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The 5 Sneaky Biases Sabotaging Your Customer Research (And How to Fix Them)

4 min read

You’ve probably experienced this: your product seemed fine at first, but over time, you notice it’s not hitting the mark—customer churn increases, and growth slows. You’re left wondering, I did the research, but where did I go wrong?


The challenge? Biases—silent, sneaky ones—have been creeping into your customer insights all along, distorting your research. And if you don’t catch them, you’ll end up building products based on flawed data.


That’s a dangerous game. Wasting time and resources on a product that misses the mark can cost you more than just money. It can set your team back and give competitors an edge.


But don’t worry, there’s a way through this.


In this blog, we’re diving into five subtle biases that sneak into your customer research, warp your results, and cost you time and money.


  • Confirmation Bias: Only hearing what you want to hear and ignoring contradicting feedback.

  • Framing Effect: Poorly worded questions that nudge customers toward a particular answer.

  • Anchoring Bias: Letting first impressions or numbers mislead your decision-making.

  • Social Desirability Bias: Customers sugarcoating feedback to avoid being too critical.

  • Availability Bias: prioritising the most frequent feedback, even if it’s not the most important.


I’ll show you how to spot them, fix them, and get your research back on track.


Let’s get into it and make sure your next round of customer insights is spot on.



1. Confirmation Bias: Only Seeing What You Want


Confirmation bias is when you only hear what fits your beliefs and ignore anything that doesn’t. It’s like wearing blinders—you miss the full picture.


For example, asking, “How has Feature X improved your workflow?” assumes the feature helped, which might not be true.


The Google Glasses' team made this mistake. They were focusing on early adopters' feedback, ignoring mainstream users who found the glasses intrusive, awkward, and privacy-invasive.


How to fix it: Use open-ended questions like:

  • “What’s been your experience with X?”

  • “Have you faced any challenges with this feature?”


Always question your assumptions—don’t just look for things that confirm what you already believe.



2. Framing Effect: Asking Leading Questions


The framing effect happens when the way you ask something influences the answer. For example, asking, “Don’t you think our new interface is user-friendly?” pushes the customer to say yes.


Look at Microsoft Zune. They assumed people would love its features without asking the right, unbiased questions. People didn’t care, and the product failed.


How to fix it: Get rid of leading questions. Instead, ask:

  • “What are your thoughts on the new interface?”

  • “Can you walk me through your experience with this feature?”


This way, you’ll get honest answers, not what people think you want to hear.



3. Anchoring Bias: First Impressions Stick Too Much


Anchoring bias happens when people cling to the first info they hear. If you say, “Most customers saw a 20% increase in efficiency—how about you?” they’ll probably focus on that 20% even if it’s not true for them.


Segway made this mistake. They assumed Segways would replace walking, without thinking about real issues like rules or if people even wanted to stop walking. It didn’t work out.


How to fix it: Keep it neutral. Don’t give numbers before asking for feedback. Instead, ask:

  • “How has the tool impacted your work?”

  • “What benefits, if any, have you noticed?”


This keeps the answers honest and natural.



4. Social Desirability Bias: People Want To Be Nice


Social desirability bias is when customers tell you what they think will make you happy. They want to be nice, so they sugarcoat their feedback.


Think about Amazon’s Fire Phone. People probably didn’t want to criticize a big company like Amazon, so they downplayed their dislikes. But that backfired—the product failed.


How to fix it: Make it clear you want the truth. Say something like:

  • “It’s important for us to hear the hard truths so we can improve.”

  • “We’ve made mistakes before, so please point out any flaws.”


This shows customers you value honesty, not just compliments.



5. Availability Bias: Giving Too Much Weight To What You Hear Most


Availability bias is when you focus too much on what you hear often, instead of considering all the feedback. For example, if several customers mention a small issue, you might think it’s the biggest problem, even if bigger issues are being overlooked.


Remember Microsoft’s Clippy? It was designed based on feedback from tech enthusiasts, but regular users didn’t like it. The feedback didn’t represent everyone, and Clippy failed.


How to fix it: Gather a wide range of feedback and don’t just act on the loudest voices. Ask:

  • “What’s something you’d like to change?”

  • “What’s the most frustrating part of using this product?”


This helps you focus on what really matters to most users, not just the few who shout the loudest.



Here’s how to get started:


  • Look at your customer interview questions and take out any that suggest the answer (leading questions).

  • Ask open-ended, neutral questions, and create a safe space for honest feedback.

  • Let customers know you want the truth, not just nice words.

  • Make sure you review all feedback, not just the things you hear the most.


By doing this, your customer insights will be clearer, more useful, and real. That’s how you build a product people actually want!



As a customer insight consultant, I run a 4-week customer insight sprint where I handle outreach, conduct interviews, and keep these biases in check every step of the way. By focusing on unbiased, honest feedback, I’ve helped businesses avoid these traps and launch successful products that truly meet customer needs.


If you want clear, actionable insights that lead to stronger decisions and better products, I’ve got you covered. Feel free to drop me a question or book a call if you need your customer insights done in 4 weeks, so you can make bias-free, data-driven decisions!


Let’s fix your insights and get back to data you can trust!


Click here to book a call.

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