This article will give you tips on how to analyze responses from an Inactive Users survey about value perception. If you want practical steps for survey response analysis, you’re in the right place.
Choosing the right tools for survey response analysis
If you want clear insights from an inactive users survey on value perception, your choice of tools depends on the structure of your collected data. Let’s break it down simply:
Quantitative data: Think about responses like “Which feature do you use most?” or NPS scores. These are straightforward counts and averages—Google Sheets or Excel can do the heavy lifting here in seconds.
Qualitative data: Open-ended questions and conversational follow-ups are a different beast. When hundreds mention why they stopped using your product or what they value, there’s too much nuance for a spreadsheet. That’s where AI-powered tools step in, surfacing the themes you’d miss by hand.
There are two approaches for tooling when dealing with qualitative responses:
ChatGPT or similar GPT tool for AI analysis
Copy, paste, chat: Export your survey data (often as a CSV), copy it, and paste into your favorite GPT tool—like ChatGPT. From there, you can prompt the AI with questions about what users said or look for common themes.
This gets old quickly: While it works, it’s tedious—especially if you have a lot of responses, want to filter by certain groups, or need context-aware follow-up. You’ll find yourself editing out columns, creating summaries, and manually figuring out who said what. But as a lightweight option, it offers flexibility if you know your way around AI.
All-in-one tool like Specific
Purpose-built for survey response analysis: Tools like Specific are designed from the ground up for this job. They handle both collecting deeper, chat-like survey responses and analyzing them automatically.
With Specific, you get an edge thanks to automated follow-up questions, which capture nuance traditional surveys miss. Afterward, the AI summarizes every open-ended answer, highlights core insights, and organizes everything by key topics or personas. You don’t need to wade through heaps of text or make sense of endless CSV exports—actionable summaries come standard, not as a bonus.
Conversational analysis and better management: Ask the AI anything—literally chat about your data, just like you’d with ChatGPT. Plus, you can use filters, isolate segments (like specific NPS groups), and collaborate across teams. That’s all without losing context or scrambling to move data between tools.
Whether you use something universal like ChatGPT, or a dedicated survey response analysis tool like Specific, make sure your tool helps you see the story behind the numbers—not just the numbers themselves.
That’s crucial, considering that nearly 40% of U.S. households who haven’t tried generative AI simply don’t see the value in these tools. If you’re surveying inactive users about value perception, you’re stepping right into the heart of this modern skepticism. [1]
Useful prompts that you can use to analyze Inactive Users survey about value perception
Once you have your surveys and tools ready, prompts are the secret weapon for extracting actionable insights—especially if you’re sifting through data all about value perception from inactive users.
Prompt for core ideas: This is the heavy lifter. It distills big chunks of text into headline topics, exactly like Specific does. Try this in ChatGPT or anywhere you analyze qualitative data:
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
Boost results with extra context: Always let the AI know what the survey is about, who answered, and your goals. Here’s an example:
Analyze the following survey responses. The survey targeted inactive users to understand their value perception of our product. My goal is to identify main barriers to re-engagement and perceived benefits or gaps.
Dive deeper: Once you see what themes emerge, ask follow-up prompts like:
Tell me more about dissatisfaction with pricing (core idea).
Validate with direct prompts: Use this to quickly check if the topic you care about was mentioned.
Did anyone talk about missing integrations? Include quotes.
Uncover personas: For bigger surveys, you might want to group users into behavioral personas:
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.
Surface 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.
Motivations and drivers:
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:
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.
Suggestions and opportunities: Zero in on ideas you haven’t considered yet.
Identify and list all suggestions, ideas, or requests provided by survey participants. Organize them by topic or frequency, and include direct quotes where relevant.
These prompts cut through the noise and help you turn ambiguous “value perception” answers from inactive users into patterns you can act on. Want more tips straight from the experts? Check out the best questions to ask in an inactive users value perception survey and how to create a value perception survey for inactive users for ideas on survey design.
How Specific analyzes qualitative data from different survey question types
Open-ended questions (with or without follow-ups): Specific gives you a summary for all responses to a question, plus a breakdown of common themes from any follow-up probes triggered by the AI. It doesn’t just cram all the data into one list—you get clarity for every layer of each conversation.
Choice questions with follow-ups: Here, every single choice—say, “Didn’t understand the core benefit” or “Too expensive”—has its follow-up responses summarized and themes extracted. You see exactly why that choice resonated (or didn’t) among inactive users, which helps you know where your value messaging might have faltered.
NPS questions: Specific analyzes reasons separately for promoters, passives, and detractors, so you get a clear picture of what makes people love (or leave) your product. Each category’s feedback gets a summary and key insights, so you can target your retention strategy more precisely.
You can do all this with a GPT tool like ChatGPT, of course—but you’ll spend more time prepping your data, rerunning analysis for each segment, and organizing summaries yourself.
For a deeper dive, check out this guide on using AI for survey response analysis.
Staying inside AI context limits when handling large survey data sets
Every AI tool, even the best ones, has a limit—a “context window”—on how much data it can process at once. If your inactive users survey gets hundreds of detailed responses, it’s easy to hit that wall. That’s why Specific provides two smart ways to deal with data overload (and you can replicate these strategies even with a simple GPT tool):
Filtering: Instead of analyzing everything at once, filter your conversations to include only users who replied to certain questions, or who made specific choices (like those who gave low value perception scores). This shrinks your dataset and makes analysis more meaningful.
Cropping (questions): Focus the AI on specific parts of each conversation—such as only answers to “What stopped you from continuing to use the product?”—instead of sending every chat transcript. This keeps you inside your tool’s data limits and gets to the point faster.
If you want even more control, Specific lets you tweak these settings in real time—so you always get rich analysis without hitting those context ceilings. This matters especially as you scale up, considering that 69% of workers still haven’t used AI for analysis at work, possibly out of concern for tool complexity or practicality. [3]
For building surveys that are easy to analyze, try the Specific AI survey generator preset for inactive users value perception surveys.
Collaborative features for analyzing inactive users survey responses
Collaboration can get messy fast—especially when you’re trying to align multiple teams on why your inactive users don’t see the value. The worst case is version chaos: multiple analysts, multiple spreadsheets, endless email threads about “which summary is the right one?”
Analyze survey data by chatting: In Specific, everyone can chat with the AI about your responses—no need to spin up separate threads outside your workspace. The AI remembers the context and doesn’t treat each question as disconnected, so your follow-up prompts always make sense.
Multiple chats for different perspectives: Want your product manager to zero in on lost feature value while a marketer focuses on churn language? No problem. Each chat (analysis thread) can have its own filters applied. You see who started each discussion, which gives clarity and avoids cross-team confusion.
Transparency is built in: Every message in AI Chat shows who sent it, represented with a sender avatar. This makes complex survey analysis social—if you’re interpreting why users bailed or what value means to different audiences, you’re not doing it alone. It’s all traceable, efficient, and easier to present in a team meeting or to leadership.
Looking to launch a collaborative survey analysis workflow? Use the AI survey editor to co-design your survey as a team, or check out the survey generator for any topic.
Create your inactive users survey about value perception now
Act now: create a survey that feels like a conversation, captures deep user motivations, and gives you instant AI-powered insights—so you know exactly how inactive users see your value.