Quality & Coaching
Everything we've written on quality & coaching.
Using AI to Pre-Score Conversations for Human Review
Let AI propose a first assessment, then spend reviewer time checking evidence, calibrating judgment, and coaching.
From Spot-Checks to Full Coverage: A QA Maturity Model
Where is your QA program today, and what's the next stage? A maturity model to find out.
How to Score Empathy and Tone Without Being Arbitrary
Tone is the hardest thing to grade fairly. Here's how to make it concrete.
Pass/Fail vs. Weighted Scores: Which QA Model Is Right for You
Holistic 1-5 scores feel fair but hide failures. Here's when category-weighted pass/fail wins.
The Conversation Quality Metrics That Actually Predict Churn
Not every QA category matters equally. These are the ones that move retention.
QA for AI Agents: Scoring Conversations a Bot Handled
Your AI agent needs the same scrutiny as your team. Here's how to QA what it handled.
Coaching From Scores: Turning QA Data Into Better Reps
Scores are only useful if they change behavior. Here's how to coach from them weekly.
Calibration Sessions: Getting Your QA Scorers to Agree
If two reviewers score the same chat differently, your scores are noise. Calibration fixes that.
How to Build a Support QA Rubric Your Team Won't Argue With
A good rubric is specific, weighted, and fair. Here's how to write one reps trust.
Conversation QA Coverage: What a Sample Can Miss
Broader scoring can reveal more patterns. Measure coverage and scoring accuracy before treating it as a complete picture.
Broader Conversation QA. Better Questions to Ask.
Use AI scoring to widen the reviewable evidence, then check coverage, calibration, and what your team does with the finding.