Treat “score every conversation” as a coverage requirement with a defined denominator, not as a guarantee of accurate judgments. Track what was captured, what was eligible, what was processed, and what received a valid score. Keep human review for disputed, uncertain and consequential evaluations.

Which coverage claims should you investigate?

Level AI advertises automated scoring across calls, chats, emails and bot conversations. CallMiner describes automated interaction scoring in its conversation analytics platform. These statements identify products to investigate; neither establishes that every interaction in your own systems will be available, supported or correctly evaluated.

What does the denominator need to include?

The denominator is the population against which a percentage is calculated. Write it down before accepting a dashboard percentage. A contact can exist in the phone system but never reach the QA pipeline. Another may arrive with audio but no usable transcript. A third may legitimately have no applicable rubric. Those cases should remain visible rather than silently disappearing from the report.

  • Created: all interaction identifiers in the original system for the reporting period.
  • Captured: identifiers received with required recording or text data.
  • Eligible: captured interactions meeting documented channel, language and rubric conditions.
  • Processed: eligible interactions successfully analyzed within the agreed delay.
  • Validly scored: processed interactions with usable criterion results and supporting evidence.

How can a pilot expose missing conversations?

Our recommended reconciliation starts with a daily export of source-system identifiers and timestamps. Match those identifiers against the QA export. Assign a reason to every unmatched record: expected exclusion, delayed ingestion, duplicate, unsupported input or unexplained failure. Test weekends, transfers and unusually long conversations instead of sampling only a quiet weekday.

Calculate both source-to-score coverage and eligible-to-score coverage. Report counts alongside percentages so a change in exclusions cannot masquerade as improvement. Ask the vendor to demonstrate retries and show how late arrivals affect historical reports. Establish whether an interaction that receives only some criterion scores is counted as fully scored.

Why is coverage different from scoring quality?

A pipeline can process every eligible item and still misjudge an important behavior. Review false failures and missed failures on a human-labeled holdout sample. Inspect uncertain language, cross-talk and incomplete transcripts. Separate technical failures from valid not-applicable decisions and from model disagreement. These categories require different owners and different remedies.

Expanding coverage also expands the review queue. Decide which findings need immediate attention and which belong in trend reporting. Use calibration and dispute procedures before using automated scores in consequential personnel decisions. Connect recurring patterns to a manageable coaching workflow.

Limits

The population model and reconciliation steps are editorial recommendations, not a description of a specific vendor export. Product documentation was checked on 19 October 2026. We did not measure either vendor’s actual coverage or accuracy. Contract scope, integrations, retention, channel eligibility and transcription support determine what can be scored in a particular deployment.