Here are some of the best questions for a beta testers survey about bugs and issues, plus practical tips for creating them. We’ve seen how using a tool like Specific helps you build a survey in seconds—so your focus stays on what matters: actionable feedback from real users.
Best open-ended questions for beta testers survey about bugs and issues
Open-ended questions are essential when you need honest, detailed feedback on what’s not working—directly from your beta testers’ real-life experiences. These questions invite rich, specific insights that you’d never get with yes/no or checkbox formats. After all, context and nuance matter when you want to track down tricky bugs or UX hiccups.
The main advantage: open-ended questions allow testers to share unexpected pain points, patterns, and context—that’s your goldmine for prioritizing fixes and improvements. They work best early in a survey, or after quantitative check-ins, giving testers plenty of room to expand.
Here are our top 10 open-ended questions for a bugs and issues survey:
What bugs or issues did you encounter while using the app?
Can you describe the steps that led to any problem you found?
How did the bug impact your experience or workflow?
Were there any error messages, and if so, what did they say?
Did you find any issues that made you stop using a feature entirely?
Were there problems that seemed to happen only sometimes? Please describe when or how often you noticed them.
How easy or difficult was it to recover from an error or problem?
Did you try to find workarounds for any bugs? What did you do?
What would you expect to happen instead of what actually occurred?
Are there any additional technical or usability issues you haven’t mentioned yet?
Open-ended responses are messy—but gold for discovery. Platforms using AI to analyze survey responses can distill key insights and themes quickly, enhancing data quality by up to 40% with automatic detection and correction of inconsistencies. [2]
Best single-select multiple-choice questions for beta testers survey about bugs and issues
Single-select multiple-choice questions work best when you want to quantify experiences or quickly gauge the prevalence of specific bug types. They’re also perfect ice-breakers to guide deeper follow-up questions, especially when testers might not recall every detail off the bat. Sometimes, it’s simply easier for users to pick from a handful of clear options—and you maintain structure that’s easier to aggregate and report on.
Question: How often did you experience bugs or issues during your sessions?
Never
Rarely
Sometimes
Frequently
Every session
Question: Which area of the app did you notice the most issues?
Login/sign-up
Navigation/menu
Core features
Performance/speed
Other
Question: Did you report the bugs or issues you found?
Yes
No
I tried, but couldn’t
When to follow up with “why?” Single-select responses make it easy to spot trends (“performance issues” is a popular answer), but you get the juiciest insights when you follow up and ask why. For example, “You selected ‘Navigation/menu’—can you tell me more about the issue?” That’s when beta testers dive deeper, and your insight level jumps.
When and why to add the “Other” choice? Include “Other” when your predefined choices might not cover every possibility. It signals you’re listening and opens the door for feedback you hadn’t considered—then the follow-up, “What else did you experience?” helps reveal those unexpected patterns that elevate your product.
NPS question for bugs and issues surveys
NPS (Net Promoter Score) is a classic that works, even in a bugs-and-issues beta survey. It's simple: “On a scale from 0–10, how likely are you to recommend this product to a friend or colleague?” What makes NPS powerful here: it gives you a quick barometer on overall experience—even if there are bugs. If promoters outweigh detractors, your user base sees promise despite known issues. More importantly, NPS serves as a launchpad for qualitative follow-ups (“What one thing would improve your score?”). You can instantly add an NPS question with a single click.
The power of follow-up questions
Follow-up questions are what turn good surveys into great conversations. With automated AI follow-up questions, you never lose context or leave a bug report half-baked. The AI in Specific probes deeper in real time, just like a sharp product researcher, to clarify confusing responses or dig into “edge case” issues—so you don’t have to juggle endless email chains. Plus, with AI, you also avoid the problem of vague answers:
Beta tester: “The login sometimes doesn’t work.”
AI follow-up: “Can you tell me exactly what happens when the login fails? Is there an error message, or does nothing happen at all?”
How many follow-ups to ask? Usually, 2–3 is the sweet spot—enough to get the detail you need but not so many it turns into an interrogation. With Specific, you can set how deep you want to go, and the survey jumps to the next topic when you’ve got the info you need.
This makes it a conversational survey, not just a static form. It feels more natural, and testers are much more likely to share specifics that transform your understanding.
AI analysis of open-ended feedback: Don’t worry about being buried by pages of unstructured text—the AI survey response analysis features pull out the actionable insights fast, summarizing key themes and letting you dig deeper as needed.
These automated follow-ups are new for many—try generating a survey and see the richer insights in action.
How to prompt ChatGPT or other GPTs to generate great questions
If you want to use ChatGPT or another large language model to come up with targeted bugs and issues survey questions, start with this simple prompt:
Suggest 10 open-ended questions for Beta Testers survey about Bugs And Issues.
But you’ll get better results if you add more context about your product, your audience, and your goals. For example:
I am a product manager for a SaaS collaboration tool currently in closed beta. Our testers are mostly tech-savvy users who rely on integrations. Please suggest 10 open-ended questions to uncover bugs, workflow issues, and usability pain points related to integrations and new features.
Once you have a list, organize them using another prompt:
Look at the questions and categorize them. Output categories with the questions under them.
Pick the categories that matter most to your beta and then ask:
Generate 10 questions for categories “Integration issues” and “Feature usability.”
This technique makes it much easier to cover gaps and ensure you don’t miss vital domains of user feedback.
What is a conversational survey?
A conversational survey transforms feedback collection from checklist forms into a natural, chat-driven experience. Instead of asking everything all at once, the survey adapts dynamically—just like a real dialogue. It feels more human, and users are far less likely to abandon the process (conversational surveys can see completion rates up to 70–80%, compared to 45–50% for traditional formats [1]).
Here’s a quick look at the difference:
Manual Survey Creation | AI-Generated Chat Survey |
|---|---|
Manual question writing, error-prone setup | AI suggests relevant, expert-level questions in seconds |
No dynamic follow-ups, static pathways | Conversational, with smart follow-ups based on real answers |
Difficult to analyze open-text feedback | AI groups and summarizes themes for you |
Higher abandonment, less engagement | Mobile-friendly, natural interaction boosts completion rates |
Why use AI for beta testers surveys? Automated AI survey builders dramatically reduce the grunt work of survey design, boost response rates, and capture richer, more accurate data. Companies using AI survey generators report a 25% jump in customer satisfaction—and retention climbs too. [3] Surveys created this way don’t just deliver feedback, they help you act on what matters.
You can create a survey from scratch with Specific’s AI survey maker or use ready-made templates—either way, it’s all about making the experience smooth and meaningful for both beta testers and your team. The Specific platform’s conversational approach sets a new bar for engagement and actionable feedback, letting you surface what really matters.
See this bugs and issues survey example now
Get the questions and insights you need with a conversational AI survey that adapts in real time. Experience the difference—set up your beta testers survey in seconds with automated follow-ups and AI-powered analysis.