Best questions for user survey about support experience

Here are some of the best questions for a user survey about support experience, plus quick tips on crafting yours. With Specific, you can build these surveys in seconds and instantly start gathering quality insights.

Best open-ended questions for user survey about support experience

Open-ended questions help us dig into the real stories behind a user’s support experience. They bring rich, qualitative data, offer unexpected insights, and reveal the “why” behind user behavior—absolutely critical for improving support and gaining loyalty. While open-ended questions take a bit longer to answer than multiple-choice, the trade-off is invaluable feedback you’d never otherwise hear. That’s why we always use a combo of both question types for depth and structure in surveys, making the results easy to analyze and compare. Research shows that while multiple-choice speeds up response time, open-ends help you discover what you wouldn’t even think to ask. [1]

1. Can you describe the support experience you recently had with us?

2. What was the biggest challenge you faced when interacting with our support team?

3. How did our support team meet—or not meet—your expectations?

4. What stood out most about your support interaction?

5. Was there anything that surprised you during the support process?

6. What, if anything, made your support experience frustrating?

7. If you could change one thing about our support, what would it be?

8. How does our support compare with other companies you’ve interacted with?

9. What’s one thing our support team did especially well?

10. Is there anything you wish our support team asked or noticed during your recent conversation?

To generate variations or expand with follow-up logic, use the AI survey builder from Specific—or customize questions further with our AI survey editor for more nuanced probes.

Best single-select multiple-choice questions for user survey about support experience

Single-select multiple-choice questions are perfect when you want quantifiable trends, or need to nudge hesitant users into sharing feedback. Users can answer in seconds, helping boost response rates and making it easier to spot key patterns across groups. Because they’re quick and easy, respondents feel less friction—yet you can always follow up for more detail, keeping the conversation rich. In one study, multiple-choice survey-takers finished their surveys much faster than with open questions, with no drop in learning or accuracy. [1]

Question: How satisfied were you with your recent support interaction?

• Very satisfied

• Satisfied

• Neutral

• Dissatisfied

• Very dissatisfied

Question: Which aspect of the support experience mattered most to you?

• Speed of response

• Clarity of communication

• Knowledge of support team

• Solution effectiveness

• Other

Question: How likely are you to contact our support team again if you have an issue?

• Very likely

• Somewhat likely

• Not sure

• Unlikely

• Very unlikely

When to followup with "why?" Don’t hesitate to ask “why?” right after a choice—especially if someone is dissatisfied, or selects the most/least extreme option. For example, if a user chooses “Dissatisfied,” immediately prompt "Can you share what led to your dissatisfaction?" This nudges them to share context you’d otherwise miss.

When and why to add the "Other" choice? The “Other” option is excellent when you’re not sure you’ve captured every scenario in your choices. It opens the door for unexpected insights, and an automatic follow-up can ask for specifics to add even richer understanding.

Should you use NPS in a support experience survey?

NPS (Net Promoter Score) questions are a gold standard for understanding overall loyalty and are highly effective in support experience surveys. The single question—"How likely are you to recommend our company to a friend or colleague?”—gives you a clear sense of whether users see your support as a differentiator or a pain point.

• Average NPS across industries is 32, with top companies scoring 72 or higher. But in technology and services, the average is 64—which means support plays a massive role in separating great companies from good ones. [2]

• Promoters (those scoring 9-10) are 4.2x more likely to buy again and 7.2x more likely to try a new offering, showing a direct link between support quality, loyalty, and revenue growth. [4]

For a ready-made NPS question (and smart follow-ups for promoters, passives, or detractors), try the NPS survey generator for users about support experience from Specific.

The power of follow-up questions

Follow-up questions are where surveys move from data collection, to actual conversations. Automated follow-ups probe for clarity, context, or detail—like a smart interviewer. This not only enriches the insights, but makes the respondent feel heard. Specific’s automated AI follow-up feature crafts follow-ups live, asking just what’s needed based on the previous answer, in a way that’s impossible with traditional survey forms.

This real-time probing saves time (think: you don’t need to follow up by email later) and keeps feedback fresh and specific. Here’s what happens if you skip good follow-ups:

• User: “The support was okay.”

• AI follow-up: “When you say 'okay', can you share what could have made your support experience excellent?”

That’s the difference between vague and actionable feedback.

How many followups to ask? Generally, two to three follow-ups per answer strike a good balance—enough for depth without feeling intrusive. It’s worth letting users skip to the next question if you already have what you need. On Specific, you can easily set and manage these preferences for a more personal or efficient experience.

This makes it a conversational survey. You’re not sending a static form; you’re creating a dynamic, real-time interview that feels less like paperwork, more like a chat—keeping users engaged and thoughtful in their responses.

AI survey analysis is easy. Even though there’s a lot of unstructured text, AI-powered analytics (like those in Specific’s response analysis tool) make it simple to summarize, find key themes, and highlight trends. No manual coding needed—you can analyze responses as quickly as you gather them.

These automated follow-up questions are a game-changer—try generating a survey and see how much deeper your insights get without extra overhead.

Great prompts for ChatGPT or GPT-4 to generate user survey about support experience

If you're using ChatGPT or any GPT-based tool to brainstorm survey content, simple prompts are a good start. For example:

Suggest 10 open-ended questions for user survey about support experience.

This works, but you get even better results if you give more context—describe your company, users, any recent issues, and what you hope to learn:

I work for a SaaS company that serves small business owners. We want to understand pain points in our support experience to improve satisfaction and retention. Suggest 10 open-ended questions that explore user perceptions, expectations, and comparisons with competitor support.

Next, use the AI to help you organize your questions and uncover topic areas you might have missed:

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

Finally, take those categories, pick the ones that matter most, and double-click with:

Generate 10 questions for categories "response speed" and "solution quality."

This modular approach surfaces a greater range of topics and lets you steer the conversation toward the issues that matter most to your users.

What is a conversational survey?

A conversational survey is a new breed of surveys—AI-powered, chat-like, and interactive. Instead of static forms, these surveys adapt in real time, ask tailored follow-up questions, and build a genuine back-and-forth. The result: users feel engaged, and you get richer, more honest feedback.

If you’ve ever compared building a manual form-based survey with an AI survey generator, you know the pain: traditional surveys are slow to build, static in logic, and tough to personalize. AI-powered surveys, especially in Specific, take your simple prompt and spin up a full survey—complete with structure, tone, and smart logic—within minutes. They’re especially powerful for support experience, where each reply can open new avenues to explore.

Why use AI for user surveys? You get speed, depth, and personalization that simply aren’t possible with traditional survey makers. AI survey examples show higher engagement rates, deeper insights, and less user drop-off. Plus, with Specific, the whole experience—creation, delivery, and analysis—is smooth for both creators and respondents, whether on mobile or desktop. Want to dig deeper? Check this guide on how to create a user survey about support experience with Specific.

See this support experience survey example now

Choose a better way to listen—see what a conversational support experience survey looks like in action and start seeing insights you can act on today. Specific helps you uncover richer stories, automate probing for honest feedback, and transform your survey data into action, all in one seamless flow.