This article will give you tips on how to analyze responses from a hotel guest survey about problem resolution using AI and the latest survey response analysis tools.
Choosing the right tools for analysis
Your approach for analyzing hotel guest survey responses about problem resolution depends on the structure of your data. Here’s how different data types call for different tools:
Quantitative data: For structured data, like the percentage of guests dissatisfied with their stay, Excel or Google Sheets work well. You can easily count, visualize, and chart these results.
Qualitative data: For open-ended answers (for example, “Describe an issue you experienced during your stay”), reading each response one by one isn’t practical. With qualitative data sets, especially large ones, you’ll want to lean on AI tools to sort through responses and surface actionable insights.
There are two approaches for tooling when dealing with qualitative responses:
ChatGPT or similar GPT tool for AI analysis
Export and copy your data into ChatGPT: This method works if your data set is small enough to fit into a single prompt. Just paste your responses and chat about them with AI.
Not very convenient: You’ll quickly hit context limits with longer surveys. Formatting data for each run, keeping track of answers, and ensuring you don’t lose important context can be tedious.
All-in-one tool like Specific
Purpose-built AI for survey analysis: Specific is designed for feedback-driven teams. It not only collects survey responses in a natural, conversational flow, but also uses AI to analyze qualitative feedback—extracting key themes and summarizing conversations without manual effort.
Follow-up questions boost quality: When guests answer a survey built with Specific, the AI asks intelligent follow-ups, so you get more detailed problem descriptions. Learn more about how automatic AI follow-up questions increase data quality.
Instant AI summaries and insights: With built-in AI survey response analysis, your results are summarized, categorized by theme, and instantly available for exploration. No spreadsheets, no exporting—just clear, actionable findings. You can also chat with the results, much like in ChatGPT, but with filters and context tailored for survey work.
Useful prompts that you can use to analyze hotel guest survey responses about problem resolution
Strong survey analysis starts with good prompts. Here are my favorite ways to get quick but deep insight from hotel guest survey data:
Prompt for core ideas: If you need a concise list of the main issues or themes, use the same prompt that Specific uses to instantly summarize large text sets:
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
Tip: AI performs better if you give it extra context about your hotel, guest profile, or resolution goals. For example:
This feedback is from guests who recently stayed in a city-center business hotel. Our goal is to quickly resolve problems and increase guest loyalty. Use this information to prioritize issues that impact business travelers most.
Prompt for digging deeper: If you see a recurring theme, ask, “Tell me more about XYZ (core idea).”
Prompt for specific topic: Want to know if Wi-Fi came up as an issue? Try, “Did anyone talk about Wi-Fi? Include quotes.”
Prompt for pain points and challenges: Get a clear, organized list of frustrations 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: To gauge whether feedback trends positive or negative:
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: Uncover actionable guest suggestions by prompting:
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: To find where your team can improve guest experience:
Examine the survey responses to uncover any unmet needs, gaps, or opportunities for improvement as highlighted by respondents.
If you’re building your first survey, check our guide on the best questions for a hotel guest survey about problem resolution or try our survey generator with relevant prompts preloaded.
How Specific analyzes qualitative data based on question type
Getting a high level summary is great, but sometimes you want to dive deep into specific answer types. Specific structures its analysis like this:
Open-ended questions (with or without follow-ups): You get a summary of all responses, including the follow-up details related to each answer. This makes it easier to see context behind each complaint or piece of praise.
Choices with follow-ups: Each choice gets its own summary of every follow-up, so you can see why guests felt a certain way.
NPS survey questions: Specific separates its analysis by group—detractors, passives, and promoters. You see individual summaries for what prompted each NPS score, so it’s easy to target improvements.
You can perform similar breakouts using ChatGPT, but it takes more manual steps for sorting and summary work.
How to tackle challenges with AI context limit
Every AI tool has context size limits—if your survey has hundreds of hotel guest responses, you won’t be able to process them in one go with basic tools like ChatGPT. Here’s how I recommend getting around that:
Filtering: Only analyze survey conversations where guests replied to specific questions or reported certain problems. This keeps your focus narrow, so AI can handle the data.
Cropping: Instead of sending every question in your survey for analysis, pick only the most relevant ones (e.g., all answers to “Describe the issue we resolved”). This way, AI stays within technical limits and your insights stay focused on actionable details.
Specific offers both strategies out of the box, so big data sets aren’t a blocker.
Collaborative features for analyzing hotel guest survey responses
It's common for hotel management teams to analyze guest service feedback together, but collaborating in spreadsheets or text docs quickly gets overwhelming, especially with qualitative responses about problem resolution.
Analyze data together in AI Chat: In Specific, you can chat with AI about your responses, just like with ChatGPT, but designed for team work. Multiple users can spin up their own chats, each with custom filters or focus topics—like Wi-Fi complaints, or NPS analysis.
Multiple chats, each with owner visible: Every chat has a visible creator and can be filtered independently. No mix-ups, overlaps, or duplicated work. This streamlines collaboration—even across departments like operations and guest relations.
See who said what in chat: In team analysis sessions, each message clearly shows who’s speaking. Put simply, collaborating on hotel guest survey analysis turns from chaos to clarity.
Want to master collaboration for hotel guest survey analysis? Learn more about how collaborative AI survey response analysis works in Specific, or see the benefits of the AI survey editor for real-time group edits.
Create your hotel guest survey about problem resolution now
Start capturing deeper feedback, surface the true causes of guest dissatisfaction, and act on your findings instantly with AI-powered surveys and analysis tailored to the reality of modern hospitality.