This article will give you tips on how to analyze responses from an online event attendee survey about discussion topics using AI—so you get real insights from both numbers and nuanced, conversational feedback.
Choosing the right tools for analyzing your survey data
The approach you’ll take, and the software you’ll need, depends on the type of answers you collect from your online event attendees about discussion topics.
Quantitative data: If you’re dealing with straightforward questions—like "Which discussion topic are you most interested in?"—these are easy to analyze with tools like Excel or Google Sheets. You can quickly tally how many attendees chose each option, run simple charts, and spot trends by the numbers.
Qualitative data: Open-ended questions (for example, “What would you like to discuss in depth?”) create rich, nuanced data that’s impossible to comb through manually at scale. Even just 50 attendees means 50 unique stories. For this, using AI-powered tools isn’t just a luxury—it’s a necessity. AI reduces the risk of human bias and fatigue, providing more thorough, real-time insights. In fact, the integration of AI and natural language processing (NLP) is changing the game for survey analysis, letting you capture deeper sentiments fast [1].
There are two approaches for tooling when dealing with qualitative responses:
ChatGPT or similar GPT tool for AI analysis
Copy, paste, and chat: You can export your qualitative responses into a spreadsheet and paste them into ChatGPT (or similar tools). Then, you’ll chat with the AI to analyze themes or summarize what people said.
What you gain: Flexibility and access to cutting-edge large language models (LLMs). But—copy-pasting gets tedious fast, and it’s easy to lose track of context with longer surveys or messy data formats.
Context management is manual: You’ll have to keep conversations organized, manage how much data you paste (there are context size limits), and possibly break up big data sets.
All-in-one tool like Specific
Purpose-built for survey analysis: Specific is designed specifically to collect, manage, and analyze both quantitative and qualitative survey data using state-of-the-art AI. You can launch a conversational survey and immediately analyze results in the same workspace—no spreadsheets needed.
Better data, better insights: The platform asks smart, AI-powered follow-up questions as attendees complete the survey. This improves both the depth and quality of your data automatically. (See more about how automatic follow-up questions work.)
Instant summaries and deep dives: Once responses arrive, AI distills key themes, summarizes individual and group answers, and surfaces actionable findings—letting you discover what actually matters to your attendees, right away.
Conversational analytics: You can chat directly with the AI about your survey results, ask follow-up prompts, and manage which data gets included in each query. There’s no more endless cutting, pasting, or switching tools—analysis is truly interactive.
If you want a more hands-on approach or to explore prompt-driven survey creation, check out the AI survey generator for online event attendees or visit the main AI survey generator page for fully custom surveys from scratch.
Useful prompts that you can use for online event attendee survey analysis
Whether you’re using ChatGPT or a tool like Specific, prompts are your secret weapon for making sense of qualitative survey data about discussion topics.
Prompt for core ideas: This is a foundational, Specific-proven prompt that works brilliantly for extracting summary themes from large response datasets:
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
Give more context for even better results: Always add specific details about your survey or event, like this:
This is a pre-event survey for our annual virtual summit. Attendees are mostly software engineers and product managers. Our goal is to discover which discussion topics resonate most, and collect any suggestions for the agenda. Extract themes and explanations accordingly.
Prompt for deeper dives: To explore a specific idea, use:
Tell me more about XYZ (core idea).
This lets the AI find all related subtopics, nuances, and attendee quotes about that theme.
Prompt for specific topic mentions: Want to check if anyone mentioned a particular subject, and get actual participant quotes? Try:
Did anyone talk about [keyword]? Include quotes.
Prompt for personas: Segment your audience based on interests or backgrounds, which is especially useful for events with a diverse attendee base:
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: Identify what your attendees struggle with the most when it comes to discussion topics or event agendas:
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: Uncover what’s really fueling people to join certain discussions:
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 suggestions and ideas: If you want your discussion topics to be truly attendee-driven, let AI pull out every suggestion or creative idea:
Identify and list all suggestions, ideas, or requests provided by survey participants. Organize them by topic or frequency, and include direct quotes where relevant.
Want a deep dive on question writing? Browse best questions for online event attendee survey about discussion topics for inspiration.
How Specific handles qualitative data based on each question type
Specific automatically sorts and analyzes qualitative survey data in ways that align with the type of question you ask.
Open-ended questions with or without follow-ups: For each open question, you get a summary of all responses plus a synthesis of any AI-generated follow-up conversations. This is perfect for discovering unexpected topics or deeper attendee needs.
Multiple-choice with follow-ups: Every selected option receives a dedicated summary of the related follow-up answers. So, if someone picks “Networking Opportunities” and gets a tailored follow-up, Specific keeps that thread organized, making it easy to see what motivates each segment of your attendees.
NPS (Net Promoter Score) with follow-ups: Each NPS category—detractors, passives, and promoters—gets its own summary of the underlying reasons, as voiced in the follow-up questions. It’s a shortcut to knowing what drives positive or negative sentiment.
You can achieve something similar in ChatGPT, but it’s manual work to break data apart, paste into multiple threads, and organize your findings. Specific does it for you—no wrangling required. To see NPS in action, check out this NPS survey builder for online event attendees.
How to tackle challenges with AI context size limits
Large surveys often exceed the context limit of GPT-style AIs—meaning you can’t analyze all responses at once. Even the best LLMs have a maximum number of tokens (words and punctuation) they can process in a single prompt. Specific tackles this in two ways:
Filtering: You can filter conversations to only the respondents who answered certain questions or gave specific responses. For example, analyze only attendees who mentioned "panel discussions" or only those who replied to a question about networking.
Cropping: Limit which survey questions go into the AI analysis. Instead of sending the full dataset, just select the questions you really want to explore by theme, keeping within the LLM’s processing window and focusing AI's attention on the areas that matter most.
Both methods let you get more data analyzed, spot granular trends, and make sure context size doesn’t stop your analysis from scaling with your event.
Collaborative features for analyzing online event attendee survey responses
When teams analyze surveys about discussion topics for online event attendees, aligning on insights can be tough—especially when wrangling files, comments, or separate analysis threads across different tools and time zones.
Collaboration made streamlined: In Specific, you work together by chatting with AI about survey data. Every chat can take a different angle: one chat for agenda suggestions, another for content sentiment, and another for segment-specific feedback.
See who’s driving insights: Each chat shows the avatar of its creator—so it’s always clear who’s working on what. If a colleague wants to analyze only those who requested networking topics, they can create a filtered chat just for that segment. You can jump between chats and viewpoints seamlessly.
Chatlog transparency: When collaborating, every message logs who said what—so ideas, edits, and findings are always attributable and easy to follow. No more lost comments or scrambled analysis.
If you want to design a survey together before analysis, try the conversational AI survey editor, which lets teams craft questions simply by describing them in plain language.
Create your online event attendee survey about discussion topics now
Start capturing actionable insights from your event audience in minutes—get deeper feedback, instant AI-powered analysis, and all the tools you need to make your event discussion topics truly attendee-driven.