Getting great questions for onboarding interviews ready is crucial for understanding how new users experience your product during their first interactions.
This article provides question sets and strategies for conducting effective interviews with users during onboarding, using AI-powered conversational surveys.
You'll discover the most effective first-session questions, learn how to follow up in the first week, and see how in-product targeting delivers feedback at the perfect moment for actionable insights.
First-session onboarding questions that reveal immediate friction
The first session is your window into the most honest impressions and pain points. First-session questions should capture these raw reactions, surfacing fresh insights before memories start to blur. Here’s how I approach it:
Initial expectations: “What brought you to [product] today?”
This uncovers user intent and what job they hope your product will do—essential for aligning onboarding journeys with real goals.First impression: “How would you describe your first experience with [product]?”
Sentiment here is gold. If a user mentions a pinch point (“felt a bit lost creating my first project”), AI can instantly probe with clarifiers, surfacing specifics you’d otherwise miss.Value discovery: “Which feature caught your attention first?”
When a feature stands out, that’s your hook. AI follow-ups explore why it resonated and what about it sparked interest. Read how automatic probing works in practice.Setup friction: “Was there anything confusing during setup?”
AI goes straight to the cited friction—“You mentioned an issue with permissions; can you tell me more?”—to fix what actually holds people back.
Analyze first-session responses to identify the top 3 friction points users encounter during initial setup and suggest improvements for each
The value is clear: 52% of users say they’ve abandoned products due to confusing onboarding[1]. Early, specific feedback avoids this churn spiral.
First-week experience questions that track user progress
After the initial encounter, users go from confusion to discovery—ideally. First-week questions help you track where they land and where they stall. It’s not just about sentiment, but about how their experience is evolving and why.
Usage patterns: “How has [product] fit into your workflow this week?”
AI surfaces non-obvious use cases and flags integration gaps.Value validation: “Has [product] helped you achieve what you hoped?”
Follow-ups dig for unexpected wins or disappointments that inform roadmap priorities.Feature discovery: “What features have you tried beyond your initial use?”
This uncovers adoption blockers—and AI can probe why something wasn’t explored.Comparison to alternatives: “How does this compare to what you used before?”
Contextual probing here—“What’s a workflow where this falls short?”—makes competitive insights actionable.
Follow-up Type | Example |
|---|---|
Manual | Generic "Can you tell me more?" |
AI | "You mentioned the dashboard was confusing - which specific elements made it hard to navigate?" |
Tracking how sentiment and engagement evolve helps you pinpoint where users activate or drop off. Research shows that engaged users within the first week are up to 4x more likely to stick around[2]. Conversational surveys deliver these signals with context, not just numbers.
Smart in-product targeting for timely onboarding feedback
Timing is everything in onboarding feedback—catching users at just the right moment delivers richer, more honest responses. Behavioral triggers are the secret ingredient to next-level insights.
Time-based triggers: Show a first-session survey 2 minutes after signup. This catches users once they’ve explored but before details fade.
Action-based triggers: Launch feedback immediately after the first core action (for example: creating the first project). Value perception is captured when it’s top of mind.
Milestone triggers: Trigger a week-one survey after three product sessions to ensure there’s enough experience for meaningful insights.
Exit intent triggers: Detect signals like rapid clicking or frequent help doc visits, then intervene with targeted questions to rescue confused users.
Conversational surveys feel less intrusive than traditional forms, so users are more likely to share openly. This approach boosts completion rates—one study showed chat-style surveys achieve up to 40% higher response rates than static forms[3]. Dive deeper on in-product targeting here.
Specific delivers best-in-class experiences for both survey creators and respondents, making every feedback opportunity smooth and engaging.
How AI follow-ups turn surface feedback into actionable insights
AI follow-ups act like the best user researchers—they listen deeply, then ask just the right thing to get the true story, not just the polite one. Here’s how probing turns casual feedback into gold:
Example 1: User says “The setup was okay” → AI follows: “What specific part of setup took longest?” → Reveals authentication flow confusion that needs fixing.
Example 2: User says “I'm still figuring things out” → AI: “What’s the main thing you’re trying to accomplish?” → Surfaces mismatched expectations—opportunities for better guidance surfaced instantly.
Example 3: User remarks, “It’s different from [competitor]” → AI: “What’s the biggest adjustment you’re making?” → Uncovers mental model conflicts that product and education teams can address directly.
AI-driven follow-ups make surveys feel like true conversations, lifting the quality and clarity of user responses far beyond what static forms achieve. Explore how chat-based feedback analysis works and discover what you’re missing in surface-level surveys.
When surface feedback becomes deep context, product teams stop guessing and fix what really matters.
Crafting questions that feel natural while gathering structured data
Onboarding interviews don’t have to feel like interrogations. Here’s how I balance open exploration with the kind of structure you need to see patterns and drive product decisions:
Start broad, then narrow: Warm up with “How’s your experience so far?” before dropping into specific feature or workflow questions.
Mix question types: Blend open-ended questions for discovery with single-select for validation (think: ask for stories, then follow with NPS).
Natural transitions: Don’t jump abruptly—use conversational bridges to keep feedback flowing smoothly.
Practice | Example |
|---|---|
Good | “Now that you've explored a bit, which features are most relevant to your work?” |
Bad | “Rate the following 15 features from 1-10” |
Tone matters—an AI-guided survey can keep a voice that matches your brand (professional, casual, super-friendly) throughout the conversation, so feedback feels like advice from a peer, not a test. Try the AI survey editor to craft every question in your style.
Start capturing rich onboarding insights today
Transform onboarding feedback from guesswork into data-driven improvements. Stop losing users in their first week—use conversational AI surveys to understand exactly where they struggle. Ready to create your own onboarding interview survey? Use our AI survey generator to build one in minutes.