tried to solve this problem" or "What's frustrating about your current process?" These give you real insights based on actual experiences, not hopeful predictions. You can then design solutions that address genuine problems rather than hypothetical ones. Trust me, your app's success will depend much more on solving real problems than meeting imagined future needs.
Multiple Questions Packed Into One
I see this mistake all the time in user research sessions—and honestly, it drives me a bit mad because its such an easy trap to fall into. You're sitting there with your user, you've got limited time, and suddenly you think "I'll just squeeze in a few related questions at once." Bad idea.
Here's what typically happens: you ask something like "What do you think about the checkout process, and would you prefer PayPal or card payments, and also how important is express delivery to you?" Your poor user sits there looking confused, tries to answer the first bit, forgets the middle part, and gives you a half-answer that's basically useless.
The problem isn't just that people get overwhelmed—though they absolutely do. Its that their brains naturally focus on whichever part of your mega-question feels easiest to answer. So you end up with responses that don't actually address what you really needed to know.
I learned this the hard way during a project for an e-commerce client. We were testing their mobile checkout flow and I kept bundling questions together because we were running behind schedule. The feedback we got was all over the place—users would answer part A, ignore part B, and sometimes invent part C that we hadn't even asked about.
How to Fix Multi-Question Mistakes
Break everything down into single, focused questions. Ask one thing, get your answer, then move on to the next point. Yes, it takes a bit longer, but you'll get much cleaner data.
- Ask about the checkout process first
- Wait for the complete response
- Then ask about payment preferences
- Finally, discuss delivery options
- Keep each question simple and specific
Your users will thank you for it, and your research data will actually be worth something. Trust me on this one—I've seen too many research sessions ruined by question overload.
Jargon and Technical Language Mistakes
Right, let's talk about one of the biggest mistakes I see when conducting user research—and honestly, it's something that trips up even experienced teams. Using jargon and technical language during user interviews is like speaking a foreign language to your participants. You might as well be asking them questions in Klingon!
I've sat through countless research sessions where the interviewer starts throwing around terms like "conversion funnel," "user journey mapping," or "API integration" and then wonders why participants look confused or give vague answers. The thing is, your users don't live in your world of product management terminology—they're just trying to get stuff done with your app.
Common Technical Terms to Avoid
- User interface (say "screen" or "what you see" instead)
- Navigation (try "moving around the app" or "finding things")
- Functionality (use "what it does" or "how it works")
- User experience (just say "how it feels to use")
- Touchpoints (say "ways you interact with us")
- Workflow (try "the steps you take" instead)
But here's the thing—it's not just about avoiding obvious tech speak. Sometimes we use words that seem normal to us but are still confusing. Words like "optimise," "integrate," or "leverage" might sound perfectly clear to you, but they can make participants feel like they need to give "smart" answers rather than honest ones.
Always do a quick jargon check before your interviews. Read your questions out loud and circle any word that wouldn't appear in a casual conversation with a friend. If you wouldn't use it down the pub, don't use it in research.
The goal is to make participants feel comfortable and understood. When you speak their language, you get their real thoughts—not what they think you want to hear.
Personal Opinion Questions to Avoid
Here's where things get a bit tricky—and honestly, it's something I see developers mess up all the time. When you're conducting user research, asking people for their personal opinions might seem like the obvious thing to do. I mean, you want to know what they think, right? But here's the thing: personal opinions in user research are about as useful as a chocolate teapot.
The problem with opinion-based questions is they tell you what people think they want, not what they actually need or how they'll behave. I've lost count of how many times clients have come to me saying "but our users told us they wanted this feature!" only to launch it and watch tumbleweeds roll through their usage analytics.
Questions That Sound Helpful But Aren't
These are the opinion traps that'll lead you down the wrong path every time:
- "Do you like this design?"
- "What's your favourite colour for buttons?"
- "Would you recommend this app to friends?"
- "What do you think about having notifications?"
- "Do you prefer this layout or that one?"
- "How would you rate the user interface?"
Instead of asking what people think, focus on what they do. Ask them to complete specific tasks. Watch where they struggle. Ask about their current habits and behaviours—that's where the real gold is hidden.
Replace "Do you like this checkout process?" with "Show me how you'd buy this item." The difference in insights you'll get is genuinely mind-blowing. Actions speak louder than opinions, especially when you're trying to build something people will actually use rather than something they say they'd use.
After years of watching brilliant app ideas crash and burn because of poor user research, I can tell you that asking the wrong questions isn't just a minor setback—it's often the difference between building something people actually want and building something that collects digital dust.
The questions we've covered might seem obvious when you read them laid out like this, but honestly? I see teams make these mistakes all the time. Even experienced developers fall into the trap of leading their users toward the answers they want to hear, or drowning them in technical jargon that completely derails the conversation.
Here's what I've learned from hundreds of user research sessions: your users are trying to help you build something great, but only if you let them. Every time you ask a leading question or pack three questions into one, you're basically putting words in their mouth. And that's not research—that's just expensive confirmation bias.
The mobile app world is competitive enough without handicapping yourself with bad research. Users have thousands of apps at their fingertips; they don't need another one that sort of solves their problem. They want apps that genuinely understand their needs, and the only way to build those is by asking the right questions in the right way.
So next time you're planning user interviews or testing sessions, remember this: your job isn't to validate your assumptions. Its to challenge them. Ask open-ended questions, listen more than you talk, and be prepared for your users to surprise you. Because when they do, that's when you know you're onto something good.
