This article will give you tips on how to analyze responses and data from a User Roundtable Attendee survey about Discussion Topics, using effective survey response analysis tools and methods.
Choosing the right tools for survey response analysis
The approach and tools you need depend on the structure of your survey responses. Here’s how to break it down:
Quantitative data: Numbers and counts—like how many attendees selected a specific discussion topic—are straightforward. Tools like Excel or Google Sheets can quickly visualize this information with charts or pivot tables.
Qualitative data: Open-ended answers or responses to follow-up questions are rich in detail, but manually reading through dozens (or hundreds) of them isn’t practical. This is where AI-powered tools shine, efficiently distilling themes and summarizing feedback at scale.
There are two approaches for tooling when dealing with qualitative responses:
ChatGPT or similar GPT tool for AI analysis
Copy data and chat: You can export your survey responses and paste them into ChatGPT or another large language model.
Limitations: This method can feel clunky. Handling chunks of text, pasting, and keeping track of where you are is not very user-friendly. As surveys grow larger, you’ll probably hit the model’s context limit—resulting in missed insights or incomplete analysis.
Basic summaries: While GPT models can surface patterns, those using traditional AI chat tools need to manage prompt design, manual data filtering, and verifying that privacy or sensitivity concerns are addressed. There’s a lot of context switching.
All-in-one tool like Specific
Purpose-built for survey analysis: Tools such as Specific are designed to both collect conversational survey data from roundtable attendees and deliver instant, AI-powered analysis—no copying and pasting required.
Smart follow-ups: Unlike static forms, Specific automatically asks relevant follow-up questions during the survey, yielding higher quality data that captures the “why” behind each participant’s responses. (learn more about automatic follow-up questions)
Instant insights & chat-based analysis: After collecting responses, Specific’s AI groups answers into key topics and core themes, summarizes sentiment, and even highlights outlier feedback. You can chat interactively with the results, clarify findings, or filter by conversation topics—all within the same survey workspace. That dramatically reduces the time and manual effort compared to legacy approaches—some studies estimate up to a 90% reduction in analysis time with AI-driven tools. [3]
Control and collaboration: Specific gives you tools to manage, edit, and refine the data you send to AI for analysis. Filters, chat history, and feedback management provide more control than simply pasting everything into ChatGPT.
If you want to create new surveys or try ready-made question sets, the AI survey generator for User Roundtable Attendee Discussion Topics is worth checking out.
Useful prompts that you can use for User Roundtable Attendee Discussion Topics survey response analysis
AI tools work best with clear, specific prompts. Here are prompt ideas and quick explanations of how to use them with your data (in ChatGPT, Specific, or similar):
Prompt for core ideas: This prompt extracts the main topics and themes across all responses—the same format Specific relies on internally. Paste your data, then use:
Your task is to extract core ideas in bold (4-5 words per core idea) + up to 2 sentence long explainer.
Output requirements:
- Avoid unnecessary details
- Specify how many people mentioned specific core idea (use numbers, not words), most mentioned on top
- no suggestions
- no indications
Example output:
1. **Core idea text:** explainer text
2. **Core idea text:** explainer text
3. **Core idea text:** explainer text
AI delivers better results when you supply extra context—such as your survey’s purpose or what you want to learn. For example:
My goal is to understand what topics drive the most engagement among User Roundtable Attendees. Please extract not just what topics were mentioned, but which themes surface repeatedly and seem most meaningful to participants.
Drill deeper on a single theme: Once you have core ideas, you can dig in—for instance: “Tell me more about breakout session feedback” or any topic you want to investigate further.
Prompt for a specific topic: Did anyone mention a particular issue or idea? Just prompt:
Did anyone talk about [specific topic]? Include quotes.
Prompt for personas: To develop an understanding of different attendee types:
Based on the survey responses, identify and describe a list of distinct personas—similar to how "personas" are used in product management. For each persona, summarize their key characteristics, motivations, goals, and any relevant quotes or patterns observed in the conversations.
