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How to use AI to analyze responses from citizen survey about permit and licensing process

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Adam Sabla

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Aug 22, 2025

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This article will give you tips on how to analyze responses from a citizen survey about the permit and licensing process. We'll break down proven strategies, practical tools, and essential prompts for getting real insights from your data.

Picking the right tools to analyze your citizen survey data

Choosing the right approach largely depends on the format and structure of your survey responses. Here’s how to break it down:

  • Quantitative data: For responses like multiple-choice or rating questions, you can quickly tally numbers using tools like Excel or Google Sheets. This gives you clear stats on how many citizens faced issues or expressed satisfaction.

  • Qualitative data: When you collect open-ended responses or follow-ups, the real depth comes from context and nuance—things you can't just scan or count. Reading every answer by hand isn’t practical, especially when you have hundreds of entries. This is where AI tools step in and make all the difference, helping you summarize and spot themes in a fraction of the time.

There are two common approaches to handling qualitative survey data:

ChatGPT or similar GPT tool for AI analysis

You can export your open-ended citizen survey responses and paste them directly into ChatGPT or a similar AI tool. From there, simply ask questions about your dataset—as you would with a research assistant.

However, this manual approach has downsides: Copying and pasting data from spreadsheets can become tedious if you have lots of responses. Keeping context (like which question was asked) or managing filters for specific topics can get confusing fast. Also, if your data set is too large, the AI may hit context size limits and miss valuable details.

All-in-one tool like Specific

Specific is designed for this exact use case—streamlining both collection and fast analysis of survey responses via AI.

When citizens take your survey, Specific’s conversational format encourages richer answers by asking follow-up questions automatically—a feature that instantly raises the quality and depth of your data. See how automatic AI follow-ups work in this detailed guide.

After responses are collected, Specific’s AI analyzer can instantly summarize what citizens said, highlight key topics, and reveal actionable themes—without any spreadsheets or copying-pasting. You can also chat directly with the AI about your survey results, use advanced filters, and manage which data is sent to the AI for analysis. Want the full rundown? See the breakdown of AI survey response analysis features in this article.

Useful prompts that you can use for citizen survey analysis

AI-powered tools are only as good as the prompts you give them. Here are my top prompts for getting deep insights from your citizen permit and licensing process survey:

Prompt for core ideas: Use this to uncover the most frequently mentioned themes or pain points. This exact prompt powers much of Specific’s own AI summary output, and it works great in ChatGPT, too:

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

Tip: AI always gives you better results if you give it more context about your survey, your audience, and your goals. Just describe the scenario at the start:

I conducted a citizen survey on permit and licensing processes in our city to evaluate satisfaction and find barriers. Please analyze the following responses using the guidelines above.

Prompt for deeper dives: When you spot an interesting idea or pain point, ask the AI to expand. Try:

Tell me more about XYZ (core idea)

Prompt for targeted topics: Quickly check if anyone talked about a specific issue:

Did anyone talk about long wait times? Include quotes.

Prompt for personas: Want to segment your citizens into meaningful groups? Try:

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: Instantly surface the most common barriers:

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 suggestions and ideas: Collect actionable insights for improvement:

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 sentiment analysis: Gauge how satisfied or frustrated citizens are:

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.

Want more smart question ideas? Check out these examples of the best questions for a citizen survey about permit and licensing process.

How Specific analyzes citizen survey responses by question type

Specific tailors how it analyzes your qualitative data depending on the survey question:

  • Open-ended questions (with or without follow-ups): For every open-ended item, you get a comprehensive summary across all responses, including deeper dives from follow-ups that target clarifying details or new insights.

  • Choices with follow-ups: If your multiple choice question triggers follow-up questions, you get focused summaries for each choice’s unique follow-up responses. This lets you compare what’s really driving choices (or frustrations) between those who, say, selected "satisfied" versus "frustrated".

  • NPS (Net Promoter Score): When you use an NPS-style question, Specific highlights summary themes for detractors, passives, and promoters, based on their respective follow-up feedback. This segmented view often reveals why people give high or low ratings.

You could recreate these granular analyses manually using ChatGPT—but it takes more time, and you’ll need to carefully manage copying, filtering, and structuring your data.

For tips on creating smarter surveys that drive better responses to these question types, see this citizen survey how-to.

Overcoming AI context size limits in survey analysis

All AI tools—ChatGPT included—face context size restrictions, meaning they can't digest unlimited data at once. If your citizen survey on permit and licensing process collects hundreds or thousands of responses, here's how to avoid running into a wall:

  • Filtering: Only feed the AI with those conversations that include replies to the questions or choices you care most about. For example, if you want to dive deep into "frustrated" respondents, filter out responses from satisfied ones.

  • Cropping: Instead of sending the full survey transcript, narrow the analysis to just selected questions. This way, the AI works efficiently, staying within its input limits while maximizing insights from what's most relevant.

Specific offers both approaches natively—so you can move from collection to deep analysis without worrying about technical hurdles. For an overview of these filtering and cropping features, see this explainer on response analysis.

Collaborative features for analyzing citizen survey responses

Collaborating on survey analysis is often challenging for teams managing citizen permit and licensing process feedback—especially when discussions sprawl across email threads or shared docs.

In Specific, you don’t need to leave the platform to go deep on insights. You and your colleagues can chat directly with the AI about survey responses and quickly spin up as many conversations as you want, each focused on a different question or sub-group of citizens.

Each AI chat session tracks who created it and what filters are applied. This makes it easy to keep track of different lines of inquiry—whether you're segmenting by city, by complaint, or by overall NPS score. Working across teams becomes smoother, as everyone can see who asked what and why.

Collaboration is visual and contextual. You always know the source of each insight: each message in the chat shows the sender's avatar, keeping conversations organized and reducing confusion.

If you want a hands-on example of generating these collaborative citizen surveys, see this survey generator tailored for this exact use case. Or if you'd rather start from scratch, try the AI survey generator for any topic.

Create your citizen survey about permit and licensing process now

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Sources

  1. Jordan News. 95.5% Citizen Satisfaction with Procedures at Government Service Centers (Q1 2025)

  2. The Express Tribune. Populace critical of tough driving licence requirements (Punjab, 2016–2023 trends)

  3. IJMABER Journal. Client satisfaction in Driver’s License Renewal Offices in the Philippines

Adam Sabla - Image Avatar

Adam Sabla

Adam Sabla is an entrepreneur with experience building startups that serve over 1M customers, including Disney, Netflix, and BBC, with a strong passion for automation.

Adam Sabla

Adam Sabla is an entrepreneur with experience building startups that serve over 1M customers, including Disney, Netflix, and BBC, with a strong passion for automation.

Adam Sabla

Adam Sabla is an entrepreneur with experience building startups that serve over 1M customers, including Disney, Netflix, and BBC, with a strong passion for automation.