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Honest SLA reporting fixes the ‘watermelon’ problem by measuring real customer outcomes, not vanity metrics.

Standardize SLA, TTR and FCR definitions to stop metric disputes, improve reporting accuracy, and focus teams on real customer outcomes.

A trusted support analytics dashboard focuses on 5-8 clear KPIs, visible trust indicators, and actionable views that drive decisions.

Run a monthly ticket-data review to spot recurring issues, find root causes, prioritize fixes, and automate insights with AI.

Use ticket tags and AI to find KB gaps: set a two-tier taxonomy, auto-tag tickets, generate article drafts, and measure deflection.

Focus on time-to-resolution, not just deflection: track link rates, search success, helpfulness, and use AI to speed ticket resolution.

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