Qualitative Interviews: Types, Questions, and Best Practices

Interviews are rich territory for understanding what drives users. Conducting them seems pretty straightforward. You sit down, ask questions, and take notes (thank goodness for note-taking tools!).

But if you want actionable results, you need a more focused approach. One that allows you to:

• Ask questions that give you valuable answers
• Extract the most relevant insights from your hours of recordings

In this guide, we'll show you how to plan, conduct, and analyze a qualitative interview to help shape your product.

When you’re ready to turn insights into actions, our AI-powered qualitative analysis platform and UX research repository is there to help.

Create a free HeyMarvin account to manage your user interview panel, select participants, and automate recording and analysis — all within one platform.

TL;DR - What you need to know about qualitative interviews

Interviews are among the most common methods of qualitative research. By asking carefully developed open-ended questions, you can understand how people think and feel about your product or service.

Whether structured, semi-structured, or unstructured, qualitative interviews can help you spot issues early, improve product decisions, and increase business success.

Below, you’ll discover the full process, along with practical examples you can use in your own interviews: exploratory, experience-based, and reflection-based questions.

What is a qualitative interview?

A qualitative interview is a conversation with a purpose. You ask open-ended questions to get deep insights into how people think, feel, or behave.

When doing such interviews, you’re not after numbers or stats. You’re looking for raw, detailed answers that reveal your users’ motivations, struggles, and needs.

Imagine you’re talking to users about their experience with a new app feature. Instead of asking, “Do you like it?” (which might lead to a simple yes or no), you’d ask, “What stands out to you about this feature?”

This approach gives interviewees room to open up, so you can pick up on specific words, tones, or ideas that tell you why they feel a certain way.

Purpose and benefits of qualitative interviews

The main goal of qualitative interviews is to capture a user’s experience in their own words. You’re looking for the small details and emotional nuances that can drive meaningful product improvements.

This approach brings unique benefits to your product development process:

• Spot usability issues early: Hear directly from users about friction points in a new product feature or process.
• Improve design decisions: Gather actionable feedback that sharpens your design choices and aligns with user needs.
• Enhance empathy: Better connect and understand real user experiences to shape better UX within your product.
• Gain richer insights: Discover nuanced details that surveys miss, such as user frustrations or hidden needs.
• Boost product success: Gather data that directly influences product roadmaps, leading to more user-centered development.

Types of interviews in qualitative research

Interviews are conversations — but not all conversations are the same. Different interview types suit specific goals, depending on how much structure you need and how much freedom you want users to have.

Here’s a quick look at four key types of qualitative interviews that can uncover unique insights at each stage of product development:

1. Structured interviews

Think of the structured interviews as the “no surprises” approach.

You ask every participant the same questions in the same order, with little room for variation.

This style is great when you need consistent data to compare across users — for instance, when testing a standard onboarding flow in an app.

2. Semi-structured interviews

As the name suggests, this style gives you some flexibility. You start with set questions but can adjust them based on how users respond.

Semi-structured interviews are ideal for exploring new features. You have a few key questions about a feature’s ease of use, yet when someone mentions a specific pain point, you go a bit off course and ask more questions about it.

3. Unstructured interviews

Here, you’re free-forming, listening, and letting users lead. You might have a topic in mind, but let the conversation flow naturally.

This approach is best for broad, open-ended research, such as learning how users manage a problem in their daily workflow without using a specific app.

4. In-depth interviews

As the name suggests, in-depth interviews are designed to be deep.

While any interview type can be detailed, in-depth interviews focus solely on complex topics. For example, you might spend a full session unpacking one user’s experience with your product, layer by layer.

Unlike structured or semi-structured interviews, these sessions don’t follow a tight script. As a result, you’re allowing the user’s insights to unfold naturally.

The qualitative interview process

No matter how structured or free-flowing your interview is, you want to conduct it with a clear process in mind. Following a set plan has multiple benefits:

• Keeps you organized through each stage
• Creates a safe space for honest answers
• Leads you to more reliable data

Below is the interview protocol for qualitative research, broken down into its three essential steps.

How to prepare for the qualitative interview process

"By failing to prepare, you're preparing to fail,"

said Benjamin Franklin.

Indeed, preparation sets you — and the participant — up for success. Here’s what steps it involves:

• Define your goals: Know exactly what you want to learn.
• Choose your format: Decide if it’ll be structured, semi-structured, or unstructured.
• Write a guide: Create a flexible list of questions, leaving room for follow-ups.
• Set up your tools: Check your recording equipment, note-taking tools, and anything else you need.
• Make your participants comfortable: Brief them on the topic and let them know they can speak freely.

