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.
A monthly handful of reviews can tell you what happened in those conversations. It may leave your team short of evidence when the question is broader: which topics cause trouble, where expectations slip, or whether a fix helped.
AI scoring can widen the set of conversations your reviewers can inspect. The value comes from the evidence and the decisions it supports, not the scoring percentage alone.
Ask about coverage first
A scoring workflow needs a supported channel, usable conversation evidence, and an applicable rubric. Show the total, eligible, and successfully scored counts for the same period.
A missing transcript or excluded channel belongs in the coverage explanation. It should not disappear behind a “100%” headline.
Ask about the rubric next
Quality needs concrete criteria. A reviewer should be able to identify the behavior being assessed and explain what a pass or fail means.
AI can propose an assessment, but its application of those criteria needs testing. Inspect available evidence, compare reviewer judgments, and sample AI passes as well as failures. Full scoring coverage does not mean every miss was detected.
Keep a human review path
Reviewers need a way to correct the assessment and add context. Reps need a way to question a score. Calibration helps identify unclear criteria or inconsistent judgment before a scorecard becomes a coaching problem of its own.
Use corrections to decide what to revise in the rubric or scoring process. Do not assume that a correction automatically retrains the model.
Use the wider evidence well
Broader scoring can give the team more examples to investigate and trends to test. Each finding still needs a defined period, comparable coverage, and a concrete next step.
| Question | Evidence to look for |
|---|---|
| Which step needs attention? | Criteria results and reviewed examples |
| Is this rep improving? | Comparable coverage and rubric versions over time |
| Did a new macro help? | Relevant conversations before and after the change |
| What needs a cross-team fix? | Recurring cause, owner, and outcome to check |
BearScope’s Quality workspace brings available scored conversations, rubric review, calibration, and coaching together. Broader coverage can reveal useful patterns, but it still depends on connected channels and usable transcripts. Book a demo to inspect coverage and review a score with its available evidence.
See the work in BearScope.
Choose a workflow. We’ll demonstrate the current views, review your sources, and agree what a pilot should measure.
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