Prompt for pain points and challenges: To find what might be holding people back or frustrating them:
Analyze the survey responses and list the most common pain points, frustrations, or challenges mentioned. Summarize each, and note any patterns or frequency of occurrence.
Prompt for motivations & drivers:
From the survey conversations, extract the primary motivations, desires, or reasons participants express for their behaviors or choices. Group similar motivations together and provide supporting evidence from the data.
Prompt for sentiment analysis: This is especially helpful using NLP models purpose-built for sentiment scoring, which have up to 95% accuracy for English-language text. [9]
Assess the overall sentiment expressed in the survey responses (e.g., positive, negative, neutral). Highlight key phrases or feedback that contribute to each sentiment category.
Prompt for suggestions & ideas:
Identify and list all suggestions, ideas, or requests provided by survey participants. Organize them by topic or frequency, and include direct quotes where relevant.
You can find more advice on what questions to ask and prompt presets over in the guide to best questions for User Roundtable Attendee Discussion Topics surveys.
How Specific analyzes qualitative survey data, by question type
Different question types require distinct analysis approaches to generate actionable insights:
Open-ended questions (with or without follow-ups): Specific automatically summarizes all responses for a given question. If you included follow-up probes, those responses are grouped and summarized by type, giving a nuanced read of what participants shared.
Choices with follow-ups: For each answer, Specific presents a separate summary covering the feedback and explanations provided for that answer—making it easy to see, say, what drove attendees to select certain discussion topics.
NPS: Responses are summarized and grouped into promoters, passives, and detractors. For each group, Specific highlights the main themes and concerns behind their scores—critical for action-oriented decision making.
You can replicate these summaries in ChatGPT, but this usually means copy-pasting, manual prompt-writing, and reviewing outputs for each individual question or grouping. Using a platform built for this job is simply more efficient.
If you want to see how it works in practice, here’s a walkthrough on how to create and analyze a discussion topics survey for roundtable attendees.
Dealing with AI context limits in survey analysis
All AI tools have a hard limit (the “context window”) on how much data you can analyze at once. For large surveys where responses won’t fit in a single session, consider these strategies—both available in Specific:
Filtering: Narrow down the dataset. You might want to analyze only participants who engaged with a particular topic, or only those who gave long-form feedback. Filtering ensures the AI focuses on your most relevant conversations.
Cropping questions: Instead of analyzing full conversations, you can send only the key questions—and their responses—to the AI. This keeps the input within the allowed size, prioritizing depth on your priority topics.
By combining filtering and cropping, you maximize the insight you can get from even the largest events or surveys—without manual data splitting or random sample loss. This approach reflects best practices for AI-powered survey analysis and is built into Specific’s workflow.
It’s also worth noting that organizations implementing AI survey tools see a massive reduction—up to 70%—in total time spent from survey creation to insights. [7]
Collaborative features for analyzing User Roundtable Attendee survey responses
Analyzing survey feedback is rarely a one-person job. For roundtable events or group discussion surveys, keeping everyone on the same page—especially in remote or cross-functional teams—can be surprisingly tough.
Integrated team collaboration: Specific lets anyone on your team join an AI chat about the results. Multiple ongoing chats, each focused on a different aspect—like session topics, feedback on speakers, or network opportunities—help you cover more ground, faster.
Personalized workspaces: Each chat can have its own filters and can show who started which line of questioning. This means people can specialize (e.g., product team dives into feature topics, while the events crew reviews logistics) while seeing all insights in one place.
Visibility & transparency: You always know who said what. With user avatars in every chat message, it becomes simple to track input and prevent duplicate work or missed findings.
Frictionless sharing: Teams can easily share findings, flag important quotes, or assign follow-up work directly within Specific—and since everything happens in a single space, context switching is reduced to zero.
If you’re interested in building your own collaborative workspace, explore the AI response analysis features in Specific or try out the AI survey generator for a custom survey workflow.
Create your User Roundtable Attendee survey about Discussion Topics now
Start analyzing feedback in minutes, uncover the key themes driving your roundtable discussions, and use AI to turn every participant’s voice into actionable insights—instantly and collaboratively.