How to conduct qualitative research interview

This should be fun. You sit back and let your respondent talk. But don’t relax just yet. 

Staying vigilant is critical for guiding them and even asking spontaneous follow-up questions.

• Start with a warm-up: Begin with easy questions to break the ice.
• Stay neutral: Avoid leading questions; you want their honest perspective.
• Follow their lead: If they mention something intriguing, ask for details.
• Take notes but stay engaged: Jot down highlights, but make eye contact and remain responsive.
• Wrap up with thanks: Let them know their input was valuable and ask if they have any questions.

How to analyze qualitative interview data

The interview is over, but the job is far from done. 

Here’s how to maximize the analysis of interview data:

• Transcribe your interview: Get everything down word-for-word if possible.
• Look for themes: Identify patterns, keywords, or common issues users mentioned.
• Tag data points: Organize information by tagging. Examples of tags include user needs, pain points, and suggestions.
• Synthesize insights: Quantify your qualitative data. Then, summarize what you learned and how it impacts your design or product goals.

By this point, the excitement of hearing directly from your users has probably faded. You look at all the data and start feeling the pressure of analyzing it without missing essential insights.

Our AI research assistant takes away that pressure, offering you the following:

• Real-time transcriptions that capture every word
• Time-stamped notes and tags to mark the key moments
• Automated workflows that organize and analyze your data
• Qualitative data analysis broken down into beautiful charts and graphs
• Quick clips, highlight reels, and interactive reports of your users’ feedback

Ready to see HeyMarvin in action? Book a demo to discover how HeyMarvin can help you at every step of your qualitative interview process, making things faster, easier, and clearer.

Qualitative interview questions

The right qualitative research interview questions are critical for your success. Typically, they tick the following boxes:

• Open-ended
• Specific enough to guide responses
• Flexible enough for users to express themselves freely

Your goal? Encourage users to open up and reveal their thoughts, feelings, and experiences.

Qualitative interview questions examples

We call it an interview, but it’s more of a “friendly interrogation.” Each question has a purpose and, based on its focus, it can be:

• Exploratory
• Experience-based
• Reflection-based

Mixing these question types lets you gather a range of insights, from general impressions to specific experiences.

Take a look at the following examples of qualitative research questions for interviews to see what we mean:

Exploratory questions

These questions explore general attitudes and needs. They’re perfect for the early stages of understanding how users feel about a topic before jumping into specific product interactions.

Examples:

• “What are the biggest challenges you face in your day-to-day tasks?”
• “How do you typically solve problems in your work?”
• “What tools or resources do you find essential to your workflow?”
• “If you could create an ideal solution for your biggest challenge, what would it look like?”
• “How do you decide which tasks or goals to prioritize in your work?”

Experience-based qestions

As the name suggests, these questions focus on users' interactions with your product. Use them to uncover what’s working and what needs attention in your design or functionality.

Examples: 

• “Can you walk me through your last experience using this feature?”
• “What did you find most helpful or frustrating during that interaction?”
• “Were there any steps that felt confusing or unnecessary to you?”
• “How did using this feature compare to what you expected?”
• “Was there a moment when you felt particularly satisfied or unsatisfied while using it?”

Reflection-based questions

With reflection questions, you ask users to think back on their overall impressions and takeaways. You’re trying to understand their lasting thoughts about the experience.

Examples: 

• “Looking back, what stands out to you most about using the product?”
• “If you had to describe your experience with this feature in one sentence, what would it be?”
• “What would you change about the feature if you could?”
• “How likely are you to use this feature again, and why?”
• “What’s one thing you’d tell a friend or colleague about this product?”

Best practices for qualitative interviews

Conducting a qualitative interview involves a lot more than just asking questions.

You’re setting the stage for an honest, open conversation, so you want to create a smooth experience for you and your participants.

Below are some of the best user interview tips. Use them to keep the conversation natural and meaningful, gaining richer insights:

• Build rapport first: Start with small talk to make the participant comfortable.
• Ask open-ended questions: These invite fuller answers, helping you capture detailed insights.
• Be an active listener: Show you’re engaged by nodding, giving verbal cues, and asking follow-up questions.
• Avoid leading questions: Keep questions neutral to avoid biasing the responses.
• Stay flexible: Let the participant guide parts of the conversation; sometimes, the best insights come unplanned.
• Record with permission: This ensures accuracy and lets you stay focused on the conversation.

