How do you conduct a user research interview? Best questions for user research interviews that unlock real insights with AI surveys

If you’re wondering how do you conduct a user research interview that actually leads to actionable insights, start with strong questions. This guide shows you exactly how to craft effective research questions using conversational AI surveys—no more hours in traditional interviews, no more manual note-taking.

With AI-powered conversational surveys, you get the depth of 1:1 interviews automatically, with sharper follow-ups and richer feedback every time.

Map your research goals to question types

Every great user research interview starts with clear goals, and each goal needs the right kind of question. Instead of a one-size-fits-all script, I map research objectives to question types designed to unlock exactly the insights I want.

The Specific AI survey builder does a lot of this heavy lifting for you—match your research “why” to the right question automatically, so you skip the guesswork and get a sharp survey every time.

Behavioral questions dig into “how” and “when”—think usage habits, workflow steps, or the actions users actually take. They give me the raw, messy truth about what people do, not just what they wish they’d do. For example, “Walk me through how you solved this last time.”

Attitudinal questions get at beliefs, preferences, and emotions. They’re about why users feel a certain way or make particular choices—for example, “What matters most when you choose a tool?” These questions surface the stories and motivations behind the actions.

AI-driven surveys can boost completion rates to 70–90%, far outperforming traditional surveys which often linger around 10–30% completion. That means you get much broader and richer data for every goal. [2]

Best questions for user research interviews: open-ended starters

Unlocking honesty and detail in research always comes down to starting with open-ended questions. In my experience, these are the best openers to include in your script:

• Walk me through how you currently…
  This draws out detailed descriptions of real behavior—perfect for mapping user journeys or uncovering unexpected bottlenecks.

• What’s the most frustrating part about…?
  Users will highlight pain points and emotional triggers, giving you a hit list of improvement opportunities.

• Can you recall the last time you…?
  This roots the conversation in specifics, surfacing actual examples, not hypothetical answers.

• Tell me about a time when…
  Great for revealing real user stories, edge cases, and exceptions to the rule.

• Why did you choose [product/solution] over alternatives?
  This gets to the heart of motivation and purchase drivers.

• If you could change one thing about…
  This elicits creative ideas and points out unmet needs directly from users.

• What surprised you most while…?
  Uncovers moments of delight, confusion, or misalignment between expectations and reality.

Each of these starter questions works best when paired with AI follow-ups that dive deeper—so after “Walk me through how you currently handle this,” the AI can gently prod for more detail, clarify steps, or ask for examples. Learn more about how automatic AI follow-up questions work in conversational surveys and why they make a difference.

What I notice again and again: because conversational surveys feel like a friendly chat, participants open up more. There’s less “form fatigue,” so you get candid, thoughtful responses—almost like you’re sitting next to them, talking over coffee. A recent study with 600 participants found that AI-driven conversational surveys yielded much richer, more specific responses, with higher engagement than traditional forms. [1]

Add AI follow-up intents for deeper insights

It’s not enough just to start a conversation—you need to keep it going. That’s where AI follow-up intents come in. These are dynamic, real-time prompts that probe, clarify, and expand on user responses. Here are the main types I use:

• Clarification
  

  Could you explain what you meant by "hard to use"?

• Emotion exploration
  

  How did that make you feel when it happened?

• Use case discovery
  

  Can you share a recent example of when you tried that feature?

• Motivation probing
  

  What made you decide to switch at that moment?

• Comparative exploration
  

  How does this tool compare to others you’ve tried?

These intent types make conversational surveys feel alive—they adapt to what the respondent says, just like in a live interview. Respondents don’t just tick boxes; they explain, reflect, and dig deeper alongside you.

Follow-ups transform a static survey into a genuine conversation, which means you capture more context, authenticity, and “aha!” moments.

One thing I love: AI adapts these follow-ups in real-time, tailoring prompts to each user’s wording and logic. That means you always get the next best question, without any manual setup. Studies show that this kind of AI probing increases the detail and specificity of responses, although on mobile, user experience can be a little less smooth. [5]

Sample user research script with probing rules

Want a plug-and-play script? Here’s how I structure a product feedback interview that gets to the heart of what matters:

• Q1 (Behavioral): “Walk me through the last time you used [the product/service].”
  AI Rule: Probe for step-by-step details, clarify vague actions.

• Q2 (Attitudinal): “What did you like most and least about that experience?”
  AI Rule: Explore emotional responses, ask for reasons behind likes/dislikes.

• Q3 (Comparative): “How does this compare to what you’ve used before?”
  AI Rule: Ask for specific comparisons and differences, dig into tradeoffs.

• Q4 (Pain Points): “What’s the most frustrating thing you encountered?”
  AI Rule: Dive deeper into the ‘why’, and probe for impact on workflow.

• Q5 (Improvement): “If you could wave a magic wand, what would you change?”
  AI Rule: Encourage creative thinking, ask for examples or context.

To analyze results at scale, I use Specific’s built-in AI survey response analysis. With a prompt like:

Summarize the top three recurring issues users mentioned in their open-ended responses.

Or, for a different cut:

Highlight any surprising suggestions or themes that came up in the feedback.

Want to tweak the questions or logic? The AI survey editor lets you rework the flow (and even the tone) by simply chatting with the AI. No spreadsheets, no survey fatigue—just agile, high-quality interviews in minutes.

And if you’re ready to dig deeper, chat with AI about survey results for instant pattern recognition, actionable insights, or custom summaries.

Start conducting better user research interviews

Conversational AI transforms user research—letting you scale interviews, capture real insights, and free yourself from scheduling headaches. Discover nuanced answers and see what users really think. Create your own survey now.