This article will give you tips on how to analyze responses from an Inactive Users survey about Churn Reasons using AI-powered tools and proven strategies for survey response analysis.
Choosing the right tools for analyzing survey data
How you analyze survey responses really depends on the type and structure of your data. Let’s quickly break down approaches for both:
Quantitative data: If your survey results include things like how many users selected a specific churn reason, you can count these using tools like Excel or Google Sheets. Counting and filtering are fast, straightforward, and don’t require any special expertise.
Qualitative data: When you’re sitting on a collection of open-ended responses or follow-up answers, it’s impossible to manually process and make sense of all those individual stories at scale. That’s where AI comes in to help summarize patterns, themes, and unique feedback.
There are two approaches for tooling when dealing with qualitative responses:
ChatGPT or similar GPT tool for AI analysis
Copy and chat: You can copy the exported survey data from your results sheet and paste it into ChatGPT or another GPT-based tool. When you ask it to summarize or cluster feedback, you’ll usually get solid insights.
Pain points: This method isn’t super convenient for big surveys—it’s easy to hit context size limits, lose track of individual threads, or have to jump through hoops to get the summary you want. Managing which answers you send for analysis can be fiddly.
All-in-one tool like Specific
Purpose-built for AI survey feedback: Specific is designed specifically for running conversational surveys and analyzing responses. Not only does it collect feedback, but it automatically asks intelligent follow-up questions to get richer data (learn more about automatic AI follow-up questions).
Instant AI-powered analysis: As soon as your Inactive Users survey is done, Specific's AI survey response analysis kicks in: it summarizes feedback, clusters key churn reasons or trends, and extracts actionable insights. No manual summaries, no spreadsheet wrangling.
Conversational analytics: You can chat directly with the AI about your data, similar to ChatGPT—but with added context, filters, and features specifically for survey work. It even lets you decide which conversations or questions get sent to the AI for analysis.
Seamless workflow: No copy-pasting, no fuss, just go from raw feedback to decision-ready insights.
Useful prompts that you can use to analyze Inactive Users churn reasons survey data with AI
If you want your AI tool—or even ChatGPT—to deliver meaningful survey analysis, your prompts matter. Here are a few I rely on with datasets about Inactive User churn reasons:
Prompt for core ideas: Use this to surface strong topics and themes in a large set of open-ended feedback. It’s the same structure Specific uses to extract main insights:
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
This works even better if you give AI extra context up front. For example, describe your goal, the audience, or how the Inactive Users were selected. Here’s how you can do that:
This dataset contains survey responses from users who stopped using our product in the last 90 days. My goal is to understand their main reasons for leaving, as well as any feedback that could help us improve onboarding or customer experience. Please analyze for recurring themes and quantify how often each main reason appears.
Dive deeper into core ideas: If a theme like "poor onboarding" pops up, follow up with, “Tell me more about poor onboarding” to get richer details.
Prompt for specific topic: To check if anyone mentioned a topic you care about (like pricing):
Did anyone talk about pricing in their churn reasons? Include quotes.
Prompt for pain points and challenges: To spotlight top friction points:
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 personas: When you need to identify personas among churned users:
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 unmet needs & opportunities: To find what features or experiences could have kept them active:
Examine the survey responses to uncover any unmet needs, gaps, or opportunities for improvement as highlighted by respondents.
For other prompt ideas and a deeper dive, check out our article on the best questions for churn reasons surveys.
How Specific analyzes qualitative data based on question type
Specific gives you structured summaries for every type of survey question:
Open-ended questions (with or without follow-ups): Get a concise summary for all responses, plus an analysis of any connected follow-up answers. You instantly see patterns and key reasons mentioned by Inactive Users.
Choice questions with follow-ups: Each answer option includes its own summary of related follow-up feedback. This helps reveal why users selected particular churn reasons.
NPS questions: Feedback is broken down separately for detractors, passives, and promoters, so you get distinct insight into why different user groups left or stayed.
If you prefer ChatGPT, you can still get high-quality insights, but you’ll need to manually copy, paste, and repeat prompts for each question type and segment. With Specific the workflow is ready out of the box.
See how this works in practice with our AI-powered survey response analysis tool.
How to tackle challenges with AI’s context limits
When you’ve got a lot of Inactive User survey responses, there's a good chance your dataset will hit the AI’s context size limit (the max it can process at once). That can block large-scale analysis. Here’s how you can work around these limits—both approaches are baked right into Specific:
Filtering: Zero in on conversations where users replied to particular questions or picked specific churn reasons. This trims the dataset so AI can analyze the most relevant insights without getting overloaded.
Cropping: Instead of sending entire conversations, crop responses so only answers to selected questions go to the AI. This ensures you stay within context size limits and cover more users in your analysis.
For more on streamlining your analysis with context controls, check our guide to AI-powered survey response analysis.
Collaborative features for analyzing inactive users survey responses
Collaborating on survey analysis—especially about churn reasons—can be messy. Teams are often spread across different docs or tools, and it’s tough to keep everyone aligned or see what insights colleagues already found.
Effortless team collaboration: In Specific, you can analyze survey data just by chatting with AI. It’s as intuitive as group messaging, but with the added power of context-aware AI analysis.
Multiple perspectives: Each team member can spin up their own chat—focused on a specific filter, segment, or question. For example, one chat might dig into onboarding pain, another into pricing objections. This lets you work in parallel and compare findings easily.
Visibility and attribution: Every chat shows who created it, so there’s no confusion about whose insights or directions you’re seeing. When collaborating in AI Chat, each message displays the sender’s avatar, so attribution is crystal clear.
If that sounds useful, learn how to create and launch surveys designed to reduce churn with your team.
Create your Inactive Users survey about churn reasons now
Start collecting and analyzing rich churn feedback from Inactive Users in minutes with AI-powered prompts, follow-up questions, and actionable insights—all in one seamless workflow.