This article will guide you on how to create a user survey about feature requests, fast and stress-free. At Specific, we help you build surveys like this in seconds—no guesswork, no endless forms.
Steps to create a survey for users about feature requests
If you want to save time, just generate a survey with Specific—it takes seconds and works for any user or feature request research.
Tell what survey you want.
Done.
You genuinely don’t need to read further if your goal is speed. With AI, the survey instantly embeds expert knowledge, plus it asks dynamic follow-up questions to gather real user insights—not just surface-level answers. If you ever want to tweak or create something more custom, the AI survey generator lets you go from idea to publish-ready survey with plain language. This is conversational survey design at its best.
Why user surveys on feature requests matter
The importance of user feedback hardly needs selling, but it’s worth seeing just how much you can lose by not running these surveys. If you’re not asking users what they want, you risk:
Missing out on emerging needs before competitors address them
Letting valuable users churn without understanding why
Wasting development time on features no one asked for
We all like to think users will tell us openly when they're dissatisfied. The reality: only 1 in 26 customers will share a negative experience—the rest just disappear [1]. By not having an ongoing feedback loop, products stagnate and loyal users quietly move on, often without a trace.
Conversational user surveys empower your team to catch pain points and new ideas in real time. With the right tool, gathering these insights isn’t just possible—it’s painless.
What makes a good survey on feature requests?
You get better insight when your survey is clear, concise, and genuinely feels like a conversation—not a test. The importance of survey design can’t be overstated. Research shows that using a conversational tone can increase completion rates by up to 17% [2].
Ask simple, unbiased questions to ensure clarity
Keep the language friendly, encouraging respondents to share honest feedback
Balance open-ended and closed-ended questions for depth and structure
Bad practices | Good practices |
|---|---|
Leading questions: “Don’t you agree this feature is important?” | Neutral questions: “How important is this feature to you?” |
Too many questions (survey fatigue) | Keep it concise (under 10 minutes) |
No context/follow-ups | Conversational, clarifying follow-ups |
The real measure of a great survey? High quality responses that don’t drop off halfway through—and a healthy quantity, too. If you only get a few short answers, or everyone abandons your survey, you’re not actually learning what matters to users.
What are question types with examples for user survey about feature requests?
Choosing the right mix of question types is a big deal—it shapes the kind of insight you’ll get. For user surveys about feature requests, we recommend a blend of open-ended, single-select multiple-choice, NPS, and targeted follow-up questions. If you want more inspiration, see our guide to the best questions for user surveys about feature requests.
Open-ended questions are gold when you want users to share their thoughts freely—great for surfacing new requests or pain points. They work best at the start, or to follow up on a specific answer. Here are two examples:
“What’s the one feature you wish our product had right now?”
“Tell us about a recent time you felt limited by the current feature set.”
Single-select multiple-choice questions keep things structured, making it easy to quantify trends. They’re excellent for prioritizing requests or measuring consensus. For example:
Which type of new feature would be most valuable for you?
Performance improvements
Customization options
Integrations with other tools
Better reporting and analytics
NPS (Net Promoter Score) question is ideal for benchmarking user satisfaction and loyalty around recent changes or new features. Want an instant NPS survey for users about feature requests? Generate one here. Example:
On a scale of 0 to 10, how likely are you to recommend our product to a friend after trying new features?
Followup questions to uncover "the why": Open-ends and ratings are helpful, but you get to the real insight by asking “why?” or “can you tell me more?”. Follow-up questions clarify vague responses, or expand on specific pain points. Good examples include:
“You mentioned wanting more integrations. Why is that important for your workflow?”
“You rated the new analytics feature a 5. What’s missing for you?”
If you’re building this out, or just want to up your game, our guide on survey questions for feature requests is packed with ideas and best practices.
What is a conversational survey?
Unlike old-school forms where you throw 20 questions at your users, a conversational survey feels more like a friendly interview. Each question is delivered in a chat, and the AI adapts the conversation based on how users respond. Traditional survey builders force you to think through every branch and follow-up; with AI, the process is radically simpler, faster, and much more human.
Manual surveys | AI-generated surveys |
|---|---|
Static questions | Dynamically adapts based on answers |
Hard to personalize | Automatic context-aware follow-ups |
Often low completion rates | Feels like a chat, engages users |
Why use AI for user surveys? AI unlocks everything modern research needs: a conversational experience, dynamic follow-ups, and higher engagement. With AI survey generators, the results speak for themselves—AI-powered surveys can increase response rates by up to 40% [2]. Plus, using a tool like Specific, survey creators and respondents both enjoy a seamless flow. If you want a play-by-play on creating these, check out our detailed guide on how to create a survey—you’ll see just how fast and frictionless it can be.
Specific sets the gold standard with a conversational survey builder and the best respondent experience—mobile-friendly, visually clean, and naturally engaging for both you and your audience.
The power of follow-up questions
If there’s one feature that sets conversational surveys apart, it’s automated, AI-generated follow-ups. Automated follow-up questions dig deeper, ask for clarification, and push for specifics the way a human researcher would. With Specific, the AI listens contextually to the user’s previous answer and can probe in real time, unlocking a richer layer of understanding. This saves immeasurable time you’d otherwise spend emailing back and forth, and keeps the survey flow feeling organic, not robotic.
User: “I want better charts.”
AI follow-up: “Can you share which kinds of charts or reports you need most, or where current ones fall short?”
How many followups to ask? Generally, 2-3 smart follow-up questions hit the sweet spot between clarity and fatigue. You always want the option to let users skip once you’ve learned enough. Specific lets you adjust these settings to fit your goals and audience (and skip when appropriate).
This makes it a conversational survey. Instead of just collecting data, you create a real dialogue—participants feel heard, and responses are instantly more valuable.
Analysis, insights, and AI: With all these follow-ups, you might worry about parsing big blocks of text. No stress—our AI makes response analysis effortless. Check out this article on analyzing user survey responses for how easy it actually is.
Conversational, automated follow-ups are a newer concept, so if you haven’t tried it yet, generate a survey and watch the experience play out in real time.
See this feature requests survey example now
See real results and meaningful insights: create your own survey in seconds and discover why conversational surveys powered by AI can make all the difference.