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Conversation analytics dashboard metrics: demand, friction, outcome and reliability groups, four marks of a useful metric and vanity metrics.
Insufficient evidence analytics: the cost of forced categorisation, "other" vs "unknown" vs "not analysed", percentages and coverage reports.
Conversation analytics privacy: purpose, minimisation in field design, access roles, retention and deletion of facts, and a jurisdiction check.
Conversation analytics CRM integration: identifier, channel, status and consent; cross-channel merging and the risk of wrong matches.
AI categorization validation: false positives and negatives, a blind sample audit, a calibration cycle and five situations where checking is mandatory.
Conversation analytics taxonomy: one field one question, mutual exclusivity, definitions and boundaries, "other", stable keys and versioning.
Speech transcription accuracy in analytics: which result term, number, negation, language and speaker errors distort, and how to check.
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