This article will give you tips on how to analyze responses from Conference Participants surveys about Preferred Location—using methods that actually work and tools that save time.
Choosing the right tools for analyzing survey responses
The approach you take—and what tool you use—depends completely on what your data looks like.
Quantitative data: Numbers and checkboxes (like "Which city would you prefer?") are fast to add up in Excel or Google Sheets. You can count, chart, and filter these options easily—perfect for quick stats, heatmaps, or simple comparisons.
Qualitative data: If you’ve got paragraphs of text, follow-up answers, or open-ended reasons why attendees want a specific location, you’re in the world of qualitative data. Manually reading every comment takes forever and you’ll hit bias problems. AI tools, on the other hand, surface trends and key points in a fraction of the time—especially when processing hundreds of conversations at once.
There are two approaches for tooling when dealing with qualitative responses:
ChatGPT or similar GPT tool for AI analysis
If you export all qualitative responses—say, everyone’s open-ended preferences—you can pop them into ChatGPT and start a conversation with AI.
Pros: You’re in control of the prompts. It’s fast for smaller sets of data.
Cons: For a big conference survey, copying and pasting hundreds of replies gets old quickly. Chat histories can become chaotic, and it’s easy to lose context, especially for multi-question surveys.
If you want to dig into all the follow-ups (the “why’s” behind choices), this workflow is clunky. Data management and accurate context become pain points.
All-in-one tool like Specific
Purpose-built for analysis: Specific lets you both collect and analyze survey data, so everything stays in one place. It’s built for chat-like, AI-driven surveys—which makes analysis seamless.
Deeper insights: As responses come in, Specific’s AI automatically asks smart follow-up questions, getting at the “why” behind each preference. This creates higher-quality data that’s more actionable and less generic. Curious? Here’s how automatic AI follow-up questions work and why they matter.
Instant, actionable outputs: The platform analyzes answers instantly—grouping core themes, key ideas, and suggested changes. It goes further than just summarizing: you can chat directly with the AI about your survey data, just like you would with ChatGPT but without losing track. Features for filtering, managing context, and key phrase extraction are built-in.
Want a starting point? You can use their AI survey generator specifically for conference location—it’ll save you from building a survey from scratch, and it’s optimized for exactly this scenario.
Useful prompts that you can use for Conference Participants preferred location surveys
When diving into qualitative data—especially hundreds of participant thoughts about venue and city—it pays to have AI prompts ready that bring out the signal from the noise. Here are a handful of tested prompts:
Prompt for core ideas: Best for finding recurring themes and the main reasoning in a big pile of conversational responses.
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
For better results, always tell the AI about your survey audience, context, and goals. The more background it has, the sharper its analysis becomes. For instance, try this prompt:
We conducted a survey with 300 conference participants to understand their preferred locations for upcoming events. Open-ended and multiple-choice data included the reasoning behind their choices. Please extract the main themes and any outliers.
Dive deeper on ideas. Use a prompt like:
“Tell me more about convenience of travel (core idea)” to get everything the AI can find about a specific theme.
Prompt for specific topic: Direct and great for quick checks.
“Did anyone talk about costs of accommodation?”
Tip: Add “Include quotes” to see which attendee said what.
Prompt for personas: Identify archetypes among your respondents—useful for grouping preferences:
“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:
“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 location preferences. Group similar motivations together and provide supporting evidence from the data.”
Prompt for sentiment analysis: Use this if you want a top-down read on how positive or uneasy people feel about different locations.
“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.”
Prompt for unmet needs & opportunities: Reveals what participants feel is missing or overlooked.
“Examine the survey responses to uncover any unmet needs, gaps, or opportunities for improvement as highlighted by respondents.”
Don’t hesitate to use combinations, or tweak prompts as you chat with your AI—especially when you want to chase down emerging themes.
How Specific analyzes qualitative data by question type
Specific breaks down analysis based on what you actually asked, making executive summaries dead easy. Here’s how:
Open-ended questions (with or without follow-ups): All responses (including those to follow-ups) to a question get a consolidated summary or theme extraction. You see both the big picture and nuanced reasoning in one go.
Choices with follow-ups: Say you have “Which city would you prefer?” and for each, a “Why?” follow-up. Specific summarizes all the “why” answers by choice—so you’ll know the top arguments for each location, not just a generic blob of feedback.
NPS (Net Promoter Score): For these, each category—detractors, passives, promoters—gets individual attention. Their follow-up answers are grouped and summarized, letting you address the unique “why” behind their scores.
You can achieve similar results in ChatGPT, but it’s a slog: you’ll be copying, pasting, and sorting, one group at a time. If you want this level of structure, a platform designed for survey response analysis is going to make your life much easier.
For more details, here’s a deep-dive on AI survey response analysis in Specific.
Navigating the context limit challenge in AI survey analysis
Here's where things can get hairy: most AIs, including ChatGPT, can only digest so much data at a time—usually a few thousand words. With hundreds of conference participant responses, you’ll hit that ceiling fast. Context limit is the enemy of big qualitative research.
Two smart workarounds (offered out-of-the-box by Specific):
Filtering: Instead of analyzing every response, just filter to those that matter most. For example: only attendees who mentioned “Europe”, or only those who gave detailed reasons for “other” choices.
Cropping: Only send the most relevant questions to the AI for a given analysis pass. This keeps the conversation about a key topic manageable, so you can get more insights from more conversations without running into data overload.
Both methods keep your analysis focused, actionable, and within the boundaries of what AI can actually handle.
Collaborative features for analyzing Conference Participants survey responses
Collaboration on analysis—which, let’s be honest, is where great events get planned—often gets bogged down by “who’s looking at what?” issues, version mismatches, and scattered feedback documents.
Chat-driven workflows: With Specific, you chat about data directly—no exporting required. Your team can each open their own chat sessions, ask different questions, and see the results instantly. It’s both powerful and transparent.
Multiple focused chats: Each chat lets you apply custom filters and analysis angles—like “Motivations for picking major cities,” or “Complaints about past locations.” This means a marketing lead can dig into big-picture trends while a logistics planner focuses on transport pain points. Each chat shows which teammate started it, so analysis can be handed off or picked up by others.
Track who said what: Messages in these chats are labeled with each contributor’s avatar, so cross-functional collaboration (marketing, logistics, leadership) comes together in one place. No more mystery spreadsheets or endless email threads.
Ready to go deeper? The AI survey editor is perfect for collaborative tweaks. And if you want to start a new survey from scratch, try the AI survey generator—it’ll walk you through everything.
Create your Conference Participants survey about preferred location now
Unlock real, actionable insights from your attendees and confidently plan your next event. Start discovering what truly matters to your conference participants and make your location strategy smarter than ever—don’t wait, create your survey today.