The user interview process is the backbone of understanding what your users truly need, but crafting the right discovery interviews can make or break your research. The best insights rarely come from surface-level questions—instead, they emerge when you probe deeper and let conversations flow naturally.
Great discovery questions paired with AI-powered follow-ups unlock rich context and hidden motivations you’d easily miss in traditional interviews. In this guide, I’ll share the best questions for the user interview process and how tools like AI-driven conversational surveys can help you dig even deeper.
Core questions that reveal user problems and motivations
To get to honest needs and root challenges, the right questions are essential. With decades of research experience—and reinforced by the latest advances in AI-powered interviews—I always lean on a handful of core prompts that invite users to open up. Here are the essentials:
"What's the hardest part about [current process/task]?"
This open-ended prompt gets right to the pain points and emotional hurdles. It encourages people to share frustrations they might not have expressed otherwise—key for finding real opportunities. You can also phrase it as, “Can you tell me about the most challenging aspect of [process]?” or “Where do you get stuck most often?”
"Tell me about the last time you [specific action]"
Concrete examples over generalities every time. This uncovers recent, detailed stories and naturally surfaces what happened, who was involved, and how the user felt. Variations include: “Walk me through your most recent experience with [task],” or “Describe the last time you used [product/feature].”
"What would you do if you couldn't use [current solution]?"
One of my favorites for surfacing workarounds and the underlying needs those solutions address. People reveal creative alternatives and how much they actually depend on what exists. Alternative phrasing: “If [tool/process] disappeared tomorrow, how would you cope?”
"Walk me through how you currently handle [task]"
This question reconstructs the workflow and routines around a job. It exposes inefficiencies, missing pieces, and improvisations. You might also say, “Show me step-by-step how you complete [job],” or “Can you outline your process from start to finish?”
These questions aren’t just about gathering facts—they motivate users to reflect and share nuances that standard surveys miss. In fact, 77.1% of researchers now incorporate AI to empower richer user research, with 51.1% using ChatGPT for tasks like discovery interviews, underscoring the shift to more dynamic, context-aware approaches. [3]
Setting up AI follow-ups that dig like a seasoned researcher
Static surveys miss critical opportunities because they can’t adapt. This is where AI follow-ups transform standard interviews into adaptive, revealing conversations. When you use automatic AI follow-up questions with Specific, you’re empowering every user interview process with the curiosity of a seasoned researcher.
In Specific, you can customize follow-up logic so the AI asks clarifying or probing questions based on each answer. Here’s how I recommend setting it up for different question types:
Ask 2-3 follow-up questions to understand the specific pain points and frequency of the problem. Focus on understanding the impact on their workflow and what workarounds they currently use.
If a user mentions frustration, ask them to describe a recent time when this happened. Probe for how they dealt with the issue and its consequences on their day.
When a user describes a workaround, ask what made them choose that method and if it fully solves the problem or just gets them “good enough” results.
Specific’s conversational survey engine listens to every answer, automatically detecting when a response signals unresolved needs or hidden emotions, then generates contextual probes. A study of 1,800 participants found that AI-powered chatbots conducting surveys consistently elicited more detailed open-ended feedback compared to static forms—elevating data quality for everyone. [2]
Advanced techniques for deeper user insights
Truly effective discovery interviews often mean building flows—sequences of questions that naturally build on each other’s context. In Specific, you can use AI for multi-question flows, customizing both language and tone to match your audience and topic. The AI survey editor lets you tweak everything in plain language, ensuring authenticity and empathy for every respondent.
Contextual branching: Set up conversational logic so if someone shares a pain point, the AI investigates its root cause, frequency, or emotional tone—no scripts needed.
Emotional probing: Teach AI to reflect user language subtly: “You mentioned this is frustrating—can you tell me more about how it affects your work?” This deepens rapport and surfaces experiences that matter most.
Always avoid leading users to answers you’re hoping for. Instead, instruct AI to ask for examples or consequences, keeping responses unbiased while still uncovering motivations.
Traditional interviews | AI-powered discovery |
|---|---|
Rigid question lists | Dynamic, context-aware probing |
Manual note-taking and follow-ups | Automatic analysis and responsive questions |
Limited reach (one-on-one) | Scalable, many interviews at once |
Inconsistent depth between interviews | Consistent exploration across all users |
Conversational surveys allow you to scale rich, in-depth discovery interviews to hundreds—even thousands—of users without losing the subtleties of real conversation. As proof: a SIGDIAL 2024 study reported 69% of participants had positive experiences with an AI-powered, human-like interviewer, confirming AI’s role in modern user research. [4]
Avoiding common discovery interview mistakes
Even experienced interviewers slip up. The four most common mistakes can damage response quality, but AI-powered surveys are purpose-built to avoid them:
Leading questions: Human bias creeps in; we sometimes nudge users toward what we hope to hear. AI in Specific is programmed to maintain neutrality—restating and clarifying without suggesting answers, keeping your data clean and reliable.
Missing follow-up opportunities: When conversation moves fast, even a sharp human might miss a chance to dig deeper. AI never gets tired or distracted; it always asks for clarification and stories, so you capture the full context of every response.
Inconsistent questioning: With manual interviews, fatigue or assumptions easily lead to skipping questions or missing important threads. AI ensures every user gets thorough and fair exploration, keeping your research process truly scientific and repeatable.
Interview fatigue: Traditional interviews can feel like interrogations—leading to short, rushed answers. The conversational format of AI surveys feels more natural, helping users open up and provide more thoughtful, detailed feedback. A Resume Now survey found that 96% of U.S. hiring professionals already use AI to screen and assess, and 94% report these tools are highly effective at surfacing quality candidates—proof of the power AI brings to both interviewer and respondent experience. [1]
Start uncovering deeper user insights today
Supercharge your user interview process with AI-powered discovery interviews that probe beneath the surface. Create your own survey and start revealing the insights that drive smarter decisions.