When you're looking for an NPS survey example that actually drives results, the key isn't just asking for a score—it's understanding what drives that number.
Traditional NPS surveys often miss crucial context by only asking the standard question.
Using conversational AI, in-product NPS surveys can automatically probe deeper based on whether someone is a promoter, passive, or detractor. In this guide, I’ll break down the best questions for NPS surveys, show how automated AI follow-ups make them richer, and share how you can trigger them at the best moments to capture truly actionable user insights.
The foundation: crafting your core NPS question
It all starts with the core NPS question. The standard wording—while time-tested—can be fine-tuned to fit the nuances of SaaS products and in-app experiences. If you want users to engage honestly and thoughtfully, you need to meet them where they are, both in language and context.
Here are a few proven variations that work especially well for in-product surveys:
Classic approach: "How likely are you to recommend [Product] to a friend or colleague?"
Feature-specific: "Based on your experience with [Feature], how likely are you to recommend us?"
Post-milestone: "After achieving [Milestone], how likely are you to recommend [Product]?"
Create an NPS survey for a project management SaaS that triggers after users complete their first project
In each case, it’s crucial to explain the 0–10 scale clearly so users know exactly what their answer means. But timing matters just as much as wording. For example, research shows that sending NPS surveys within 24-48 hours of a customer interaction ensures the experience is fresh, leading to richer, more specific feedback. [1]
Best questions for promoters: understanding your champions
Promoters—those magical users who give you a 9 or 10—are your potential superfans. But to turn their enthusiasm into actionable advocacy, you need to know exactly why they love your product so much.
Some of my favorite follow-up questions for promoters are:
Value discovery: "What specific aspect of [Product] would you highlight when recommending us?"
Use case mining: "Can you share how [Product] has helped you achieve your goals?"
Advocacy enablement: "What results or outcomes would you share with others?"
Instead of stopping after one open-ended prompt, an AI survey with automatic follow-up questions can ask for concrete examples: “Can you give me a specific example?” or “How much time or money did that save you?” This isn’t just a nice-to-have—dynamic probing in conversational AI interviews drives significantly better quality responses by being more relevant and specific, and it boosts engagement rates. [2]
AI can even tailor the line of questioning based on each promoter’s unique feedback, turning every response into an instant, high-value testimonial or product insight.
Questions for passives: uncovering hidden friction
Passives (scores of 7-8) represent your biggest opportunity for growth. They like your SaaS, but aren’t enthusiastic enough to spread the word. Pinpointing what holds them back is where the gold is.
Friction identification: "What’s preventing you from rating us higher?"
Improvement focus: "What one thing would make you more likely to recommend us?"
Competitive context: "How does [Product] compare to other solutions you’ve tried?"
Don’t settle for generic answers—ask for specifics. AI-enabled surveys excel here, drilling into answers like “it’s okay” by asking, “What specific aspect feels just okay rather than great?” Studies show that targeted conversational probes elicit far more detailed, actionable feedback. [2]
It’s by mining these nuanced, sometimes hesitant responses that you uncover the tweaks or missing features that could push your product into the “can’t live without it” zone.
Questions for detractors: turning criticism into roadmap insights
I see detractor feedback (scores 0-6) not as a threat, but as one of the richest sources of honest product intelligence. The secret is to seek understanding, not to defend your choices or argue back.
Root cause analysis: "What specific experience led to this score?"
Expectation gaps: "What were you hoping to achieve that you couldn’t?"
Recovery opportunities: "What would need to change for you to reconsider?"
Tone matters more here than anywhere—your AI survey should be friendly, empathetic, and never dismissive. Here’s a quick visual on best practices:
Good practice | Bad practice |
|---|---|
“Thank you for being honest—can you tell me more about what made things hard?” | “But most users like this feature. Are you sure?” |
“I’m sorry for your frustration. How could we have made this easier?” | “We don’t usually hear that complaint.” |
AI can maintain this empathetic dialog automatically, which has been shown to increase the depth and quality of feedback, even from users who start out frustrated. [2] And when it’s time to make sense of trends and pain points across hundreds of responses, tools like AI survey response analysis enable you to chat directly with the themes emerging from your detractor segment.
When to trigger your NPS survey: timing is everything
Even the best questions for NPS survey campaigns won’t help if you trigger them at the wrong moment. Well-timed, contextual surveys are key in SaaS—and good targeting can be the difference between insight and noise.
Post-activation (Days 14-30): Trigger after users have had time to experience your core value.
Feature adoption: Trigger 7 days after the first use of a key feature.
Milestone completion: Trigger immediately after achieving a meaningful outcome (like completing the first project).
Renewal approach: Trigger 30-45 days before subscription renewals.
Well-timed, context-sensitive surveys can generate much higher NPS response rates—especially when paired with conversational formats that feel less like interruptions and more like a helpful check-in. [1] Don’t forget to configure frequency controls (like max once per quarter), and use advanced in-product targeting to reach the right users at the right moments, never spamming or fatiguing your customer base.
Putting it together: complete NPS survey examples
Let’s make this concrete with two NPS survey flows you can generate and adapt using conversational AI:
Example 1: Post-onboarding NPS
Core NPS question, triggered 14 days after signup
Promoter branch: “What features helped you most during onboarding?” “How would you describe our product to a teammate?”
Passive branch: “What did you expect that was missing?” “What would have made onboarding smoother?”
Detractor branch: “What obstacles or issues did you encounter?” “If we fixed one thing, what would make you reconsider?” (all with empathetic, supportive responses)
Create an NPS survey for a CRM tool that triggers 14 days after account creation, with follow-ups that explore specific features for promoters, identify gaps for passives, and understand blockers for detractors
Example 2: Feature-specific NPS
NPS score question after a user tries your new reporting feature three times
If promoter: AI asks for details on the favorite elements and best use case stories
If passive: AI probes for confusing UI, missing filters, or workflow friction
If detractor: AI investigates what’s confusing, slow, or broken, with friendly promises to share feedback with product team
Build an NPS survey for users who've tried our new reporting feature at least 3 times, focusing on understanding their specific use cases and any limitations they've encountered
The magic is in the branching and the tone. Each branch and probe should fit the user's score, and with the right level of conversational depth, even a simple SaaS feedback survey feels like a personal user interview. With AI, you can easily generate and customize these NPS surveys to suit your workflow—no scripting expertise required.
Transform NPS from score to strategy
The difference between basic NPS and strategic, actionable NPS is all about what happens after the score. Thoughtful questions paired with the right timing create conversations—conversations that reveal not only the “what” but the “why” and “how.”
With AI-powered follow-ups, every response becomes its own mini user interview, happening automatically and at scale. This means you’re not just measuring customer loyalty—you’re understanding it on a granular level, using insights to drive product decisions, refine user journeys, and create real advocates.
Ready to move beyond simple scores? Create your own NPS survey with intelligent follow-ups that adapt, probe, and build real understanding with every response.