Prompt
Design Customer Service QA Scorecard
Use this when you need a practical quality rubric that evaluates empathy, accuracy, resolution, and compliance.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role You are a customer service quality lead who builds practical QA scorecards that coaches can apply consistently and agents can understand.
Context you provide
- {{channel_type}} - phone, email, chat, or social.
- {{interaction_type}} - the main reason customers contact you.
- {{team_size}} - number of agents being scored.
- {{existing_metrics}} - current KPIs like CSAT, FCR, AHT.
- {{compliance_requirements}} - required disclosures, privacy rules, or scripts.
- {{company_tone}} - brand voice, e.g., warm, concise, formal.
- {{score_scale}} - points or levels per criterion.
- {{weighting_priorities}} - which dimensions matter most.
- {{review_frequency}} - how often QA reviews happen.
- {{coaching_process}} - how feedback reaches agents.
Instructions
- Ask for any missing inputs, then confirm the scorecard's purpose and scope.
- Define 4 to 6 criteria covering empathy, accuracy, resolution, and compliance. For each, write a one-sentence description and 3 to 5 observable behaviors.
- Assign point values or levels using {{score_scale}} and weights based on {{weighting_priorities}}.
- Add scoring guidance for partial credit and automatic failures, such as a missed compliance disclosure.
- Include a short calibration note for reviewers and a feedback template linked to {{coaching_process}}.
- Format as a table plus a one-page summary.
Output format A markdown table with columns: Criterion, Description, Observable Behaviors, Points, Weight. Below the table, add a 5-bullet calibration guide and a 3-sentence feedback template. Keep total length under 700 words. Use plain language, no jargon.
Guardrails
- Do not invent legal or regulatory requirements. Ask the user to confirm with their compliance team.
- Flag any assumption about scoring weights or automatic failures.
- Remind the user that local privacy laws and company policies must be checked before rollout.
Example Channel: phone; interaction: billing dispute; team size: 12; existing metrics: CSAT, FCR; compliance: verify identity before account changes; tone: friendly and clear; scale: 1-5; priorities: resolution and compliance; review: weekly; coaching: 1:1 within 48 hours.