Here are some of the best questions for a Fireside Chat Attendee survey about discussion topics, along with tips for crafting them. With Specific, you can build this type of survey in seconds using our AI-powered tools.
Best open-ended questions for Fireside Chat Attendee survey about discussion topics
Open-ended questions give us genuine feedback, helping reveal what attendees really think and feel. They're invaluable when we want depth—open responses can highlight new discussion angles or surface unexpected issues. Keep in mind that open-ended questions often come with higher nonresponse rates (up to 18% or even 50% in some studies), but respondents’ comments provide richer, actionable insights that management teams find extremely valuable. [1][2]
What discussion topic did you find most engaging during the fireside chat, and why?
Were there any topics you wish had been explored in more depth? Please elaborate.
Is there a discussion topic you feel was missing that should have been included?
What was your biggest takeaway from the discussion topics covered?
How did the chosen topics impact your perspective on the subject matter?
Can you share an example of how a discussion topic changed your thinking or approach?
What suggestions do you have for future discussion topics in upcoming fireside chats?
How relevant were the topics to your current challenges or interests?
In what ways did the discussion topics encourage audience participation or questions?
Do you have additional comments about the topics or the overall structure of the conversation?
Despite taking longer to analyze, open comments can be an absolute goldmine. With AI, we can now process and summarize these at scale for fast, actionable insights—without the manual slog. [3]
Best single-select multiple-choice questions for Fireside Chat Attendee survey about discussion topics
Single-select multiple-choice questions shine when we need clear, quantifiable data or want to kick off a focused conversation. They’re often easier for attendees to answer—sometimes a quick click opens the door for deeper discussion, especially when paired with follow-ups.
Question: Which discussion topic resonated with you the most?
Future trends in the industry
Leadership challenges
Innovation and technology
Audience Q&A
Other
Question: How relevant did you find the topics presented in this fireside chat?
Highly relevant
Somewhat relevant
Neutral
Not very relevant
Question: How likely are you to attend another fireside chat based on the topics covered?
Very likely
Somewhat likely
Not likely
When to followup with "why?" Follow up with "why?" whenever a multiple-choice response could mean many things. For example, if someone selects "Not very relevant," a quick "Can you tell us more about why the topics didn’t connect for you?" uncovers the real story. This transforms quick clicks into rich qualitative feedback.
When and why to add the "Other" choice? Always consider adding “Other” when you’re listing options—especially if your audience’s interests could be broader than you expect. People choosing "Other" are practically inviting you to learn something new, and a follow-up lets you capture that valuable input. That’s where real surprises (and insights) often surface.
Should you use a NPS question for Fireside Chat Attendee survey about discussion topics?
The Net Promoter Score (NPS) is a classic, reliable metric to measure overall satisfaction and the likelihood attendees will recommend your fireside chat to others. Especially in events, an NPS-style question helps gauge if your discussion topics are compelling enough for word-of-mouth buzz or return attendance. To try an NPS survey tailored to this purpose, check out our AI-powered NPS survey creator.
The power of follow-up questions
We’ve found that follow-up questions are where the magic happens. Instead of stopping with a basic answer, a smart follow-up unlocks deeper context and more thoughtful responses. That’s why at Specific, we built automated follow-up questions directly into the survey flow.
Attendee: “I didn’t get much out of the leadership challenges discussion.”
AI follow-up: “Could you share what would have made the leadership challenges topic more valuable for you?”
Just asking one more question like this helps us turn a vague response into something we can genuinely improve on.
How many followups to ask? Two to three follow-up questions are usually enough to get full context. It’s important to offer a “skip to next” option once the relevant information is collected. We’ve built this flexibility into Specific, so you stay in control without overwhelming your respondents.
This makes it a conversational survey. The follow-up system keeps the conversation flowing naturally, which makes the survey experience more engaging and human.
AI response analysis is easy. Even if you end up with hundreds of open-ended or follow-up responses, analyzing them isn’t a headache. Our platform offers AI-powered analysis that sorts, tags, and summarizes everything for you—no manual coding required.
These conversational follow-ups are something you really have to experience—use our AI survey builder to generate a custom survey and see the value firsthand.
How to use AI for fresh survey questions about fireside chats
ChatGPT or other GPT-based tools are awesome for brainstorming meaningful survey questions about discussion topics. Start simple if you want, but the more detail you give, the better the ideas you’ll get back.
For a quick start, try this:
Suggest 10 open-ended questions for Fireside Chat Attendee survey about Discussion Topics.
But if you add more context (your audience, goals, the fireside chat’s theme), you’ll get even richer, more relevant questions:
We just hosted a fireside chat for mid-career product managers focused on industry innovation and leadership. Our goal is to understand which discussion topics resonated, which were missing, and what would make future events more valuable. Suggest 10 open-ended questions for this scenario.
To group your brainstormed questions into themes—handy for building a logical survey:
Look at the questions and categorize them. Output categories with the questions under them.
Finally, drill down into specific themes you want to explore. For example:
Generate 10 questions for categories “innovation topics,” “leadership challenges,” and “future trends.”
What is a conversational survey?
Conversational surveys feel like an ongoing dialogue, not a cold checklist—respondents answer, the AI listens, then asks just the right follow-up. The feedback you get is richer, more nuanced, and feels less like a task for your audience.
Here’s how conversational AI surveys beat traditional manual surveys:
Manual Surveys | AI-Generated (Conversational) Surveys |
|---|---|
Static, one-size-fits-all questions | Dynamic, context-aware follow-ups for richer feedback |
Time-consuming to create and edit | Build or edit full surveys in minutes with an AI survey generator |
Responses often unclear or incomplete | AI probes deeper for clarity and actionable insights |
Manual data analysis required | Instant AI analysis and theme tagging for structured insights |
Why use AI for fireside chat attendee surveys? AI-driven conversational surveys keep the feedback loop open and natural—attendees are far more likely to share real thoughts and stick around to finish. This is especially true when our target is exploring complex discussion topics. Plus, it means you spend dramatically less time both building and analyzing your survey data. If you want to make the whole process smooth, take a look at our guide on how to create a survey with AI.
From my perspective, Specific offers one of the best, most seamless conversational survey experiences out there—both for creators who need rich insights, and for attendees who want to be heard without jumping through hoops.
See this discussion topics survey example now
Explore what an AI-powered conversational survey really feels like—fast, simple setup, rich follow-up logic, and effortless analysis you just can’t get with traditional forms. Make your next fireside chat feedback session smarter and more effective by starting with Specific.