This article will give you tips on how to analyze responses from workspace admins surveys about access management with practical, AI-driven techniques.
Choosing the right tools for analysis
The way you analyze survey responses from workspace admins on access management depends on your data’s structure.
Quantitative data: If you’re looking at numbers—like how many admins said “yes” to a security feature—it’s straightforward. Tools like Excel or Google Sheets quickly generate counts, percentages, and charts. Perfect for multiple-choice, ratings, or binary questions.
Qualitative data: When your responses are open-ended—think admins describing pain points or sharing solutions—the game changes. Reading every response by hand isn’t practical, especially if your survey is successful and the data piles up. This is where AI tools, particularly ones using language models like GPT, help make sense of it all.
There are two approaches for tooling when dealing with qualitative responses:
ChatGPT or similar GPT tool for AI analysis
You can take your exported open-ended data and drop it into a tool like ChatGPT. From there, you’re able to “chat” about your results, asking questions or prompting GPT to summarize themes.
But here's the catch: This process can be clunky if you have a lot of data. You’ll spend time cleaning CSV files, stripping out personally identifiable info, and chunking the dataset into digestible pieces that fit the AI’s memory limit. It's a manual, sometimes messy process—even though the actual AI analysis part is powerful in itself.
Good for rapid prototyping, but not the best for ongoing analysis or large-scale, collaborative projects where you want everything in sync.
All-in-one tool like Specific
Specific is purpose-built for this workflow. It lets you create and run AI-powered conversational surveys in minutes, and then automatically analyzes both quantitative and qualitative responses.
Smart data collection: By asking automated follow-up questions, Specific gets better answers from workspace admins—deeper insights, clearer context, less noise. Learn more about automatic AI follow-up questions.
No spreadsheets or copy-paste needed: The platform’s AI-powered survey response analysis summarizes open-ended responses, identifies key themes, and instantly flags what’s most and least common. It’s like having a research analyst who never misses a detail.
Conversational querying: You can chat directly with the AI about the data—just like ChatGPT, but with powerful survey-specific context and controls. Adjust what info gets sent to AI, filter by demographics or responses, and always see the underlying data. This streamlined approach means you spend less time wrangling exports, and more time learning what workspace admins actually think.
Workplace survey software like Specific is growing in popularity for these reasons—over 73% of organizations have adopted automation for survey data collection and analysis, drastically reducing manual workloads while increasing the speed and clarity of insights. [1]
Useful prompts that you can use for analyzing Workspace Admins Access Management survey data
Let’s talk prompts. When you’re analyzing workspace admin responses about access management, the right instructions for your AI tool will make a world of difference. Here are proven, plug-and-play prompts—start with them in ChatGPT, or experiment right inside a tool like Specific.
Prompt for core ideas: This “extract topics” prompt reliably pulls out the most discussed themes, with counts. (Specific uses this prompt under the hood.)
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 models always give better results with more context. You can (and should) tack on details like your survey's purpose or what you hope to achieve. For instance:
Here’s the context: This survey was run among workspace administrators to understand current pain points and future priorities in access management across SaaS tools. Our goal is to identify blockers, unmet needs, and actionable improvement areas in our IAM processes.
Dive deeper on any theme: When you see a result you care about (“2FA confusion,” for example), use:
“Tell me more about 2FA confusion.”
Prompt for specific topic: Validate whether a concern (or suggestion) showed up in the data.
“Did anyone talk about single sign-on? Include quotes.”
Prompt for personas: Great for segmenting your workspace admin community:
"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: Direct line to friction and blockers:
“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 and drivers: Understand what inspires action:
“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: Spot the mood of your admins:
“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 and ideas: Collect requests and “why didn’t I think of that?” gems:
“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: Find what’s missing:
“Examine the survey responses to uncover any unmet needs, gaps, or opportunities for improvement as highlighted by respondents.”
If you want to improve your next access management survey or just want to learn what questions work best for workspace admins, see our detailed breakdown on survey design.
How Specific analyzes qualitative data by question type
Every question format benefits from AI analysis, but Specific customizes its approach based on structure:
Open-ended questions: You get a bird’s-eye summary for all responses, and if you use follow-ups (for example, “Why is this a pain point for you?”), you get a focused summary of the extra context workspace admins provide.
Choices with follow-ups: Each choice (e.g., “We use SSO,” “Manual provisioning”) gets its own summary for any follow-up responses. No more manual filtering—just clear, per-option insights.
NPS: Specific automatically splits out follow-up answers by NPS group: detractors, passives, promoters. Each group’s responses are summarized side by side, showing you the different motivations driving each score.
You can do all this the “manual way” in ChatGPT—just copy-paste and re-prompt for each question or group. But with a platform like Specific, it’s all built in, streamlined, and ready for collaboration. Explore more tips on running workspace admin access surveys.
Overcoming AI context size limits in survey response analysis
AI context limit is real: Most large language models max out at a few thousand tokens. That means if your access management survey has hundreds of admin replies, you can’t cram it all in at once.
There are two effective fixes, both available natively in tools like Specific:
Filtering: Quickly filter down your dataset—analyze just the conversations where users answered a particular question, or only admins who picked “manual provisioning.” You get laser focus and high-quality output.
Cropping: Select only the questions (or sections) that matter for your current analysis. This keeps the dataset slim and relevant, and drastically increases the number of responses you can actually fit and process in a single AI conversation.
Both these modes help you maximize the AI’s performance, while still surfacing the detailed, actionable findings that matter. Plus, you always maintain a clear audit trail of what subset you analyzed—critical for teamwork and compliance. [2]
Collaborative features for analyzing workspace admins survey responses
Collaboration on survey data is often a pain— especially for access management, where IT, security, ops, and product teams all want answers, often from different angles. Emailing fat Excel files and comment threads is a recipe for chaos.
AI chat for survey analysis: Specific lets you explore survey findings just by chatting with AI—so every stakeholder can ask their own questions, get custom summaries, and drill into themes that matter to their role.
Multiple chats, each with context: You can create as many separate AI analysis threads as you want, each filtered for specific departments, questions, or persona groups. Every chat shows who created it, making it super easy for a distributed team to track discussion and avoid duplicated work.
See who’s asking what: In every chat, messages show the sender’s avatar—so it’s obvious who raised what insights or asked for a deeper dive. You can cross-comment, branch into new focus areas, and keep the teamwork tidy without sticky notes or Slack screenshots.
If you want to see collaborative AI survey analysis in action, Specific offers a rich chat interface built for real workflows—not just solo experimentation.
Create your Workspace Admins survey about access management now
Start collecting real answers from the right people and let AI do the heavy lifting—unlock deeper insights, faster, for your access management decisions.