This article will give you tips on how to analyze responses from an Ex-Cult Member survey about Coercive Control Experiences. Whether you want to go deep into qualitative feedback or quickly surface top trends, AI can help you turn complex survey data into clear, actionable insights.
Choosing the right tools for survey response analysis
How you approach analysis depends on the structure and format of your survey responses. The best strategy and tooling is shaped by whether you’re working with quantitative or qualitative data.
Quantitative data: If your survey includes clear-cut numbers—how many respondents selected a certain option, scored a statement, or checked a box—Excel or Google Sheets gets the job done. You can tally frequencies, calculate averages, or build quick charts in minutes.
Qualitative data: Open-ended answers, story-driven feedback, or multiple follow-up responses demand a different touch. Since reading through hundreds of raw narratives just isn’t feasible, you’ll want to lean on AI tools designed to understand, organize, and summarize human language.
There are two main approaches for analyzing qualitative responses efficiently:
ChatGPT or similar GPT tool for AI analysis
With ChatGPT (or other GPT-4+ models), you can copy and paste exported survey data and ask the AI to summarize, extract themes, or identify key trends. In many cases, you can use smart prompts to get solid overviews or targeted analyses.
However, this workflow isn’t always smooth: Formatting and preparing your data for GPT is tedious. You may run into character or context limits, making it frustrating for larger surveys.
It’s best for quick one-off deep dives where you’re comfortable managing raw data and re-prompting the model as you refine your analysis.
All-in-one tool like Specific
Specific is an AI tool built from the ground up to help you both collect ex-cult member surveys and analyze qualitative responses about coercive control experiences.
When you collect data with Specific, the AI asks smart follow-up questions in real time. This increases the quality, richness, and structure of your data—something you’ll struggle to replicate with static surveys or forms.
Analysis in Specific is frictionless: the AI instantly summarizes open-ended responses, finds recurring themes, and generates actionable insights without spreadsheets or manual work. You don’t have to prepare anything—just open up your results and start chatting with the AI about what matters to you.
You get full control over how context is managed and which responses are analyzed. You can even see how the AI analyzed each section. And, for more complex cases, you can filter which questions and conversations are included. Check out more details on AI-powered survey response analysis in Specific.
For even more on survey creation, there’s a guide to easily creating ex-cult member surveys about coercive control experiences and a list of the best survey questions for ex-cult member research.
Useful prompts that you can use for Ex-Cult Member survey data analysis
Prompting well is everything. Here are practical, field-tested prompts to help you extract real meaning from ex-cult member survey responses about coercive control:
Prompt for core ideas: This catch-all works for surfacing major topics and recurring themes from even large qualitative data 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
AI delivers better output when you provide more background. For example, if you tell the AI “I’m analyzing anonymous responses from a survey of ex-cult members about coercive control. My goal is to uncover the main patterns and actionable recommendations for support organizations,” you’ll get richer, more targeted results.
Prompt for adding context:
You are analyzing anonymous survey responses from ex-cult members about their experiences with coercive control. My goal is to discover the main challenges they faced and the support that was most (or least) helpful after leaving. Focus on extracting actionable insights for support providers.
Dive deeper into specific insights by asking follow-ups like: “Tell me more about [core idea]” — and let the AI explain or pull supporting quotes and specifics.
Prompt for specific topic: Use this when you want to check if anyone discussed a precise issue or context:
Did anyone talk about [insert topic]? Include quotes.
Prompt for personas: Great for mapping out who is responding:
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 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.
Prompt for Motivations & Drivers: Use it for the “why”:
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.
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 Suggestions & Ideas:
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:
Examine the survey responses to uncover any unmet needs, gaps, or opportunities for improvement as highlighted by respondents.
These prompts work whether you’re using ChatGPT, NVivo, MAXQDA, or Specific—adjust as needed for your chosen tool and the structure of your survey.
How Specific summarizes analysis by question type
The way results are summarized depends on how you designed your ex-cult member survey—even more so when your survey uses follow-ups or branching questions.
Open-ended questions (with or without follow-ups): Specific provides a summary of all initial responses, plus a separate summary for all follow-up answers tied to the same question. It captures both high-level themes and in-depth nuances.
Multiple choice with follow-ups: Each choice gets its own targeted summary, drawing only from the follow-up responses of participants who selected that answer. You see not just popularity, but reasoning and lived experience behind each choice.
NPS (Net Promoter Score): Specific gives a separate insight summary for each key segment—detractors, passives, and promoters—based on all their follow-up responses, so you get actionable findings by sentiment tier.
You can replicate this with ChatGPT or qualitative data tools, but it takes much more hands-on work compared to the seamless workflow in Specific.
How to stay productive with AI context limits
AI tools are transformational—but they do have context size limits. If you’re dealing with hundreds or thousands of ex-cult member survey responses, the raw data probably won’t fit into a single analysis pass.
In Specific, you get two handy approaches (these can be adapted to other tools as well):
Filtering: Limit analysis to only those conversations where respondents answered selected questions or chose relevant options. This narrows the data set and tunes the AI’s focus.
Cropping: Select which questions (or parts of questions) will be sent to the AI. By cropping questions, you keep only the material that matters and can analyze more responses simultaneously.
These strategies make large-data analysis practical, so you never have to choose between depth and breadth.
For more ideas, check out our tips on automatic AI follow-up questions and AI survey editing for tailoring and managing survey content.
Collaborative features for analyzing ex-cult member survey responses
Collaboration on sensitive, deeply qualitative surveys can be a challenge—especially when your project crosses research, mental health, and advocacy teams. Comparing notes on ex-cult member experiences with coercive control often means juggling raw data exports, confusing spreadsheets, or endless comment threads.
Specific lets you analyze by chatting: Teams can simply open up the results and start chatting with the AI about different angles or interest areas.
Multiple chats for parallel analysis: Each analysis chat can have its own filters, questions, or data slices—one chat could focus on mental health challenges, another on support systems, a third on post-exit reintegration.
Transparency around collaboration: In Specific, every message in AI Chat is tagged with the sender’s avatar. You can instantly see who asked which question, making handoff and review seamless even in a large research group.
Actionable documentation: Each chat keeps a running log. You can revisit your team’s past prompts, see how the analysis evolved, and bring new collaborators up to speed—no friction, no lost context.
For more on collaborative and AI-powered research, explore the AI survey generator or survey response analysis features.
Create your ex-cult member survey about coercive control experiences now
Start turning open-ended stories from ex-cult members into meaningful, organized insights—backed by AI-powered summaries and powerful collaborative tools. Create a conversational survey that uncovers the real impact of coercive control, with actionable findings in minutes.