This article will give you tips on how to analyze responses from Workspace Admins survey about Security Awareness, using AI to dive deep into both quantitative and qualitative data.
Choosing the right tools for analyzing Workspace Admins survey responses
Your approach to survey analysis depends on the form and structure of your data. Let's break it down so you get value from both numbers and words—because in security awareness, it's the stories and context that fuel real change.
Quantitative data:
If you’re counting how many Workspace Admins selected certain options (e.g., "Have you had security training in the past year?"), use tools like Excel or Google Sheets. These make tallying up percentages and visualizing basic trends fast and straightforward.
Qualitative data:
For open-ended responses (like "What security challenges do you face?"), or even follow-ups that ask "Can you tell me more?", you need AI tools. Reading through dozens or hundreds of responses isn’t realistic. AI can spot patterns, extract insights, and summarize conversational feedback at scale.
There are two approaches for tooling when dealing with qualitative responses:
ChatGPT or similar GPT tool for AI analysis
Manual copy-paste: You can export your survey data and paste responses into ChatGPT or a similar AI tool. Then, just chat with the model about your data, ask it for key themes or summaries, or even specific topics like “What do Workspace Admins worry about most when it comes to phishing?”
Downsides: It’s not the most convenient path. You’ll hit character or token limits, lose track of chat history, and manual context management can quickly become a headache for ongoing team analysis.
All-in-one tool like Specific
Purpose-built AI analysis: With a solution like Specific, you can both collect and analyze your Workspace Admins Security Awareness survey responses in one place.
Better data quality: Specific’s AI asks intelligent follow-up questions in real time, capturing deeper context—so your analysis starts from richer source data. More depth means better insights, which is critical since 85% of data breaches involve a human element. It’s not enough to just count answers; you have to understand the thinking behind them. [1]
Zero manual sorting: The AI instantly summarizes all responses, highlights main themes, and makes it easy to chat back and forth—just like ChatGPT, but with built-in filtering, conversation history, and fine-tuned context management. This radically speeds up Security Awareness analysis and ensures no insight gets lost in the weeds.
If you’re curious about creating the actual survey, you can learn the best questions for this topic in this article.
Useful prompts that you can use to analyze Workspace Admins Security Awareness survey responses
AI works best when you give it specific, high-impact prompts. Let’s cover proven prompts you can use in ChatGPT, Specific, or any similar tool:
Prompt for core ideas — Works great for summarizing major topics across large sets of qualitative responses:
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 always delivers stronger results if you provide more context about your survey. For example:
This data comes from Workspace Admins surveyed about Security Awareness. The goal is to pinpoint habitual risks, blind spots, and reactions to recent training. I’m especially interested in phishing prevention and software update habits.
Dive deeper into hot topics: Try “Tell me more about [core idea]” to focus on the biggest themes surfaced in the summary.
Prompt for specific topic: Use “Did anyone talk about [topic]?”—For example, “Did anyone talk about password management?” Add “Include quotes” if you want to see how respondents express themselves.
Prompt for personas: Get a landscape of your admin base by asking:
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: Tackle the most persistent headaches:
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 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.
Want to see how to create a great survey in minutes? Check out the AI survey generator for Workspace Admins Security Awareness surveys—you can use your own prompts for the questions too.
How Specific analyzes qualitative data based on question types
Specific’s analysis engine is tailored to the question type—so you get clarity no matter the structure. Here’s what happens behind the scenes:
Open-ended questions (with or without follow-ups): You’ll see a summary covering all responses and their related follow-ups. This means the AI picks up on small nuances and follow-up context, not just the main answer.
Choice questions with follow-ups: Each selected choice generates its own focused summary of related follow-up answers. For instance, if “Lack of training” is a top answer, the AI will group and synthesize all elaborations related to that choice.
NPS questions: The AI summarizes responses for each NPS segment (detractor, passive, promoter), so you quickly spot differing drivers and blockers in Security Awareness sentiment among your admins.
You can replicate this in ChatGPT by managing your summaries for each category—it just takes more manual labor and cut-and-paste effort to stay organized, especially as response counts climb.
If you’re reworking question wording or logic, consider using Specific’s AI survey editor so you can iterate with natural language instead of forms or code.
Overcoming AI context size limits in survey analysis
Context size matters: Even the best AI has a short memory. If your Workspace Admins Security Awareness survey returns lots of responses, all your data may not fit into the AI’s “context window”—that live slice of the data it can analyze at once.
Two common ways to solve this—both supported natively in Specific—are:
Filtering: Choose to analyze only conversations where users replied to selected questions or gave specific answers. This narrows AI focus to the most important issues, making responses manageable and sharp.
Cropping questions: Limit what’s sent to the AI by selecting just the questions you care about. No need to sort manually in a spreadsheet—the tool handles data reduction, so you can review more conversations with detailed analysis before hitting the context limit.
For more on how context filtering and reduction work, see this guide to AI survey response analysis.
Collaborative features for analyzing Workspace Admins survey responses
Security Awareness surveys for Workspace Admins often need input from multiple stakeholders—think IT, compliance, HR, or even external consultants. Keeping everyone aligned on the why behind results and what actions to take can get tricky.
Analysis by chat: With Specific, you interactively analyze data by chatting with the AI—simple, familiar, fast. This makes it easier for different team members to ask their own questions, whether it’s validating an incident trend or digging into training gaps.
Multiple analysis chats: Each analysis can be split into its own chat, with separate filters and focuses. This means your IT lead can drill into phishing incidents while your compliance officer explores reporting processes—side by side, with clear ownership of each thread.
See who’s saying what: Within chats, avatars reveal who’s leading each discussion and who said what. For workspace admins, this is a game-changer—it brings transparency to Security Awareness discussions and keeps everyone accountable for next steps.
If you’re ready for hands-on tips for survey creation, check out this practical guide on building Workspace Admins surveys for Security Awareness.
Create your Workspace Admins survey about Security Awareness now
Gather deeper, higher-quality insights and accelerate your Security Awareness program with smarter AI-powered survey analysis.