Quick answer
For example, use QA scorecard for sharing/archiving: back up, export to the target format and spot-check 2-3 files. Turn service expectations into observable, reproducible scoring items.
Why it matters
Real scenarios expose problems better than abstract specs.
Items need behavioral anchors, not vague labels like 'good attitude'.
Step by step
- Define QA goals and observable behaviors before building a giant scorecard.
- Stratify samples by shift, channel and risk so they represent real problems.
- Calibrate scoring boundaries before ranking or performance decisions.
- Attribute issues to knowledge, process, system or people before choosing fixes.
Common mistakes
- Scoring without calibration makes managers incomparable.
- Sampling only easy tickets biases the result.
- Using QA as punishment makes agents hide context.
- Looking only at CSAT while ignoring resolution and rework.
Checklist
- Scorecard has behavioral anchors.
- Sampling has stratification rules.
- Calibration records disputed samples.
- Issues have owners and review dates.
Key facts
- Items need behavioral anchors, not vague labels like 'good attitude'.
- Weight by business risk; refunds, privacy and safety usually outrank small talk.
- Record written rulings for disputed samples so calibration stays consistent.
FAQ
Can you show a QA scorecard example?
For example, use QA scorecard for sharing/archiving: back up, export to the target format and spot-check 2-3 files. Turn service expectations into observable, reproducible scoring items.
How long does it take?
Usually 1-3 minutes; for intermittent issues, run 30 seconds and retest elsewhere.
Is data uploaded?
Runs locally and does not upload video/audio; extensions may still read the page.
Source: Zendesk QA