Every founder’s playbook talks about the importance of customer interviews.
But let’s be honest, how many of us actually do them once we’re out of accelerator programs or past the first MVP launch?
Ask any founder of a less than 20-person company about customer interviews, and you’ll probably hear:
“We already talk to customers every day.”
Or
“We don’t have time for that kind of research. We just build and learn.”
It’s understandable. When you’re in the whirlwind of early growth, talking about customer interviews can sound like corporate overkill. But your customer pays you to build value, not features.
Every decision that ignores their voice is a step away from the value, and for a small company, that can cost survival.
The Small-Company Risk Multiplier
Working both with enterprises and being a founder of a startup myself, one thing I know for sure.
When you’re small, every mistake hits harder. One wrong feature or campaign can eat up months of work and drain your budget.
Small companies face amplified risks from missteps. A single misguided feature or campaign can consume significant resources, potentially jeopardizing funding opportunities or customer loyalty. Industry reports consistently find that 50% to 80% of software features are rarely or never used.
That wasted development effort is why customer interviews are not a “nice to have.” They are your insurance policy against existential mistakes.
The Belief of “Knowing Your Customer”
In a small, tight-knit team, it’s easy to believe you already know your customers. You’ve talked to them. You’ve built for them. You might even be one of them.
A classic example is a fitness app creator who, as an avid runner, prioritizes tracking features for marathons and endurance training, ignoring that most users are casual walkers seeking simple motivation tools.
This bias can cause the team to ignore data showing low engagement with advanced metrics, leading to features that gather dust while basic needs are not met. Like social sharing or quick workout suggestions, which Strava did well and built a strong community around.
Avoid Founder Bias and Break Out of the Echo Chamber
Avoiding your own biases is sometimes like navigating a maze you built yourself.
You’re always too close to the product, and every conversation starts by confirming what you already believe.
You build for the customer you think you have, not the one who’s actually paying, and end up repeating the same assumptions over and over.
But there are ways to break out of this cycle, and here is one that helps me.
- Implementing Structured Customer Interviews
Regular, systematic customer interviews are the most effective way to counteract founder bias. Go through this framework to make the most of every interview. - Leverage Data to Challenge Assumptions
Use quantitative data from your CRM, product analytics, or customer support tickets to identify patterns that contradict your assumptions. - Use Transparent and Traceable Tools
When using tools for interviews, especially AI platforms such as Prelaunch AI Interviewer, ensure they provide transparency, like raw transcripts and reasoning logs. - Diversify Internal Perspectives
Involve cross-functional teams or even bring external voices; founder bias thrives in small teams.
Using these practices, you create a feedback loop that keeps your team grounded in customer reality.
Who Should Handle Customer Interviews?
This question comes up in every founder discussion: “Who should be responsible for customer interviews?”
Some say the sales team should own it because they’re closest to customers. Others argue it should be marketing, since they understand messaging and positioning. And many believe it’s the product team’s job, as they’re building what’s being tested.
All valid, of course. However, what I often witness is that when multiple departments get involved, each interprets the same data differently.
It’s like steering a ship while everyone shouts directions from different sides. One group focuses on what converts, another on what looks good, and another on what’s technically possible.
Without a shared process or single source of truth, alignment breaks fast.
That’s why customer interviews need more than a “who,” but they need a system. A good system that will
- Standardizes how interviews are conducted.
- Organizes results in one place.
- Let everyone see and agree on the same insights.
This unified approach saves time and prevents misaligned priorities, like a shared project management tool that consolidates feedback from all teams into a single, actionable roadmap.
Money and Time Optimization on Customer Interviews
Even the founders who believe in research eventually hit a wall. No time, no budget, and too many other fires to put out.
Those are real concerns, and they are tempting to skip interviews altogether, leaning on intuition or moving straight to building. Although in the AI-driven world, where LLMs increase our productivity (such as Prelaunch AI Interviewer), can help to overcome these concerns.
Compared to generic AI’s such as ChatGPT or Gemini, Prelaunch AI Interviewer was built to conduct in-depth, real-time customer interviews and return results overnight by always granting the users access to
- Raw transcripts and recordings for every interview.
- Logs of the AI’s reasoning process.
- Multilingual capability across 30+ languages.
- Full visibility into how themes and patterns were derived.
Yet, using AI tools at work can increase productivity, but overuse of many different tools can distract you from meeting your interview goals.
How to Make the Most of Every Interview (Manual or AI-Assisted)
Conducting customer interviews brings a big pile of information that will be needed, whether you’re running interviews manually or using an AI-interviewer. Accelerated by one of the biggest global innovation platforms and completed over 300 customer interviews in a few months, here is a framework that helped me with customer interviews.
1. Define What You Need to Learn
Are you validating a new feature, exploring a drop in customer engagement, or refining your positioning?
Write it all down. Clarity at this step saves hours later.
2. Identify the Right Segment
Focus on 3–5 customer segments most likely to reveal new insights.
Use your CRM or product data to find users who recently churned, upgraded, or showed unusual behavior.
3. Draft Hypotheses
Before talking to anyone, list 10–15 statements you think are true. Don’t overwhelm yourself with more than that! Your interviews should prove or disprove them.
4. Conduct the Interviews
For manual interviews, use open-ended questions. Instead of asking what they like about your product, ask them to “Tell me about the last time you tried to solve X problem”. For AI interviews, prompt a clear context of what you’re testing, what tone you want, and how insights should be grouped.
5. Act Fast
Don’t let data rot in a folder. Use Prelaunch AI Interviewer’s instant synthesis or your own summary document to group insights into patterns — pains, motivations, objections, and opportunities.
6. Translate Findings Into Actions
Feed the results directly into your sprints or product roadmap. For a new feature, validate your findings by walking a customer through a mock-up or even a verbal description. If something doesn’t align with your strategy, archive it — don’t delete it. Interview data is worth its weight in gold.
Work with Your Customer to Build Value
Every startup book says “listen to your customer.”
Customers care about the value you create for them! But in the chaos of a fast-moving small team, that principle gets buried under tasks, deadlines, and assumptions.
Here’s the truth I believe in:
Your customers are your most underused growth engine.
Every time you interview them, you’re co-designing your company’s development strategy.
So don’t wait until you’re big enough to afforxfprd research. Because when you’re small, you can’t afford to build noise.
You have to build value, not noisy features.
Talking to customers isn’t a luxury. It’s the work that keeps everything else moving in the right direction. You can join the waitlist for Prelaunch AI Interviewer to see how others are keeping those conversations alive.
