Here are some of the best questions for a user survey about churn reasons, plus tips for crafting them. You can build your own AI-powered churn survey in seconds with Specific.
Best open-ended questions for user survey about churn reasons
Open-ended questions invite genuine stories and surface details you didn’t know you needed. They’re ideal when you want to get at root causes for churn—what users really think, not just which option they click. This is your chance to find the “why” that doesn’t fit a checkbox.
With churn costing U.S. businesses around $168 billion annually, getting to the heart of users’ reasons is mission-critical [3]. Here are 10 open-ended questions to uncover the full story:
What was the main reason you decided to stop using our product?
Can you describe any frustrations or challenges you encountered before cancelling?
Is there a specific feature or experience you wish had worked better for you?
Were there expectations you had that weren’t met? If so, what were they?
Is there anything we could have done differently to keep you as a user?
Did you consider any alternatives or competitors before leaving? Why?
What would have made you stay?
If you could change one thing about our product, what would it be and why?
Please describe how our service fit (or didn’t fit) into your workflow or daily routine.
Any last thoughts or advice for us as we try to improve?
Use open-ended questions like these when you want rich, detailed feedback that reveals patterns and the nuanced motivations too easily lost in stats alone. They’re especially powerful early in a research project, or anytime you want to catch issues you didn’t know to ask about.
Best single-select multiple-choice questions for user survey about churn reasons
Single-select multiple-choice questions are unbeatable when you need fast quantifiable insights. They help you spot the “top 3 reasons” for churn at a glance—or quickly segment by user type. They’re also a great conversation starter for respondents who might feel overwhelmed by a blank text box.
Question: What was the biggest factor in your decision to cancel?
Product didn't meet my needs
Found a better alternative
Too expensive
Poor customer support
Other
Question: How satisfied were you with the value our product provided?
Very satisfied
Somewhat satisfied
Neutral
Somewhat dissatisfied
Very dissatisfied
Question: Did you reach out for help before deciding to leave?
Yes, and my issue was resolved
Yes, but my issue remained
No, I didn’t reach out
When to follow up with "why?" After a respondent selects a predefined reason (like “Product didn’t meet my needs”), ask why. It opens up space for specifics and real-life examples that drive action. For instance, if a user selects “Too expensive,” your follow-up could be: “What about the pricing felt too high for you, or how did it not match what you expected?”
When and why to add the "Other" choice? Always. “Other” prevents you from missing that one-off gem—a reason you hadn’t anticipated. When someone picks “Other”, trigger a follow-up: “Please describe in your own words.” This simple tweak can uncover entirely new churn causes your team wasn’t even tracking.
NPS question for user survey about churn reasons
NPS (Net Promoter Score) asks: “How likely are you to recommend our product to a friend or colleague?” It’s a trusted metric for overall satisfaction and loyalty—and when users churn, understanding their score (and the reasons behind it) can reveal where loyalty broke down. Given that retaining a customer is up to seven times more cost-effective than acquiring a new one [4], NPS provides a quick pulse check you can dig into further.
For churn analysis, use NPS as an anchor and immediately follow up for detail on low scores. You can instantly create a tailored NPS churn survey with Specific.
The power of follow-up questions
If you’re just collecting surface answers, you risk missing the full story. Smart follow-up questions—automatically generated by AI—dig deeper, clarify meaning, and gather context. This is at the core of Specific’s automated follow-up technology, which works instantly as people respond. The system tailors each follow-up to the user’s last answer, like a skilled interviewer would.
User: “It just wasn’t working for me.”
AI follow-up: “Can you share what specifically felt off or what you hoped to achieve that didn’t happen?”
Without follow-ups, you get unclear, un-actionable responses. Automated probing saves hours of back-and-forth (email, calls), and helps users feel truly heard. The conversation feels natural and open—not like a rigid form.
How many follow-ups to ask? In most cases, two or three is best. This balances depth with respondent fatigue. You can configure Specific to automatically skip to the next question once you’ve collected what you need.
This makes it a conversational survey: Instead of one-way forms, the process feels like a friendly chat—resulting in richer, more candid insights from your users.
AI survey analysis, unstructured feedback, qualitative data: Even with lots of open-ended replies, you can analyze everything with AI. Group responses, identify themes, and get instant summaries—no spreadsheets required. Learn about AI survey response analysis.
Automated follow-ups are a new way to uncover what really matters—try generating your own AI survey and experience it firsthand.
How to compose prompts for generating great churn survey questions
Crafting the right AI prompt makes all the difference. Start simple, then add context. For example, just type:
Suggest 10 open-ended questions for user survey about churn reasons.
You’ll get better results if you add specifics—about your users, product, why you’re surveying, goals, etc. For example:
Our SaaS platform targets small businesses. We’ve noticed a 15% monthly churn over the last quarter. Suggest 10 open-ended questions to find the true reasons why users are leaving, and help us uncover needs our product might be missing.
Next, use AI’s categorization power:
Look at the questions and categorize them. Output categories with the questions under them.
Pick the themes you want to explore—maybe “feature gaps” or “customer support”—then prompt AI again:
Generate 10 questions for categories: Pricing, Support Experience, Product Fit.
This approach lets you quickly drill down, adapt, and build tailored churn surveys without getting stuck.
What is a conversational survey?
A conversational survey feels less like a form and more like a chat—guided by AI that adapts, asks smart follow-ups, and builds rapport. This is a leap beyond traditional, manual surveys, which often limit users to fixed answers and minimal context. An AI survey builder like Specific makes survey creation and respondent experience not only faster, but also richer in insight.
Manual surveys | AI-generated (Conversational) surveys |
|---|---|
Static, one-size-fits-all questions | Dynamically adapts with follow-up questions in real time |
Difficult to analyze open-ended feedback at scale | AI clusters and summarizes responses instantly |
High setup effort, prone to survey fatigue | Easy to create conversational AI survey, feels like a natural chat |
Why use AI for user surveys? Because every churn response holds hidden value—patterns to reduce loss, save cost, or improve the experience. The best AI survey examples let you get the full story, quickly analyze thousands of responses, and surface insights no spreadsheet could find. Plus, with Specific’s user-friendly flows, gathering actionable churn feedback is quick and intuitive—for both you and your users.
Specific’s conversational surveys are built for speed, engagement, and actionable insight—giving teams an edge in understanding churn that static surveys just can’t match.
See this churn reasons survey example now
Instantly launch a user churn survey that adapts, follows up intelligently, and analyzes results on autopilot—giving you deeper insight and faster action with every response. Don’t let user feedback slip through the cracks—try AI-powered churn surveys and see how effortless improvement can be.