Best questions for citizen survey about street lighting

Here are some of the best questions for a citizen survey about street lighting, plus expert tips on crafting effective feedback questions. You can build a citizen street lighting survey in seconds with Specific—our conversational AI platform makes it easy for anyone to get started.

Best open-ended questions for a citizen survey about street lighting

Open-ended questions are powerful for understanding the “why” behind public opinions. They let citizens express themselves in their own words—adding valuable context you simply don’t get from yes/no or check-box options. Use open-ended questions when you want deeper, more nuanced feedback. Here are our top 10 for citizen feedback on street lighting:

1. What are your main concerns about street lighting in your neighborhood?

2. Can you describe a time when street lighting (or the lack of it) affected your sense of safety?

3. How would you rate the current brightness and coverage of street lighting in your area, and why?

4. What improvements would you like to see regarding street lighting near your home?

5. In which locations do you feel street lighting is most lacking or unnecessary?

6. How do changes in street lighting affect your usual activities, like walking, biking, or driving at night?

7. Have you noticed any correlation between lighting and incidents of crime or road safety?

8. What impact do you think improved street lighting could have on your community?

9. Are there any negative effects of street lighting in your area (e.g., light pollution or disrupted sleep)?

10. What’s one thing you wish city planners knew about street lighting where you live?

Open questions let us discover not just complaints, but stories, suggestions, and the real “why” beneath citizen opinions. This context is crucial because, for example, studies have found that improved street lighting can reduce property and violent crimes by 21%—but impacts can vary depending on local context [1].

Best single-select multiple-choice questions for a citizen survey about street lighting

Single-select multiple-choice questions are your go-to when you want to quantify feelings, recognize trends, or kick off a conversation. Some citizens find it easier to choose from options, which helps break the ice for longer surveys—especially when followed by open-ended or “why” questions to dig deeper. Here are three examples:

Question: How satisfied are you with the street lighting in your neighborhood?

• Very satisfied

• Satisfied

• Neutral

• Dissatisfied

• Very dissatisfied

Question: Which aspect of street lighting concerns you the most?

• Not enough light in key areas

• Lights are too bright

• Frequent outages

• Light pollution or glare

• Other

Question: Do you believe street lighting has an impact on local crime rates?

• Yes, reduces crime

• No, has no effect

• May increase crime

• Not sure

When to follow up with “why?” It’s key to ask “why” after a multiple-choice response—especially if someone indicates dissatisfaction or unique concerns. For example: if a citizen selects “Dissatisfied,” we’d follow up with, “Why do you feel this way about street lighting in your area?” This reveals root causes, whether that’s safety, visibility, cost concerns, or other factors. In fact, context-driven follow-ups help explain why some studies show lighting dramatically cuts crime [1][2], while others like in Seattle or England show less direct impact [3][4]—local nuance matters.

When and why to add the “Other” choice? Always include “Other” when you want to capture concerns or ideas not covered by predefined choices. Following up after an “Other” answer often leads to insights you didn’t anticipate. It’s a proven way to uncover hidden pain points or innovations residents are thinking about.

NPS questions for street lighting feedback

The Net Promoter Score (NPS) is a classic, but surprisingly versatile, format for city feedback. It asks, “How likely are you to recommend this service…” on a scale from 0 to 10. Using NPS for citizen street lighting surveys works because it boils satisfaction down to a single number, then invites deeper feedback. You can uncover both promoters (“excellent lighting, I feel safe!”) and detractors (“too many dark spots, unsafe after dark”), and immediately follow up to learn what drives those ratings.

You can generate a ready-made NPS survey for street lighting with Specific in seconds, complete with tailored follow-ups based on each respondent’s score.

The power of follow-up questions

Follow-up questions are where the magic of conversational surveys happens. Automated AI follow-ups let us clarify, probe for specifics, and understand the true “why” behind each citizen’s answer—all in real-time, without chasing people down later. With Specific, our AI engages respondents naturally, mimicking the flow of an expert interview and ensuring we don’t miss context. It also saves researchers huge amounts of back-and-forth via email or phone.

• Citizen: “The lights don’t make me feel safe.”

• AI follow-up: “Can you share a specific example or area where lighting felt inadequate?”

How many followups to ask? In most surveys, 2–3 follow-ups are enough to capture context without fatiguing respondents. Specific lets you configure how persistent the AI should be—and it’s smart enough to move on once it’s got the answer you need.

This makes it a conversational survey: The interaction feels like a dialogue, not a form—a proven way to increase both the volume and quality of citizen feedback.

AI makes analyzing open responses easy: With tools like AI survey response analysis and citizen survey analysis guides, digging through dozens of text comments becomes simple. AI summarizes, finds themes, and surfaces insights, even with a lot of unstructured text to review.

These automated, context-aware follow-ups are still new—try generating a survey and you’ll quickly see how much richer (and clearer) the responses can get, even with brief citizen feedback conversations.

How to prompt ChatGPT to generate survey questions about street lighting

Crafting the perfect survey takes a good prompt—especially with AI tools like ChatGPT or GPT-4. Start simple:

Suggest 10 open-ended questions for citizen survey about street lighting.

The more context you provide about your project or goals, the better the output. Try adding detail:

I am a city manager aiming to improve public safety and well-being via urban lighting upgrades. Suggest 10 detailed open-ended questions for a citizen survey about street lighting that will help me understand local priorities, concerns, and desired improvements.

Once you have a draft set of questions, ask the AI to categorize them:

Look at the questions and categorize them. Output categories with the questions under them.

Review the categories—maybe “safety,” “environment,” and “operations”—then dive deeper with:

Generate 10 follow-up questions for the category "safety and security" related to street lighting.

This stepwise approach leads to a survey that feels thoughtful, complete, and relevant to local needs.

What is a conversational survey?

A conversational survey isn’t just a form. It feels like a dialogue—dynamic, context-aware, and probing, just as a skilled interviewer would be. Manual surveys are rigid: they ask a set question list, often in bulk, and rarely adjust to the nuances of each respondent’s reply. With an AI survey generator like Specific, the experience is tailored, with the AI adjusting questions and follow-ups in real time for deeper insight.

Why use AI for citizen surveys? AI survey tools are fast, customizable, and create a better respondent experience. They help us capture data we’d otherwise miss, like nuanced complaints or creative suggestions. Tools like Specific offer best-in-class survey UX—guiding both creators and citizens through a smooth, mobile-friendly conversation that delivers authentic feedback, every time. If you’re curious how easy it is, check out our guide to making surveys, or try the AI survey editor to instantly update questions in plain language.

It’s the fastest, most robust way to collect and understand feedback in 2024—no more hours spent wrangling spreadsheets, just clear themes and actionable insights.

See this street lighting survey example now

Take the first step to better feedback with a smart, conversational survey about street lighting. In just minutes you can capture real public opinion and go beyond the basics, with context-aware follow-ups and powerful AI-driven analysis.