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Employee & HR

Call Center Agent Performance Evaluation Survey

A supervisor-facing evaluation of a call center agent's call quality, adherence, and soft skills, paired with a best-worst training-priority ranking and an AI follow-up interview that reconstructs a specific recent call to explain the reasoning behind the ratings. Built for team leads and quality analysts running periodic performance reviews.

Sample questions

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

13 questions · ~7 min
Q01
Message

Thanks for taking a few minutes to evaluate this agent's recent performance. Your honest, specific feedback helps shape coaching and training decisions. Your responses are completely confidential and anonymized. This should take about 6 minutes.

Q02
Short TextRequired

Which agent are you evaluating? (Name or employee ID)

Q03
Short TextRequired

What period does this evaluation cover? (e.g., 'Q3 2024' or 'last 30 days')

Q04
MatrixRequired

Based on calls you've monitored or reviewed this period, rate this agent on each dimension.

6 rows × 3 columns
  • Professionalism and tone
  • Active listening
  • Accuracy of information provided
  • Issue resolution effectiveness
  • Adherence to scripts and processes
  • +1 more
Columns: Needs improvement · Meets expectations · Exceeds expectations
Q05
Opinion ScaleRequired

Overall, how would you rate this agent's call handling quality this period?

Scale: 110
Min:PoorMax:Excellent
Q06
Multiple ChoiceRequired

In the last 30 days, how often did this agent adhere to their scheduled shift and break times?

  • Always
  • Most of the time
  • Sometimes
  • Rarely
  • Never
Q07
Rating Scale

How would you rate this agent's teamwork and collaboration with peers and other departments?

Range: 15
Min:PoorMax:Excellent
Q08
Best–Worst Trade-off (MaxDiff)Required

Which training areas are most and least urgent for this agent right now?

  • Product knowledge
  • De-escalation and conflict handling
  • Systems and software proficiency
  • Compliance and script adherence
  • Time management and call efficiency
  • Communication clarity
  • Upselling or cross-selling technique
Pick best & worst per setBest:Most urgent training needWorst:Least urgent training need
Q09
AI Interview

Ask the supervisor to walk through one specific recent call from this agent that stands out, good or bad, and reconstruct exactly what happened: what the customer needed, how the agent handled it, and what the outcome was. Probe for concrete behavioral detail behind the lowest-rated dimension in the earlier ratings rather than general impressions. If the supervisor gives conflicting signals (e.g., high overall quality but low adherence), ask them to reconcile the two directly.

Q10
Long Text

Any other specific examples worth noting — an exceptional save, a difficult call, or a recurring issue?

Q11
Multiple Choice

What is your role relative to this agent?

  • Team lead
  • Quality analyst
  • Operations manager
  • Other
  • Prefer not to say
Q12
Dropdown

How long have you been directly supervising or reviewing this agent?

  • Less than 3 months
  • 3-6 months
  • 6-12 months
  • 1-2 years
  • Over 2 years
  • Prefer not to say
Q13
Message

Thank you for completing this evaluation. Your ratings and comments will feed directly into this agent's coaching plan and the next training cycle.

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 a supervisor-facing matrix and rating scales covering call quality, adherence, and teamwork alongside a best-worst max-diff ranking to pinpoint the single most urgent training priority
  • Pairs static ratings with an AI follow-up interview that has the supervisor reconstruct one specific recent call, surfacing the reasoning and context behind the scores rather than just the numbers
  • Captures rater context (role relative to agent, tenure supervising) so results can be segmented and trusted, plus an open-ended field for exceptional saves or difficult calls
  • Feeds directly into an auto-generated report, with transparent prompts showing exactly how the AI follow-up was conducted for this evaluation cycle

Jotform

Call Center Employee Evaluation Form Template

A fielding-ready, customizable form builder template covering standard call center evaluation criteria like communication and professionalism. It's built for quick deployment and integrates with Jotform's broader form ecosystem, but it's a static rating form rather than an interview-driven evaluation.

What it does well

  • Ready-to-use drag-and-drop template with broad form-building customization
  • Part of a mature form platform with wide integration options
  • Likely supports conditional logic for basic branching

Where it falls short

  • No adaptive AI follow-up questioning to probe the reasoning behind ratings
  • No mechanism to reconstruct or discuss a specific recent call in the supervisor's own words
  • No published prompt-level methodology or transparency into how responses are scored

SurveySparrow

Call Center Employee Evaluation Template

A conversational-style survey template aimed at call center employee evaluations, leveraging SurveySparrow's chat-like UI for a more engaging respondent experience. It covers standard evaluation dimensions but remains a fixed-question format without follow-up probing.

What it does well

  • Conversational, chat-style survey format that may improve completion rates
  • Fielding-ready template requiring minimal setup
  • Likely includes basic scoring/reporting dashboards

Where it falls short

  • No adaptive AI interview to dig into specifics of a particular call
  • No best-worst/max-diff style prioritization for training needs
  • No transparent, published prompt methodology for how follow-up or scoring works

Typeform

Call Center Employee Evaluation Form Template

A polished, fielding-ready form built on Typeform's signature one-question-at-a-time interface, suited for call center performance reviews. It emphasizes design and respondent experience but relies on fixed questions rather than dynamic follow-up.

What it does well

  • Clean, high-completion-rate one-question-at-a-time interface
  • Fielding-ready with minimal setup required
  • Established platform with logic jumps for basic branching

Where it falls short

  • No AI-driven follow-up interview to reconstruct specific call scenarios
  • No automated per-response quality scoring tied to a defined rubric
  • No voice AI interview option for richer qualitative context

Frequently asked questions

What questions are in the “Call Center Agent Performance Evaluation Survey” template?

The template includes 13 ready-to-use questions, starting with: “Thanks for taking a few minutes to evaluate this agent's recent performance. Your honest, specific feedback helps shape…” · “Which agent are you evaluating? (Name or employee ID)” · “What period does this evaluation cover? (e.g., 'Q3 2024' or 'last 30 days')”. The full set is previewed above, and every question is editable.

How long does this survey take to complete?

Respondents typically finish the 13 questions in about 7 minutes.

Can I customize this template?

Yes — every question, answer option, and the ordering is editable before you launch. You can add or remove questions, or ask the AI editor to rework the survey around your research goal.

Is this template free to use?

Yes. Open it in the editor and start customizing right away — no account required to try it, and the free plan covers launching your survey.

Ready to launch?

Open this template in the editor. Every part is yours to change before the first respondent sees it.

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