Q01
Message
All templatesCustomer 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.
Sample questions
A preview of what’s in the template. Every question is editable before you launch.
13 questions · ~7 min
Q02
Multiple ChoiceRequired
How did you contact our technical support team for this issue?
- Live chat
- Phone
- Support ticket / help portal
- Social media
- In-person / on-site
Q03
Multiple ChoiceRequired
Was your issue fully resolved?
- Yes, fully resolved
- Partially resolved
- Not resolved
- Still waiting on a resolution
Q04
Opinion ScaleRequired
Overall, how satisfied were you with this support interaction?
Scale: 1 – 7
Min:Very dissatisfiedMax:Very satisfied
Q05
Opinion ScaleRequired
How much personal effort did it take on your part to get this issue resolved?
Scale: 1 – 7
Min:Very high effortMax:Very low effort
Q06
MatrixRequired
How much do you agree with each statement about the support agent(s) you worked with?
4 rows × 5 columns
- 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
Columns: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q07
Best–Worst Trade-off (MaxDiff)Required
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
Pick best & worst per setBest:Matters mostWorst:Matters least
Q08
Number
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 Interview
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
Long Text
Is there anything specific we could have done differently to improve this support experience?
Q11
Multiple Choice
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
Multiple Choice
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
Message
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.
What’s included
AI follow-ups
Adaptive probes on open-ended answers that pull out detail a static form would miss.
Attention checks
Built-in safeguards against rushed answers and low-quality respondents.
AI-drafted copy
Wording, ordering, and branching written by the AI — tuned to your research goal.
Auto report
Themes, quotes, and a plain-English summary write themselves once responses come in.
How it compares
We reviewed the closest templates from other survey tools. Here’s what they do well — and where this template goes further.
Why this template
- 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 TemplateThis 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.
What it does well
- 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
Where it falls short
- 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 TemplateA 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.
What it does well
- 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
Where it falls short
- 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
Ready to launch?
Open this template in the editor. Every part is yours to change before the first respondent sees it.
Related templates
More studies from the same category.
Customer Experience
Short Customer Satisfaction Pulse Survey
A fast, 2-3 minute check-in that captures overall satisfaction, likelihood to recommend, and satisfaction with specific touchpoints — with an AI follow-up that digs into the real reason behind each score instead of just the number. Built for post-purchase, post-support, or quarterly relationship pulses.
View templateCustomer Experience
Donor Loyalty Acid Test
Adapts the classic loyalty acid test — would they recommend, give again, defend you, forgive a mistake — for nonprofit donors and supporters. Includes an AI follow-up interview that digs into the real reasons behind a donor's loyalty score, especially for lukewarm or at-risk givers, so fundraising teams know what to fix before the next campaign.
View templateCustomer Experience
Customer Registration Experience Survey
Measures how easy, fast, and frustration-free your sign-up or account creation flow actually is, pinpointing which steps cause drop-off. An AI follow-up interview reconstructs the exact moment a respondent almost gave up, going beyond satisfaction scores to the specific friction that needs fixing.
View templateCustomer Experience
Web Customer Service Experience Evaluation
Evaluates a recent online support interaction — channel used, resolution, effort, and satisfaction — for teams running live chat, email, or chatbot support. An AI follow-up interview digs into what actually happened during the contact so low scores come with a specific, fixable story instead of just a number.
View templateCustomer Experience
Open Customer Comments & Feedback Deep-Dive Survey
Turns a single piece of customer feedback into a structured signal — capturing what prompted the comment, rating the specific aspects of the experience behind it, and using an AI follow-up interview to reconstruct the exact moment, cause, and fix. Built for support, CX, and product teams triaging open-ended comments.
View templateCustomer Experience
Customer Contact & Support Channel Experience Survey
Captures how customers actually reach you for help, how easy and effective that contact was, and which channels they'd pick again — with an AI follow-up that reconstructs their most recent support interaction in detail instead of relying on vague satisfaction ratings.
View template