This article will give you tips on how to analyze responses/data from ex-cult member surveys about therapy experience. If you want relevant insights quickly, AI-powered survey response analysis is your best friend.
Choosing the right tools for survey response analysis
How you analyze ex-cult member surveys about therapy experience depends on the form of the data. If your responses are all multiple-choice, spreadsheets can get you far, but open-ended answers need extra muscle.
Quantitative data: Numbers are easy—Excel or Google Sheets can crunch them and help you surface patterns, track frequencies, or visualize statistics at a glance.
Qualitative data: If you have freeform answers or open-ended feedback, it’s almost impossible to read everything meaningfully at scale. That’s where AI tools come in—they sort, summarize, and prioritize themes, saving you hours of “scroll and scan.”
There are two approaches for tooling when dealing with qualitative responses:
ChatGPT or similar GPT tool for AI analysis
Copy-paste and chat: You can export your text responses and paste them into ChatGPT, then ask questions like “What are the main themes?” or “Did anyone mention trauma recovery?”
Manual setup can be tedious: With lots of responses, you’ll find copy-paste tedious, context-limited, and sometimes unstructured—especially for follow-up questions or when you want to get segment-specific insights. Still, if you’re comfortable with AI prompts, this route is super flexible.
All-in-one tool like Specific
Purpose-built workflow: Specific is designed for both collecting and analyzing qualitative survey data—especially from conversational, followup-driven surveys. If you run an ex-cult member survey about therapy experience on Specific, you’ll collect richer stories because the AI asks precise followup questions at the right moment. Learn why AI followups elevate response quality.
Insight generation with zero friction: After collecting responses, Specific instantly analyzes your data—summarizing every open-ended answer, surfacing primary themes, and letting you directly interact with results in an AI-powered chat environment. AI survey response analysis tools make desktop analysis a breeze, letting you filter, chat, or dig into segments with performance well beyond spreadsheets.
Extra features for AI context: You can manage exactly what responses or which segments get sent to AI for summarization and analysis, overcoming context-limit headaches.
Alternatives include advanced AI-powered research tools like NVivo, MAXQDA, or Canvs AI, which offer sentiment analysis, visualizations, and thematic mapping for complex qualitative datasets. These are great if you’re running big research teams or mixed-methods studies, but they require setup and process investment. [1][2]
Useful prompts that you can use for analyzing ex-cult member therapy experience survey responses
What really unlocks value in AI survey analysis is giving your AI the right prompts. Here are some that work great for ex-cult member therapy experience responses—and you can use them in any AI tool, from Specific to ChatGPT to other platforms.
Prompt for core ideas: This prompt helps you identify the main topics and how often each comes up. Use it straight-up or adapt it if needed:
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 performs better when you give more context. For example, mention if your survey explores barriers to therapy, recovery experiences, or relapse risks:
Analyze these survey responses from ex-cult members about their therapy experience. The aim is to understand what support methods feel most helpful in the recovery journey, and what common obstacles participants face in or after therapy.
After getting main ideas, dive deeper into specifics with:
Follow-up on core idea: Tell me more about XYZ (core idea)
Did anyone talk about [topic]? Use: Did anyone talk about trauma triggers in their therapy experience? Include quotes. It helps validate whether certain themes appeared.
Prompt for pain points and challenges: Ask: 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 Motivations & Drivers: From the survey conversations, extract the primary motivations, desires, or reasons participants express for seeking therapy or continuing with it. Group similar motivations together and provide supporting evidence from the data.
Prompt for 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.
Prompt for 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.
If you want more tips on survey questions or creating a research-ready interview, dig into best questions for ex-cult member therapy experience surveys or how to create one quickly.
How Specific analyzes qualitative questions by response type
In Specific, the structure of your survey makes a big difference in how AI can analyze ex-cult member therapy experience data.
Open-ended questions (with or without followups): You get summaries for each question, plus extra context from followup answers. The main summary highlights the biggest themes, and you can chat with AI to drill deeper into any unusual or emotionally-charged response.
Choices with followups: Every choice gets its own report—so if you ask, “What kind of therapy did you pursue?” and set follow-ups on each selection, you’ll see both quantitative data and qualitative summaries linked to each therapy type. Patterns leap out and you can easily segment for deeper insights.
NPS-style questions: If you ask “How likely are you to recommend therapy after leaving a cult?”, Specific slices and analyzes feedback for each NPS group (detractors, passives, promoters) separately. That means you surface what supporters love versus what critics want fixed—but you don’t have to wade through the whole dataset manually.
You can do similar things in ChatGPT or NVivo, but it’ll require good filter discipline and extra copying and slicing.
How to overcome AI context limits in survey data analysis
If you’re running a well-answered ex-cult member survey, you’ll hit the “context window” for AI—meaning your total conversation history might exceed what the AI can process in one go. Specific offers two ways to control what the AI analyzes:
Filtering: Select only conversations where users responded to particular questions or chose certain answers. That narrows focus and keeps analysis sharp.
Cropping: Choose exactly which questions will be included when talking to AI. You avoid “context spillover” while zeroing in on the most critical parts of your study.
This makes handling big data volumes much more feasible and actionable compared to generic AI chats or unfiltered exports.
Collaborative features for analyzing ex-cult member survey responses
It’s tough (and lonely) to make sense of complex therapy experience surveys on your own, especially with emotionally nuanced data from ex-cult members.
Effortless collaborative environment. Specific lets you analyze and discuss data together via live AI chat—no need for exported docs or overcrowded spreadsheets.
Multiple analysis threads. You can create multiple chats around different topics (for example, “therapy pain points” and “success stories”)—each chat shows who started the thread, so your team can divide and conquer. Filters let you zoom in on sub-populations, like men vs. women, lapsed vs. current therapy clients, or particular age groups.
Transparency and team accountability. Every chat shows avatars and names of team members contributing to the analysis, so you never lose track of who said what or how your insights evolved. This is especially valuable for research teams, therapists, or advocacy groups collaborating on high-stakes, sensitive research.
Create your ex-cult member survey about therapy experience now
Turn ex-cult member stories into actionable insight—with conversational surveys that probe deeper and AI that distills meaning instantly. Start now for richer feedback, better understanding, and smoother collaboration—no manual crunching required.