This article will give you tips on how to analyze responses from a citizen survey about small business support. If you want actionable insights instead of spreadsheets and headaches, read on—this is for you.
Choosing the right tools to analyze your citizen survey data
The best approach to analyzing your citizen survey results about small business support always comes down to the data you collect. Tools and tactics depend on whether you’re handling numbers (quantitative data) or rich, text-heavy responses (qualitative data).
Quantitative data: If you’ve got straightforward survey answers—like “How many citizens picked ‘improve parking’ as their priority?”—Google Sheets or Excel do the job perfectly. Count, filter, and chart—it’s simple, and widely understood.
Qualitative data: Open-ended answers and follow-up responses from citizens are a different beast. With dozens or hundreds of freeform opinions, no one wants to scroll through them one by one. This is where artificial intelligence can help: AI tools can read, interpret, find patterns, and summarize qualitative feedback, making it possible to extract real insights from messy text data. Given that AI-powered surveys can reduce survey fatigue by up to 40% and boost engagement by as much as 25%, it’s clear the market is moving this way fast. [4]
There are two basic approaches when you’re choosing tools to analyze qualitative survey responses:
ChatGPT or similar GPT tool for AI analysis
Copy and paste workflow: Many people simply export their survey results as text or CSV, then paste everything into ChatGPT or another GPT tool to start a conversation about the data.
Biggest drawback: While you can chat about your survey, tracking context, filtering, and handling large datasets is messy and inefficient. You’ll spend extra time keeping things organized and cleaning up raw text. Still, if you like experimenting or have only a handful of responses, it’s a quick start.
All-in-one tool like Specific
Purpose-built for survey analysis: Platforms like Specific let you both collect responses and analyze them instantly with AI. Instead of generic chat, Specific structures the process: it chats with respondents in a way that uncovers deeper, higher-quality data—by asking follow-up questions where it matters most.
AI-powered summaries and discovery: With Specific, you get instant analysis. You don't manually copy-paste or wrangle spreadsheets. The platform finds key themes, summarizes responses, and gives you actionable insights on citizens’ priorities for small business support. It’s as easy as chatting with GPT, but tailored to survey analysis. You can also manage which data points AI looks at, filter conversations, and segment results—making it effortless to see what citizens actually think and say. (If you want to know more on survey creation, check the AI survey generator for citizen small business support surveys.)
Bonus: This style of survey can ask dynamic AI-powered follow-up questions, which boosts response depth and relevance. Here’s why it matters: surveys that ask smart, targeted follow-ups collect far richer insights—there’s evidence that AI-driven survey tools are accelerating adoption, with the global market expected to hit $4.8 billion by 2025 at a 34.6% annual growth rate. [5]
Useful prompts that you can use to analyze citizen small business support survey results
Prompts are your shortcut to getting better, faster answers from AI survey tools—whether you’re using Specific, ChatGPT, or another GPT platform. Here are some go-to prompts that work great for open-ended citizen feedback about small business support:
Prompt for core ideas: Use this to quickly extract central themes from a big pile of survey 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 performs better with more context. Give it details about your survey purpose, goals, or the type of support your city is considering. For example:
The survey was answered by residents of a mid-sized city. The goal is to identify which types of small business support (e.g., reducing local taxes, storefront grants, marketing support) matter most to citizens and why.
Prompt for a deeper dive on a specific idea: After you’ve identified a core idea, ask “Tell me more about XYZ (core idea)” to have the AI elaborate or surface supporting quotes.
Prompt for specific topic: This is especially useful to test assumptions or validate trends you think are emerging. Just ask: Did anyone talk about XYZ? For richer insights, add “Include quotes.”
Prompt for pain points and challenges: Use this when you want to surface what frustrates citizens about local small business life or existing support options.
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 personas: Understand different citizen archetypes and what motivates them.
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.
Prompt for sentiment analysis: This tells you how people feel—positive, negative, or neutral—about small business support proposals.
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.
For even more prompt inspiration, you can check guides on how to create a citizen survey or best questions for small business support surveys.
How Specific analyzes survey data by question type
Specific makes sense of your citizen survey data by breaking it down by question type, letting you quickly spot themes and act on what matters most for small business support:
Open-ended questions with or without follow-ups: The platform summarizes all responses and builds a picture of each related follow-up—no more reading every comment one-by-one.
Choices with follow-ups: Each answer choice gets a separate summary, so you can see the reasoning behind every preference (e.g., why citizens favor grants vs. tax relief).
NPS questions: For Net Promoter Score items, Specific separates analysis by group: detractors, passives, and promoters. Each group’s follow-up answers are summarized in context, making it easy to know why people gave their scores.
If you want to do this in ChatGPT, it’s possible, but requires manual filtering and prompt crafting for each segment or question.
How to handle AI context limits with big citizen survey data
AI models like GPT always have a context size limit—they can only “see” so much of your data at once. If your citizen survey collected hundreds or thousands of replies, the model might run out of capacity. Here’s how you can handle it (and how Specific does it by default):
Filtering: Narrow down the sample. Filter responses so AI looks only at conversations where people replied to your selected questions or picked certain options. This way, you focus the analysis—and never hit the limit.
Cropping: Select just the most important questions. Crop out the rest so AI only gets the chunks you want it to analyze. More data fits; you get focused, relevant insights.
This targeted approach is essential when you conduct broad-reaching citizen surveys, and it’s embedded in Specific’s workflow for AI-powered survey response analysis. More on this in the AI survey analysis feature guide.
Collaborative features for analyzing citizen survey responses
Anyone who’s worked with a small business support survey knows that reviewing responses, sharing takeaways, and collaborating on insights can be a headache—especially with multiple stakeholders in the loop.
Chat-powered collaboration: With Specific, teams don’t need to dump survey responses into email threads or messy spreadsheets—they can simply chat with the AI, using real language, and get instant analysis.
Multiple simultaneous chats: You and your colleagues can launch separate, focused chats—each with unique filters (like “only show NPS promoters” or “only responses about local tax relief”). Each chat clearly shows who started it, so everyone understands who explored what, reducing duplicate effort.
Clear user identity in collaboration: When collaborating, you always see who’s authored each AI chat message; avatars show contributors at a glance. This makes cross-departmental feedback faster and more transparent—and you’ll never lose context.
Learn more about collaborative features and workflow for AI survey response analysis or get inspired by practical examples in the interactive survey demos.
Create your citizen survey about small business support now
Get meaningful input from citizens and unlock actionable insights on small business support decisions—Specific’s AI survey tools do the heavy lifting so you can focus on impact. Create your survey today and see what your community really thinks.