Customer Service Survey Questions Examples: 40+ Samples by Channel and Industry

The best customer service survey questions are asked within an hour of the interaction, name the specific channel it happened on, and pair one scored question with one open-ended follow-up asking what could have gone better. Below are more than forty examples that follow that pattern, organized by channel (email and ticket support, live chat, phone, self-service) and by industry, plus the writing rules that separate questions customers answer honestly from questions they abandon.

These examples focus on the service interaction itself. For the broader set covering product, onboarding and relationship surveys, see our full library of customer satisfaction survey questions.

What are good customer service survey questions?

Good customer service survey questions are specific to one interaction, answerable in seconds, and free of leading language. The core set is small: how satisfied the customer was with the help, how easy it was to get the issue handled, whether the issue was actually resolved, and an open prompt for what could have been better. Everything else is a variation tuned to the channel or the industry. Here is how the channels differ:

Email and ticket support survey questions

The classic post-ticket survey. Keep it to three or four questions, sent while the resolution is fresh.

• How satisfied were you with the support you received? (1 to 5)
• Was your issue fully resolved? (yes / no / partially)
• How satisfied were you with how long the resolution took? (1 to 5)
• Did the person who helped you understand your problem the first time? (yes / no)
• How many times did you have to contact us about this issue? (1 / 2 / 3 or more)
• Is there anything about this interaction we could have done better? (open text)

Live chat survey questions

Chat surveys fire the moment the conversation ends, so they get the highest response rates of any channel. Two or three questions is the ceiling. The same questions work whether the conversation was handled by a person or by an AI customer service agent; in fact, surveying both with identical questions is the cleanest way to compare their resolution quality.

• How would you rate this chat? (1 to 5)
• How easy was it to get the help you needed today? (1 = very difficult, 7 = very easy)
• Did this conversation answer your question? (yes / no)
• What brought you to chat with us today, and did we handle it? (open text)

Phone support survey questions

Ask by short follow-up text or email right after the call, or with a one-question voice prompt at the end.

• How satisfied were you with the call you just had? (1 to 5)
• How satisfied were you with the time you waited to speak to someone? (1 to 5)
• Did you have to repeat your issue to more than one person? (yes / no)
• Was your issue resolved on this call? (yes / no / a follow-up is needed)
• What is one thing that would have made this call better? (open text)

Self-service and help center survey questions

Embedded on the article or flow itself, these are one-click questions with an optional open field.

• Did this article answer your question? (yes / no)
• How easy was it to find what you were looking for? (1 to 7)
• What were you looking for that this page did not cover? (open text)
• Did you resolve your issue without contacting support? (yes / no)

Sample customer service survey questions by industry

The core questions stay the same; what changes is the vocabulary and the moment that matters. Swap these in where they fit your business.

SaaS and software

• How satisfied are you with the technical accuracy of the answer you received? (1 to 5)
• Did support resolve your issue without requiring a workaround? (yes / no / workaround needed)
• How clear were the steps you were given? (1 to 5)

Ecommerce and retail

• How satisfied were you with how we handled your order issue? (1 to 5)
• How satisfied were you with the return or refund process? (1 to 5)
• Did we resolve your delivery question before your order arrived? (yes / no)

Financial services

• How confident are you that your issue was handled accurately? (1 to 5)
• How clearly did we explain the fees, terms or steps involved? (1 to 5)
• Did you feel your account information was handled securely? (yes / no / unsure)

Healthcare and patient services

• How satisfied were you with the scheduling or billing help you received? (1 to 5)
• How easy was it to reach the right department? (1 to 7)
• Were your questions answered in language you understood? (yes / no)

How do you write customer service survey questions?

Four rules cover almost everything. First, ask about one interaction, not the relationship: "how satisfied were you with the support you received today" beats "how do you feel about our company". Second, never lead: "how amazing was our service" tells the customer the answer you want and produces flattery, not data. Third, match the scale to the metric: satisfaction on 1 to 5, effort on 1 to 7, recommendation on 0 to 10, and keep each scale consistent forever so your trend lines mean something. Fourth, always end with an open question, because the scores tell you where the problem is and only the text tells you what it is.

The follow-up question that carries most of the value

Every example above ends with some version of "what could we have done better". That single open-ended question is worth more than every scored question combined, because it names the cause: the confusing macro, the three transfers, the policy the agent could not override. It is also the question whose answers most teams never read past the first page of the export.

Treat those answers as a dataset, not a suggestion box. Survey analysis software clusters the open responses into counted themes and ties them to the tickets and accounts behind them, and pairing that with support ticket analysis shows whether the themes customers report match the themes actually driving your ticket volume. When 40 percent of "what could be better" answers and 25 percent of tickets point at the same broken flow, that is not a support problem anymore; it is next sprint's roadmap item.

UserInsight closes that loop in one place: it runs the post-service surveys from the examples on this page, themes the open-ended answers automatically, reads them alongside your tickets and reviews, and joins all of it to what those customers do in your product, on aggregate, consented data with no PII, every finding traced to its source.