Finding the right user experience survey questions sample can mean the difference between surface-level feedback and deep insights that transform your product.
In this article, I’m sharing a curated library of UX survey templates built with Specific—organized by sector and question type. You’ll see actionable question examples with AI-powered follow-up instructions, all designed for conversational surveys that make feedback more interactive and revealing.
SaaS user experience survey questions that uncover retention drivers
Understanding why users stick with (or leave) your SaaS product starts with focused UX questions. By mixing question types and leveraging AI-powered follow-ups, you go beyond satisfaction scores to reveal what actually drives loyalty. As organizations increasingly adopt AI-driven tools like Specific to analyze feedback, knowing what and how to ask is more important than ever—78% of organizations now use AI for at least one business function, marking a rapid shift in how insights are surfaced [1].
How easy was it to learn and start using our product?
This question uncovers onboarding pain points. If users say it was challenging, instruct AI to probe for specifics—such as, “Which step or feature was confusing or frustrating?”
What feature do you use the most, and why does it matter to you?
This dives into feature adoption and user priorities. AI can follow up: “Can you describe a recent moment when this feature made your work easier?”
Have you faced any barriers when trying to upgrade your account or unlock new features?
This explores upgrade barriers. Tell AI to follow up: “What could we change in the upgrade process to make it smoother for you?”
On a scale of 0–10, how likely are you to recommend us to a friend? (NPS)
For promoters (9–10), AI could ask what stands out most about the product; for detractors (0–6), instruct AI to ask, “What’s the biggest reason for your score?”
Each example above can be easily customized with Specific’s AI survey builder for your exact SaaS context.
Mobile app UX survey templates for deeper engagement insights
Mobile app surveys need to match how users actually interact—on the go, with limited time and focus. By centering on usability, onboarding, and engagement, you learn what keeps users coming back (or uninstalling).
How was your first experience with our app onboarding?
Great for spotting friction at the very first step. Conversational surveys adapt in real time, letting AI follow up with, “What could have made getting started easier?”
Did you have any trouble finding a feature you were interested in?
Targets feature discovery. AI follow-up: “Which feature did you struggle to find, and how did you try to look for it?”
What made you open our app today?
This gives direct insight into usage motives and context. The AI might probe, “Was there a specific goal you were trying to achieve, or just browsing?”
Is there anything that’s stopped you from using our app more frequently?
Essential for identifying engagement blockers and pinning down moments of churn.
Conversational surveys work better on mobile than traditional forms—they’re more intuitive, ask one question at a time, and AI can drill into friction points dynamically. Specific’s surveys are mobile-optimized from the ground up, so user feedback feels as natural as a chat thread—similar to how 64.7% of small businesses are already integrating AI tools to drive immediate value [3].
E-commerce survey questions that reveal purchase barriers
If you run an e-commerce site, the right surveys let you pinpoint what stops a user from buying. By layering on AI follow-up questions, you can uncover hidden objections and optimization opportunities.
Was there anything about our shopping experience that slowed you down or made you hesitate?
Use AI follow-up to clarify: “What specifically made you pause—product info, navigation, something else?”
What was the main reason you didn’t complete your purchase today?
Tackles cart abandonment. Dynamic follow-ups (like “Was it something about price, shipping, or checkout steps?”) help you diagnose where to focus improvements.
How satisfied were you with the checkout process?
Helps quantify friction. If a user felt stalled, AI can probe, “Which part of checkout felt slow or confusing?”
How did you find the product you were looking for?
Explores product discovery and search efficiency—a core factor in conversion rates.
With the automatic AI follow-up questions feature in Specific, it’s possible to reveal user motives and conversion barriers that traditional surveys would miss. These question templates help you discover new pathways to optimize your buying journey while surfacing objections not visible in analytics dashboards alone.
Mixing question types for comprehensive user feedback
The richest UX insights come from blending open-ended, multiple choice, and NPS-style questions. This approach gathers both structured data and narrative context—so you can spot trends while understanding users’ “why.”
Here’s an example flow for mini UX survey using mixed question types:
What was the goal of your most recent session?
Which of these tasks did you complete today? (Multiple choice: Browsed products, Added to cart, Searched for help, None of the above)
On a scale of 1–5, how easy was it to use the feature you needed? (Rating)
Is there anything else we could improve about your experience? (Open-ended with AI follow-up)
Notice how each question reveals a different layer—first motivation, then actions, perceived ease, and finally suggestions. The right mix makes feedback actionable and reduces survey fatigue.
Question Type | Best Use Case |
|---|---|
Open-ended | Digging into nuanced feedback, motivations, unexpected issues |
Multiple choice | Quantifying actions, prioritizing pain points, segmenting users fast |
NPS/scale | Benchmarking satisfaction, tracking change over time, follow-up triggers |
You can adapt your own flows instantly with the AI survey editor—just describe your audience, use case, and goals, and let the AI handle the structure. For best response rates, start with quick multiple choice or NPS, then dive into (AI-probed) open-ended questions to encourage richer context before fatigue sets in.
Turning user feedback into actionable UX improvements
Collecting deeply conversational feedback is only step one. Specific’s AI-powered analysis features turn raw responses into clear, structured insights, surfacing patterns that you might miss manually. As of 2025, 71% of organizations regularly use generative AI in business processes, making this work faster, more scalable, and less biased than ever [5].
Sample prompts for analyzing UX survey data might include:
Summarize top three friction points mentioned by users who rated onboarding as difficult.
What are the most common reasons cited for cart abandonment by users in the last 30 days?
Spot any new user segments emerging around advanced feature adoption—describe their behaviors concisely.
With AI survey response analysis, you can chat with your UX data the way you would with an experienced researcher. It’s common to discover unexpected user segments this way—like power users making requests you hadn’t considered, or silent churn drivers across certain age groups.
Conversational surveys gather deeper context because AI-generated follow-ups adapt to what matters most. For truly comprehensive analysis, set up multiple AI chats filtering responses by theme (onboarding, mobile friction, upgrade blockers) to unlock a 360° view of user experience.
Start collecting deeper user insights today
Transform your feedback process—start powering smarter experiments with user experience survey questions that go beyond the obvious. Create your own in-product conversational survey and unlock richer, more actionable UX insights in minutes.