This article will give you tips on how to analyze responses from a citizen survey about tourism experience using AI and smart methodologies.
Choosing the right tools for analysis
When you want to analyze survey data, pick your approach and tools based on the type and form of the responses you collected. Here’s how I think about it:
Quantitative data: If you have structured data—think ratings, multiple choice, or any countable answers—Excel or Google Sheets are perfect. Counting, averaging, or even making quick pivot tables is easy, and it’s often all you need.
Qualitative data: If your survey includes open-ended questions, things get fuzzier. Reading a handful of responses works, but once you hit a few dozen or hundreds, it’s a hopeless slog. AI tools are the only practical way to make sense of rich qualitative feedback at scale—especially when you want to catch the nuance in people’s stories about tourism experience.
There are two approaches for tooling when dealing with qualitative responses:
ChatGPT or similar GPT tool for AI analysis
Copy-paste and chat: Export your data from the survey tool and paste it into ChatGPT or another large language model. You can start chatting with the AI to extract insights, spot themes, or summarize pros and cons.
Drawbacks: This method gets tedious quickly if you’re handling lots of responses or want to analyze multiple questions. ChatGPT doesn’t structure responses by question or tie follow-up answers to parent questions. If your data’s messy or you want to repeat analysis with fresh data, you’re back to square one.
Still, for small datasets or quick-and-dirty analysis, it works reasonably well.
All-in-one tool like Specific
Built for surveys from the ground up: Tools like Specific come with survey design, automatic follow-up questions, and purpose-built analysis. You collect data in chat-like surveys and get instant AI insights—no need for spreadsheet exports or manual work.
Quality boost from follow-up questions: These platforms don’t just gather answers; they ask smart, real-time follow-ups, so you get deep context and well-explored responses (see automatic AI follow-up questions for more about why this matters). I’ve seen that better follow-ups directly translate to richer findings.
Instant, interactive insights: Specific summarizes answers, clusters core ideas, and lets you chat with the AI about your results—just like ChatGPT, but wired into your survey’s full context. You can even choose what parts of each response or survey run through the AI, making it easy to focus on what actually matters and avoid the clutter.
If you want control, speed, and quality in one package, these dedicated platforms are a huge step up.
Useful prompts that you can use to analyze citizen tourism experience survey responses
When you want to dig deeper—especially into open-ended survey responses—knowing exactly what to ask the AI is powerful. Here are prompts that consistently deliver insights, drawn from best practices working with citizens and tourism data. Use these whether you’re in ChatGPT, Specific, or another tool.
Prompt for core ideas: Perfect for surfacing top themes and patterns across hundreds of free-text answers. This is also the starting point I use in Specific and it works anywhere GPT-like models are used.
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
Add context for better AI results: AI always gets smarter if you share more background. For example:
This survey was answered by local residents about their experiences with tourism in our city. Our goal is to identify improvement opportunities in city planning and visitor services. Summarize the main topics discussed.
Dive deeper on hot topics: If something interesting pops up, just follow up with
“Tell me more about [core idea]”
This pulls out deeper subtopics, quotes, and data clusters.
Validate concerns with a specific topic prompt: To quickly check if citizens mentioned a particular issue, ask:
Did anyone talk about [specific issue]? Include quotes.
Find personas based on survey responses: Want to understand the different mindsets or types among your respondents? Use:
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.
Uncover pain points and challenges: To surface what frustrates or blocks local citizens or tourists, try:
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: To get at why people act or feel as they do:
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: If you need a quick read on mood, try:
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.
Collect suggestions & ideas: For inspiration or practical fixes, use:
Identify and list all suggestions, ideas, or requests provided by survey participants. Organize them by topic or frequency, and include direct quotes where relevant.
Spot unmet needs and opportunities: To find what’s missing:
Examine the survey responses to uncover any unmet needs, gaps, or opportunities for improvement as highlighted by respondents.
If you want more ideas on crafting great citizen survey questions, check out this article on best questions for citizen tourism experience surveys. And for step-by-step workflow tips, see how to create a citizen survey about tourism experience.
How Specific analyzes qualitative data based on question type
AI tools like Specific structure their analysis differently depending on the type of survey question. This structured approach means you get actionable summaries tied to what’s actually being asked, not just a soup of random comments:
Open-ended questions (with or without follow-ups): You’ll get a single summary that includes both people’s initial responses and any follow-up answers that relate to the question. This gives you a well-rounded view of what’s being said and the extra detail the AI explored.
Choices with follow-ups: Every choice people pick (e.g., “favorite aspect of city tourism”) can have its own set of AI-powered summaries for the open-text follow-up answers. This makes it easy to see how sentiment or feedback varies by choice.
NPS (Net Promoter Score): For those running citizen NPS surveys on tourism experience, each group—detractors, passives, promoters—gets a dedicated qualitative summary of their comments. It’s a powerful way to see what sets these groups apart.
You can try an NPS survey tailored for citizens and tourism instantly in Specific.
You can break your data down the same way in ChatGPT, but expect more setup and manual work to keep things organized.
For more details about AI-powered response analysis, check out how survey response analysis works in Specific.
How to tackle challenges with AI’s context limits
One thing I run into with AI analysis is context size limits: if your citizen survey about tourism gets hundreds of detailed responses, even advanced AI models can hit a wall. If your data doesn’t fit, the AI gets confused or drops responses.
Filtering: The solution is to narrow the scope. You can filter responses to only those where people replied to a certain question or chose a certain answer. This keeps the analysis relevant and inside the AI’s processing window.
Cropping: Alternatively, you can crop—tell the AI to just review responses to selected questions, skipping others. This is perfect when you want to dig into one issue at a time or keep your dataset tight.
In Specific, both methods are integrated: You can apply these filters or cropping tools instantly from the dashboard, no need to wrangle your data offline.
If you’re curious to see how context management works in Specific, take a look at AI survey response analysis in Specific.
Collaborative features for analyzing citizen survey responses
Group efforts made easy: Analyzing citizen tourism experience surveys can get messy fast when teams work together—duplicate work, uncertainty about who’s looking at what, and info getting lost.
Chat-driven team insights: In Specific, collaboration is baked into the process. Anyone can analyze survey data simply by chatting with AI. These chats—each acting like a mini research notebook—have filters, labels, and clear attribution to the teammate who started them.
Multiple chats for multiple topics: Need to break up analysis—one chat focused on local infrastructure feedback, another on tourist satisfaction, maybe another just for negative responses? You can run as many as you want in parallel. It’s obvious at a glance who’s analyzing what, and which filter or question set each chat is working on.
Clear identification: Every message inside AI chat shows the sender’s avatar, making it easy for everyone to see feedback, add new prompts, or track what’s already been discovered. I find this is a huge time saver and helps avoid double work.
For even more control, you can customize and edit your surveys using Specific’s AI survey editor, or generate a new citizen tourism experience survey on the fly.
Create your citizen survey about tourism experience now
Uncover what matters most to your community—launch a citizen tourism experience survey and analyze responses instantly with AI-powered insights. Start now for deep context, actionable findings, and a smarter, more collaborative workflow.