Customer Experience

Technical Support Interaction Quality Survey

Measures how well a recent technical support interaction resolved the customer's issue, how much effort it took, and how the agent performed — built for support and CX teams tracking ticket quality beyond a single CSAT number. An AI follow-up interview reconstructs what actually happened on the ticket instead of just the rating given.

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샘플 질문

템플릿에 포함된 내용을 미리 확인해 보세요. 모든 질문은 설문 공개 전에 자유롭게 수정할 수 있습니다.

질문 13개 · 약 7분

Q01

메시지

Thanks for taking a moment to tell us about your recent support experience! This helps us fix what's not working. Your responses are completely confidential and anonymized. About 4-5 minutes.

Q02

객관식필수

How did you contact our technical support team for this issue?

Live chat
Phone
Email
Support ticket / help portal
Social media
In-person / on-site

Q03

객관식필수

Was your issue fully resolved?

Yes, fully resolved
Partially resolved
Not resolved
Still waiting on a resolution

Q04

의견 척도필수

Overall, how satisfied were you with this support interaction?

척도: 1 – 7

최소:Very dissatisfied최대:Very satisfied

Q05

의견 척도필수

How much personal effort did it take on your part to get this issue resolved?

척도: 1 – 7

최소:Very high effort최대:Very low effort

Q06

매트릭스필수

How much do you agree with each statement about the support agent(s) you worked with?

4개 행 × 5개 열

The agent was knowledgeable about my issue
The agent communicated clearly and avoided confusing jargon
The agent was courteous and professional
My issue was handled in a reasonable amount of time

열: Strongly disagree · Disagree · Neutral · Agree · Strongly agree

Q07

최선·최악 선택형(MaxDiff)필수

When you contact technical support, which of these matter most to you, and which matter least?

Fast response time
Resolving the issue on the first contact
Agent's technical knowledge
Clear, jargon-free communication
Proactive follow-up after the ticket closes
Multiple ways to reach support (chat, phone, email)
Empathy and patience from the agent

세트별 최선·최악 선택최선:Matters most최악:Matters least

Q08

숫자

Roughly how many hours passed between when you first reported the issue and when it was resolved (or last updated, if still open)?

Q09

AI 인터뷰

Reconstruct exactly what happened during this respondent's support interaction: what the issue was, what steps the agent took, and where things went smoothly or broke down. If their effort or satisfaction rating was low, or the issue was only partially resolved, dig into the specific moment things went wrong — a hand-off, a repeated explanation, a wrong fix — and what would have prevented it. If everything went well, ask what specifically made it feel effortless so it can be repeated.

Q10

장문형

Is there anything specific we could have done differently to improve this support experience?

Q11

객관식

In the last 90 days, how many times have you contacted our technical support?

None
1-2 times
3-5 times
6 or more times
Prefer not to say

Q12

객관식

Which best describes your role in using our product?

Individual contributor / end user
Manager or team lead
IT / technical administrator
Other
Prefer not to say

Q13

메시지

That's everything — thank you for the honest feedback! Your responses go straight to our support leadership team to improve how we help customers like you.

포함된 기능

AI 후속 질문
정형화된 설문이 놓치는 세부 내용을, 주관식 답변에 맞춰 AI가 심층 질문으로 끌어냅니다.
주의력 확인 장치
성의 없는 답변과 저품질 응답자를 걸러내는 내장 안전장치입니다.
AI가 작성한 문안
문구, 질문 순서, 분기 로직까지 AI가 연구 목표에 맞춰 작성합니다.
자동 리포트
응답이 모이면 주요 주제, 인용문, 이해하기 쉬운 요약이 자동으로 작성됩니다.

다른 서비스와 비교

다른 설문 도구의 가장 유사한 템플릿을 검토했습니다. 그 도구들이 잘하는 점과, 이 템플릿이 한발 더 나아가는 지점을 정리했습니다.

이 템플릿을 선택하는 이유

Includes an AI follow-up interview that reconstructs exactly what happened during the support interaction, rather than relying only on scaled ratings
Pairs standard resolution and satisfaction/effort scales with a matrix on agent behaviors and a MaxDiff to reveal which support qualities customers actually prioritize
Captures resolution time (hours to resolution) and contact frequency in the last 90 days to add operational context beyond a single CSAT score
Closes with an open long-text question inviting specific improvement suggestions, plus a transparent, auto-generated report tying it all together

QuestionPro

Technical Support Satisfaction Survey Questions + Sample Questionnaire Template

This is a genuinely comparable template/questionnaire page covering technical support satisfaction. It offers a standard set of static survey questions and sample question bank rather than a dynamic interview flow. Useful as a question-writing reference but requires manual customization for fielding.

잘하는 점

Provides a ready sample questionnaire specifically for technical support evaluation
Likely offers question-bank flexibility and export options common to QuestionPro's survey builder
Established survey platform with broad question-type support

아쉬운 점

Static question set with no adaptive AI follow-up to probe into what actually happened on a ticket
No mention of voice AI interviews or guided screen-share tasks for reconstructing incidents
No transparent prompt methodology or automated per-response quality scoring

SurveyMonkey

Customer Support Survey Template

A general customer support survey template rather than one focused specifically on technical support tickets, so questions likely address broader service quality rather than issue-resolution mechanics. It's a fielding-ready static template within SurveyMonkey's builder. Good baseline CSAT-style survey but not tailored to technical troubleshooting nuances.

잘하는 점

Fielding-ready template within a widely used, easy-to-deploy survey platform
Likely includes standard CSAT/NPS-style questions applicable across support types
Backed by SurveyMonkey's broad distribution and analytics tools

아쉬운 점

Generic customer support focus, not tailored to technical issue resolution, effort, or ticket-specific timing
No adaptive AI interview or voice AI option to reconstruct the actual support interaction
No automated quality scoring or transparent prompt visibility for responses

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