Quick answer
QA sampling is the core object here; understand the problem it solves before choosing a tool or workflow. Sample for risk, channel and people, not just the most recent tickets.
Why it matters
Without the concept, format, permission or compatibility issues are easily misread as tool failures.
Stratify by channel × issue × severity × agent.
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
- Stratify by channel × issue × severity × agent.
- Review 100% of high-risk tickets.
- Check monthly whether the sample covers the long tail.
FAQ
What is QA sampling?
QA sampling is the core object here; understand the problem it solves before choosing a tool or workflow. Sample for risk, channel and people, not just the most recent tickets.
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: MaestroQA sampling