Running a user experience survey during SaaS onboarding helps you understand exactly where new users get stuck—and why some become power users while others churn. The right questions, asked at pivotal moments, crack open what drives adoption. This guide spotlights 20 of the best questions for SaaS onboarding, mapped to each stage, and shows how to set up AI-powered follow-ups to peel back the layers of user motivation.
Pre-activation stage: Understanding initial expectations
When a user signs up for your SaaS, they’re full of hope—and questions. This is the perfect moment to surface their goals, pain points, and backstory. Pre-activation questions make sense right after registration, before your product’s magic kicks in.
Discovery questions:
What brought you to our product today? Finds the initial trigger or pain point, revealing what problem your user is trying to solve.
What’s the main result you want to achieve? Brings out their core goal so you can tailor their path and messaging.
Which tools or solutions have you tried before? Surfaces competitor and workflow context—essential for AI follow-up (more on automatic AI follow-ups).
Context questions:
How soon do you need to see results? Gives a sense of urgency—insightful for onboarding speed and expectation-setting.
Are you evaluating this for your team or personal use? Captures scope, so you can segment for B2B vs B2C use cases.
Roughly how many people will use this product with you? Hints at growth and future expansion.
What’s the single biggest frustration with your current workflow? Open-ended, this answer is a goldmine for AI to latch onto specifics and ask why that pain matters.
Use single-select multiple choice for questions about prior solutions or urgency—it gives actionable quant data. For open-ended prompts (like frustrations), let the AI probe deeper with contextual “why” questions. Configuring AI follow-ups to automatically ask ‘Can you give an example?’ or ‘Why is that frustrating?’ turns a generic response into real insight. Teams using onboarding surveys like these see a 20% higher retention rate—largely because they pinpoint what matters, early on. [1]
Activation stage: Capturing first-value moments
Now your user is actively exploring and aiming for that “aha” moment. It’s all about minimizing friction and maximizing wins. The best questions for this stage spotlight what’s helping vs what’s holding people back, so you can design in-product improvements on the fly.
Friction indicators:
What was your first impression of our setup process? Quickly flags friction if users mention length, complexity, or unclear steps.
Was there any step that confused or slowed you down? Pinpoints blockers, letting your AI follow-up probe with “What specifically made this difficult?”
Is there a feature you needed but couldn’t find? Reveals feature discoverability gaps and highlights what to spotlight in onboarding flows.
Did our product meet your expectations so far? Helps you catch where expectations diverge from reality—AI logic can drill into gaps if “no.”
Success signals:
What’s the biggest win you’ve had using our product? Finds the “aha moment” so you know which flows to double down on.
How easy was it to get started, on a scale of 1–5? Use single-select for a quick pulse; then instruct the AI to ask for details if scores are low.
How does our product compare to what you expected when you signed up? Uncovers delight and disappointment in users’ own words.
Friction and success questions need to feel like a friendly check-in. Timing these questions right after key actions (such as completing the setup or using a core feature for the first time) delivers the richest insights. Using in-product conversational surveys means context is always fresh. Configure your NPS question so detractors get a probing follow-up (“What’s the main reason for your score?”), while promoters are nudged for testimonials (“What do you love most so far?”). By surfacing feedback at these crucial junctures, companies see a 10% increase in user adoption rates. [1]
Post-activation: Measuring ongoing satisfaction
Your users have seen the first value and now they’re deciding if your tool fits their longer-term workflow. This is the prime zone for retention and uncovering expansion opportunities.
Feature discovery:
Which features have you used in the last week? Measures adoption and highlights underused gems.
What was most useful in your daily workflow? Reveals stickiness and shows where you’re solving real problems.
Team adoption and integration:
How has your team adapted to the product? Great open-ended setup for AI follow-up about collaboration.
Where does our product fit in your daily/weekly process? Maps your tool’s place in their workflow, surfacing integration value.
ROI and satisfaction:
Since onboarding, has your workflow improved? Quick sense-check, with AI prompting for examples if “yes” or “no.”
Are you considering an upgrade or additional seats? Predicts expansion opportunities and who’s ready for the sales touch.
How likely are you to recommend us to a friend (NPS)? Essential for overall satisfaction—set an every-30-days cadence with deep AI score analysis at AI survey response analysis.
The stats make it crystal clear why surveys matter at this stage: 72% of SaaS users say onboarding surveys help them discover features they otherwise would have missed, and companies who run these see a 25% reduction in churn—not just among new users but for everyone.[1]
When user mentions a specific feature, ask up to 2 follow-up questions about:
1. How they use it in their workflow
2. What outcome it helps them achieve
Keep responses under 50 words each
For fatigue prevention, always use recontact windows (30-60 days for NPS). To dig deeper, instruct AI to ask “How has this feature changed your process?” whenever someone names a tool or integration.
Turning questions into conversational insights
Let’s be real—static forms miss the nuance that real conversations capture. When I use conversational surveys powered by AI, I don’t just get answers—I get the reasons behind them. Configuring your AI agent’s tone is simple: set it to professional if your audience is enterprise/b2b, or keep it casual for startups.
Follow-up depth: Configure the number of probing questions (usually max 2-3) and set rules to avoid pestering.
Persistence: Choose if the AI should keep nudging gently for context, or move on after a partial answer.
Use the AI survey editor to tweak, reorder, or edit questions conversationally—just describe your change and the system handles it instantly.
Multilingual support: For global SaaS, make sure surveys adapt based on user language. It’s seamless with AI.
A traditional static survey—one full of radio buttons—just can’t capture the emotional why. Meanwhile, AI-powered conversation can boost survey completion rates to 70-80%, compared to 45-50% for legacy forms, and slashes abandonment by half. [2] Here’s how the depth compares:
Survey Type | Average Completion Rate | Depth of Insights | Speed of Analysis |
|---|---|---|---|
Traditional Survey | 45-50% | Limited context, few follow-up details | Hours-days |
Conversational Survey | 70-80% | Detailed, context-rich, multi-layered | Minutes-hours |
Chat-based response pattern analysis then tags and summarizes key themes across every journey stage, so you spot friction trends, surface “aha moments,” and segment on actual, nuanced experience—not just crude satisfaction scores.
Quick-start configuration recipe
Let’s set up your first onboarding AI survey in just a few steps:
1. Build your question mix: Start with 2 context questions (“What brought you here?”, “What’s your #1 goal?”), 3 experience questions (like setup feedback, “aha moments”, and pain points), plus a single NPS.
2. Configure AI follow-ups: Tell the AI to clarify when users mention a competitor/product, or to dig deeper when a user described their goal vaguely.
3. Set follow-up max to two per question.
4. Deploy via conversational in-product survey or shareable landing page.
Quick tip: The best responses come from simple, friendly surveys where users feel heard, not interrogated—conversational surveys get 3-5x more detailed feedback.
Your responses from this short list are enough to start building user personas and mapping out journey stages. Don’t overcomplicate—expand your survey over time as you spot new patterns in the data.
AI Follow-up Configuration for Onboarding Survey:
- Ask clarifying questions when users mention competitors
- Probe for specific use cases when goals seem vague
- Explore team dynamics if collaboration is mentioned
- Maximum 2 follow-ups per question
- Keep friendly, helpful tone throughout
Ready to see what’s hiding behind the numbers? Create your own survey and start capturing those must-have onboarding insights—with context, not just checkboxes.