This article will give you tips on how to analyze responses from a hotel guest survey about spa experience. AI survey response analysis can help you extract meaningful insights from both quantitative and qualitative feedback.
Choosing the right tools for hotel guest spa survey analysis
The best approach for analyzing your survey data depends on the form and structure of your responses. Here’s what that means in practice:
Quantitative data: If you’ve asked your hotel guests to rate aspects of the spa on a scale or pick from preset options, you can summarize responses easily using tools like Excel or Google Sheets. You’ll see, for example, how many guests selected each option or how NPS scores stack up.
Qualitative data: For open-ended responses or detailed follow-ups, manual review isn’t scalable. Imagine reading hundreds of guests’ personal stories about their spa experience—you’d miss patterns, and it would take hours. This is where AI-driven tools start to make a real difference, surfacing key themes and insights from a flood of rich feedback.
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 open-ended survey results as text and paste them into ChatGPT or another large language model. You can use custom prompts to summarize feedback or extract themes. This works—and is cost effective—but can be messy if your dataset is even moderately large.
Limitations: You have to handle exports and imports, watch out for AI’s context window (more on that below), and keep track of your own filter logic. It’s more manual than a purpose-built tool.
Still, if you’re just testing the waters or have a tiny dataset, it’s perfectly valid. And with the right prompts, you’ll get surprisingly high-quality analysis (see the next section for prompt ideas).
All-in-one tool like Specific
Purpose-built for user feedback: Tools like Specific are designed to both collect and analyze survey responses from start to finish. Instead of juggling spreadsheets and ChatGPT windows, all your guest feedback lives in one place. When you create your spa survey in Specific, you can use features like automatic AI follow-up questions to boost the depth and quality of responses.
Instant AI summaries and chat: The platform then uses AI to instantly summarize qualitative feedback, highlight recurring spa themes, and turn findings into actionable insights without tedious exports or long manual coding sessions. You can chat about the results—just like you would in ChatGPT—but you benefit from data organization features, filters, and tracking of your analysis threads.
Visual anchors and workflow: It’s built for teams who want to move quickly, and keeps everything connected (survey, data collection, and analysis) under one roof, which saves a huge amount of setup and context-juggling.
Bonus: Dedicated qualitative analysis platforms like MAXQDA and Atlas.ti are also popular for in-depth research[1], but for hotel guest feedback, all-in-one survey tools with AI analysis are much easier to manage—especially if your resources are limited.
Useful prompts that you can use for analyzing hotel guest spa experience survey data
Whether you’re using ChatGPT or a tool like Specific to analyze qualitative data, well-crafted prompts help you extract clarity from a sea of feedback. Here are some tried-and-tested prompt ideas, tailored for hotel guest spa surveys.
Prompt for core ideas: This prompt works for finding the main reasons guests mention when evaluating their spa experience:
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 always gets better when you give it more background—for example, your overall goal, hotel type, or guest demographic. Combine explicit context with the prompt, like this:
I conducted a survey with hotel guests about their experience at our spa. The guests are mostly business travelers and families. I want to understand what matters most to them about the spa and where we can improve. Here’s a sample of their open-ended responses:
[PASTE RESPONSES HERE]
Drill-down prompt: After getting the core themes, use: Tell me more about spa staff friendliness (core idea) to reveal supporting details and example quotes.
Prompt for specific topic: To check if anyone highlighted a certain aspect—let’s say, “quiet relaxation areas”—use: Did anyone talk about quiet relaxation areas? Include quotes.
Prompt for pain points and challenges: Get a distilled list of negative feedback or friction points by asking:
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 sentiment analysis: For a quick read on overall vibe, 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.
Prompt for suggestions & ideas: Gather direct guest input for improvements:
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 personas: Understand your segments with:
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.
Want more survey and prompt tips? Check out this guide on best questions for hotel guest surveys about spa experience.
How Specific analyzes qualitative survey data by question type
You don’t need to settle for a single, one-size-fits-all analysis. Specific adapts based on how you designed your hotel guest survey:
Open-ended questions (with or without followups): You’ll get a clear summary highlighting the most frequent guest opinions and themes. If your follow-ups drilled down on certain topics—like “Tell me more about the therapist’s expertise”—those responses are summarized in context too.
Choices with followups: If you included options (“Which spa service did you use?”) and attached follow-up questions (“What stood out most?”), Specific delivers separate analysis for each choice, so you can compare, say, massages versus facials.
NPS questions: For guest Net Promoter Score, the AI sorts responses into promoters, passives, and detractors—then delivers rapid-fire qualitative analysis for each camp, so you see what’s driving praise or complaints.
With ChatGPT and exports, you can do this manually by filtering responses and pasting them question-by-question. It’s doable, but not nearly as smooth as having all summaries generated and sorted for you.
For more details, check out the full rundown of AI-powered survey response analysis in Specific.
How to handle context size limits when analyzing survey responses with AI
Large survey datasets come with a hidden challenge: AI models can only consider a limited number of guest conversations (“context window”) at once—whether you use ChatGPT or a survey analysis tool. If you try to cram in too much at once, you’ll get truncated or missing analysis.
Here are two strategies—both built into Specific—that make large-scale analysis possible:
Filtering: Apply filters so the AI only analyzes conversations where guests replied to certain questions or selected specific spa services. This keeps things focused and efficient.
Cropping: Select only the most relevant questions (like your open-ended or follow-up items) to send into the AI, leaving out the rest. This squeezes more meaningful insights out of your AI’s attention span.
It’s the difference between overload and getting a crisp set of themes and stats from your spa survey.
Collaborative features for analyzing hotel guest survey responses
Hotels and spa managers rarely analyze survey results in isolation—there’s usually a team needing input. But if you’re stuck sharing unstructured data files or trading ChatGPT transcripts, it’s easy to lose track of who found which insight, or which angle’s already been explored.
Chat with AI—and your team—in one place: In Specific, you (and anyone else on the team) can analyze survey responses just by chatting with the AI, right inside the platform. This means no switching tabs or exporting snippets.
Multiple parallel analysis threads: Open as many chat-based analyses as you want. Each thread can have different team members, filters (for example, analyzing only guests who booked a certain spa package), and discussion points. Every chat shows the creator—so you can see whether the spa director, marketing manager, or guest experience lead launched a particular line of inquiry.
Team transparency: Every message within the AI’s analysis chat is tagged with the sender’s avatar, making it straightforward to follow who contributed which insight. This makes collaborative analysis simple, traceable, and scalable—even if your guest survey team is spread out across locations.
For end-to-end spa survey analysis—without spreadsheets or chaos—having these features is a huge unlock.
Create your hotel guest survey about spa experience now
Start gathering actionable feedback in minutes and discover what truly matters to your guests. Use AI-driven analysis to save time, uncover actionable insights, and deliver a better spa experience in your hotel today.