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Customer Support Agent Interaction Feedback

Captures how a specific customer support interaction went — channel used, resolution, effort, and how the agent performed on key behaviors — with an AI follow-up that digs into the real reason behind the satisfaction score, not just the number. Built for support ops and CX teams tracking agent quality over time.

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Sample questions

A preview of what’s in the template. Every question is editable before you launch.

12 questions · ~7 min
Q01
Message

Thanks for taking a moment to tell us about your recent support interaction! This will take about 7 minutes and helps us coach and recognize our support team.

Q02
Multiple ChoiceRequired

Which channel did you use to contact support this time?

  • Phone
  • Live chat
  • Email
  • Social media
  • In-app messaging
  • In person
Q03
Opinion ScaleRequired

Overall, how satisfied were you with the agent who handled your request?

Scale: 1 – 5
Min:Very dissatisfiedMax:Very satisfied
Q04
Multiple ChoiceRequired

Was your issue resolved during this interaction?

  • Yes, fully resolved
  • Partially resolved
  • No, still unresolved
  • It's still being worked on
Q05
Opinion ScaleRequired

How much personal effort did it take on your end to get your issue handled?

Scale: 1 – 7
Min:Very low effortMax:Very high effort
Q06
MatrixRequired

Thinking about the agent specifically, how much do you agree with each statement?

5 rows × 5 columns
  • Listened to and understood my issue
  • Was knowledgeable about my problem
  • Communicated clearly
  • Kept me updated on progress
  • Resolved things efficiently, without unnecessary back-and-forth
Columns: Strongly disagree · Disagree · Neutral · Agree · Strongly agree
Q07
Best–Worst Trade-off (MaxDiff)Required

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

  • Speed of resolution
  • Agent's product knowledge
  • Friendliness and empathy
  • Clear communication
  • Being kept informed of progress
  • Not having to repeat myself
  • Getting it right on the first contact
  • Follow-up after the issue is closed
Pick best & worst per setBest:Matters mostWorst:Matters least
Q08
AI Interview

Explore the real story behind the respondent's satisfaction and effort scores for this specific interaction: what exactly the agent did or said that stood out, and whether the issue was actually resolved to their satisfaction. If satisfaction or effort was poor, anchor on the specific moment things went wrong and what the agent could have done differently. If the issue is still unresolved, probe what 'resolved' would even look like for them. Keep it grounded in this one interaction, not support in general.

Q09
Opinion Scale

Based on this interaction, how likely are you to continue doing business with us?

Scale: 0 – 10
Min:Not at all likelyMax:Extremely likely
Q10
Long Text

Is there anything specific the agent or our support team should know — good or bad — about this interaction?

Q11
Multiple Choice

How often have you contacted our support team in the last 6 months?

  • This was my first time
  • 2-3 times
  • 4-6 times
  • More than 6 times
  • Prefer not to say
Q12
Message

That's everything — thank you! Your feedback goes directly to our support quality team and helps us coach and recognize agents.

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

  • Captures the full interaction context in one flow — channel used, resolution status, effort, and agent-specific behavior ratings via a matrix question, not just a single satisfaction number
  • An AI follow-up interview automatically probes the real reason behind a respondent's satisfaction and effort scores instead of leaving low scores unexplained
  • Includes a max-diff question to prioritize what matters most to customers when contacting support, giving support ops a ranked view rather than just averages
  • Ends with an open long-text question inviting specific praise or concerns about the agent, plus automated quality scoring and an auto-generated report for tracking agent quality over time

SurveySparrow

Customer Support Agent Feedback Template

A ready-to-field template focused specifically on rating individual support agents, which makes it directly comparable to our template. It likely covers satisfaction and agent behavior ratings but relies on fixed question sets rather than adaptive probing. No public pricing tier for academic/nonprofit use is indicated.

What it does well

  • Purpose-built specifically for agent-level feedback, matching the use case closely
  • Likely supports conversational/chat-style survey delivery given SurveySparrow's product positioning
  • Fielding-ready template that can be deployed quickly

Where it falls short

  • Static question flow with no adaptive AI follow-up to dig into the reasons behind a satisfaction score
  • No mention of automated per-response quality scoring for support ops tracking
  • No transparent prompt methodology published for any AI-assisted features

QuestionPro

Customer Support Service Evaluation Survey Template

This is a broader service-evaluation template rather than one focused tightly on a single agent interaction, but it's a reasonable comparable for support quality feedback. It appears to be a standard fielding-ready survey template with fixed questions. As with most enterprise survey tools, deeper analysis likely requires manual review or add-on modules.

What it does well

  • Enterprise-grade survey platform with broad customization options
  • Template appears to cover general service evaluation, useful for high-level CX tracking
  • Backed by QuestionPro's established survey logic and reporting tools

Where it falls short

  • No adaptive AI interview to explore the 'why' behind scores — respondents only answer pre-set questions
  • No voice AI interview option or guided screen-share tasks
  • No automated per-response quality scoring built into the template itself

SurveyMonkey

Customer Service Survey Template (With Questions)

A general customer service feedback template rather than one focused specifically on a single agent interaction with follow-up prompts. It's a solid fielding-ready starting point with standard question types. Its scope is broader and shallower than our agent-specific, interaction-level template.

What it does well

  • Well-known, easy-to-use platform with broad template library
  • Likely includes standard satisfaction and effort-style questions
  • Simple to deploy for teams already using SurveyMonkey

Where it falls short

  • No adaptive AI follow-up interview to probe reasons behind satisfaction or effort scores
  • No agent-specific behavioral matrix or prioritization (max-diff) question apparent
  • No automated quality scoring or auto-generated reports built for ongoing agent-quality tracking

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