This article will give you tips on how to analyze responses and data from an online event attendee survey about agenda preferences. If you want clear, actionable ideas from your survey, you’re in the right place.
Choosing the right tools for effective survey response analysis
How you approach analysis depends on the type and structure of the survey responses collected. Here's how to think about the right tools for the job:
Quantitative data: When your questions collect structured data (like rating scales, or counting how many attendees preferred certain tracks or session times), good old Excel or Google Sheets are hard to beat. These tools let you quickly sum choices, build charts, and reveal high-level trends.
Qualitative data: For open-ended questions—like “What topics would make you most excited to attend?” or “Why did you attend our last event?”—you’re swimming in unstructured text. Reading all the responses manually is nearly impossible at scale. AI tools shine here, summarizing themes and surfacing hidden insights far faster than any human could.
When dealing with qualitative responses, you have two main approaches for tooling:
ChatGPT or similar GPT tool for AI analysis
One DIY option: Copy your exported survey data (usually a CSV file) into ChatGPT, Claude, or another AI chatbot. Then, prompt the AI to analyze the responses. This strategy gets you started with the tools you have—but:
Downsides: It’s clunky for anything but small datasets, requires lots of copying and pasting, and you don’t get advanced filtering or context handling out of the box.
Still, it’s a low-barrier way to experiment if you only have a handful of open-ended responses and want a quick AI-powered overview.
All-in-one tool like Specific
Built for the job: Dedicated analysis platforms (like Specific, and others in the market) are designed especially for this use case—getting insights quickly from qualitative survey data. With Specific, you can:
Collect better data: The system asks clarifying follow-up questions in real time, improving the quality of responses right from the start. Learn more about automatic follow-up questions.
Instant AI-powered analysis: Results are instantly summarized, with themes and actionable insights surfaced without the need for spreadsheets or manual coding.
Conversational querying: Chat directly with the AI about your results, ask custom questions, and iterate quickly. Each chat conversation comes with strong data management and filtering features.
Other reputable tools in this space (like NVivo, MAXQDA, Delve, and Canvs AI) also leverage AI for theme identification, text analysis, and visualization for larger or more complex data sets [1].
Useful prompts that you can use to analyze online event attendee survey data about agenda preferences
Prompts shape how the AI interprets your data. Getting this right saves hours of frustration and gets you closer to the insights you need. Here are my go-to prompts for analyzing qualitative survey responses from online event attendees about agenda preferences:
Prompt for core ideas: Use when you want a quick summary of the key themes from your open-ended survey questions. This prompt is native in Specific, but also works in GPT tools like ChatGPT:
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 AI more context: Always inform the AI about your survey’s purpose, audience (event attendees), and any goals or important event details. For example:
This survey was filled out by people who attended our virtual conference last spring. The main goal is to learn what agenda topics, formats, and session timings best meet our audience’s needs for future events.
Drill down on a theme: If an idea emerges (like “networking opportunities”), just ask:
Tell me more about networking opportunities.
Check for specific topics: When you have a hypothesis—or a stakeholder asks if anyone mentioned panel discussions, for example—try:
Did anyone talk about panel discussions? Include quotes.
Personas: Use when you want to categorize respondents by their motivations and preferences for agenda planning.
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.
Pain points and challenges: Get a list of what’s not working for attendees.
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.
Motivations & drivers: If you want to understand why people want to attend (or don’t want to attend) certain sessions.
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.
Sentiment analysis: Discover if people feel excited, disappointed, or ambivalent about agenda proposals or past experiences.
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.
Suggestions, ideas, unmet needs: Find all actionable suggestions and missed opportunities directly from attendees.
Identify and list all suggestions, ideas, or requests provided by survey participants. Organize them by topic or frequency, and include direct quotes where relevant.
Examine the survey responses to uncover any unmet needs, gaps, or opportunities for improvement as highlighted by respondents.
If you want even more guidance on wording the right questions, check out this guide to the best open-ended questions for online event agenda preference surveys for inspiration.
How Specific summarizes survey data by question type
When analyzing qualitative data, the structure of your survey questions makes a big difference in how insights are reported (and how easy your analysis will be). Here’s how Specific handles these common question types for online event attendee agenda preference surveys:
Open-ended questions (with or without follow-ups): Specific automatically summarizes all responses—and any follow-up answers—grouped by the original question, so you instantly see broad trends and deeper explanations.
Choice questions with follow-ups: For questions like “Which session type do you prefer?” where there’s an optional follow-up (e.g., “Why did you choose that?”), you get a separate summary for every possible answer, giving you context for each choice.
NPS questions: When you measure Net Promoter Score, Specific summarizes the rationale for each group (detractors, passives, promoters) based on open-ended follow-ups. This gives you actionable insight into what makes some attendees huge fans while others are on the fence.
You can do the same thing in ChatGPT or other AI models, but you’ll be doing more manual filtering and data prep every step of the way.
How to tackle challenges with AI context limits for big event attendee surveys
Even with state-of-the-art AI, context size limits are a real challenge—when you’ve collected dozens or hundreds of survey responses, you can’t always “fit” all that data into a single AI conversation.
Filtering: Narrow down responses by individual questions or by specific attendee replies (“show me everyone who mentioned workshops” or “filter to people who answered the networking question”). Tools like Specific let you do this before sending data to AI, making analyses more manageable.
Cropping: Select a subset of questions for AI analysis at any given time. Instead of sending every response, focus on just the topics or questions you care about right now (“analyze only agenda-related feedback” or “look just at follow-ups to session timing”). This makes your data fit and ensures your AI stays focused.
Specific does both filtering and cropping out of the box, so you rarely run into the dreaded AI “context overflow” wall.
Collaborative features for analyzing online event attendee survey responses
Collaboration is usually the missing link when teams set out to analyze agenda preferences collected from event attendees. Coordinating input, clarifying follow-ups, and sharing discoveries is hard if everyone’s working from a single exported spreadsheet or siloed reports.
In Specific, collaboration is built-in: You and your team analyze survey data together by chatting with AI. You can open several AI chats on the same data set, filter them by question or attendee type, and clearly see who started and contributed to each conversation.
Multiple chat tracks: Each chat can investigate a different avenue—a deep dive on favorite session formats, another on suggestions, or one on feedback about speakers. Filters and context are distinct for each, and you always know who’s driving the conversation, thanks to clearly visible avatars.
All questions and perspectives on the table: This setup helps you quickly converge on attendee priorities, answer stakeholder questions (“Did anyone mention topic X?”), and ensures nobody’s insight gets lost in an endless comment thread or static one-off report.
Create your online event attendee survey about agenda preferences now
Start collecting and analyzing high-quality feedback today—create a survey tailored to your online event audience, enjoy instant AI-powered insights, and get the clarity you need to build agendas your attendees love.