How to get more from every qualitative interview with AI

AI automates tasks, freeing up time for high-level work. It allows you to be present during interviews and spend more time and your best judgment to validate the results. Here’s how it supports every step of your interview process. 

1. Sharpen your approach before the interview begins

Instead of starting from a blank page every time, use AI to draft an interview guide. AI can give you something to work on or evaluate whatever you’ve been drafting so far:

• Suggest questions by accounting for your goals
• Review the questions you wrote
• Flag anything that sounds too leading or vague
• Follow up with other relevant questions

AI can also help you organize your existing knowledge base. You can have it look at your research repository and pull past insights, cluster themes, and extract insights. All so you can avoid asking questions you already know the answers to.

Use AI-powered deep research to identify gaps in your data and shape future interviews that will provide the missing information.

2. Stay more present during the actual interviews

AI integrates real-time transcription and note-taking into the process, so you no longer have to split your attention between listening and writing things down. Instead, you can be truly present. You’ll pick up cues such as tone, hesitation, or uncertainty, and use them to craft relevant follow-ups on the spot.

Some teams also use AI interviewers to run sessions at scale. This method works well for early-stage exploration or for gathering input from a larger group within a short timeframe.

3. Make sense of your data after the interviews

Analyzing hours of conversations is the most time-consuming part of your research. AI can significantly speed things up and extract a first rough round of insights from your data as it:

• Transcribes interviews
• Highlights the most important parts or quotes
• Tags data and clusters the tags into themes
• Creates playlists of relevant insights, with citations, so you can support your findings
• Generates reports with clear visuals, statistics, and quotes

Even though you’ll still need to review all the AI outputs and validate them, the time savings are significant. And you are once again free to focus on validating and prioritizing the most relevant findings.

But perhaps the biggest leverage of using AI for qualitative interview analysis is the ability to link insights from all your studies.

AI will review interviews one by one and link findings across your entire research repository. Therefore, it will tell you how often certain themes appear overall and compare insights between different user groups and studies. This is the kind of big-picture analysis on which  researchers spend weeks of hard work. AI can give it to you in hours.

Frequently asked questions (FAQs)

We’ve covered the big pieces. Now, here’s what else you might want to know:

Are interviews qualitative or quantitative?

At their core, interviews are a qualitative research method that leverages the relationship with the interviewee to obtain deep, nuanced answers. With this approach, you explore how people think and feel, in their own words, through detailed, open-ended answers.

Sometimes, when you analyze your interviews to categorize answers or observe patterns, you can also extract quantitative insights.

What is the difference between a qualitative interview and a user interview?

The term “qualitative interview” refers to a research method that uses open-ended inquiries to explore how users feel, think, and behave.

“User interview” indicates who you’re talking to and how that method applies in a specific product/UX context. It’s just one type of qualitative interview, along with:

• Stakeholder interviews (internal conversations)
• Subject matter expert (SME) interviews
• Customer-facing team interviews (with people in support, sales, or customer success roles)
• Buyer interviews (in B2B contexts in which the buyer isn’t always the end user)

How long should a qualitative interview last?

Keep it short enough to stay sharp. Interviews that are 30 to 60 minutes give you time to dive into key topics without wearing out the participant. 

You want detailed answers but not at the cost of the user’s attention or energy.

What is the ideal sample size for qualitative interviews?

While it might sound small, 5–10 participants per user group should be enough to reveal key themes. 

This sample size will also allow you to uncover patterns without overloading yourself with data.

How can technology enhance qualitative interviewing?

Technology brings ease and accuracy to qualitative interviewing. When using supportive tools, you can stay fully present and focus on the person you’re interviewing, knowing every detail is captured.

That’s why our AI qualitative research assistant is so powerful—it handles both transcription and qualitative interview analysis. HeyMarvin features real-time transcription and automated tagging, reducing your time to insights by days.

Conclusion

You now have everything you need to make your qualitative interviews count. 

From preparing thoughtful questions to carefully guiding your interviewees, each step we discussed will:

• Add depth to your understanding of what drives users 
• Guide you to create products that truly resonate

But we all know the challenge doesn’t end with the conversation. Organizing, analyzing, and sharing insights can be just as tricky.

That’s where HeyMarvin comes in to automatically transcribe, tag, centralize, and analyze your data. Our tool helps you make sense of ALL your interviews and build user-centered products that solve real needs.

Get started with HeyMarvin today! Our intuitive AI-powered platform will make qualitative research your new superpower.