{"id":13118,"date":"2026-10-17T14:43:55","date_gmt":"2026-10-17T14:43:55","guid":{"rendered":"https:\/\/botsify.com\/blog\/?p=13118"},"modified":"2026-10-17T14:45:12","modified_gmt":"2026-10-17T14:45:12","slug":"ai-customer-support-metrics-beyond-deflection","status":"publish","type":"post","link":"https:\/\/botsify.com\/blog\/ai-customer-support-metrics-beyond-deflection\/","title":{"rendered":"AI Customer Support Metrics: What to Track Beyond Ticket Deflection"},"content":{"rendered":"

\u201cWe deflected 60% of tickets\u201d is the metric most teams lead with. It’s also the one most likely to hide a problem. Deflection measures volume, not quality. An AI agent can close conversations without solving customer issues, making performance look impressive while customer satisfaction quietly declines.<\/p>\n

That’s why tracking the right AI customer support metrics matters. Beyond ticket deflection, you need to understand whether customers receive accurate answers, how often they contact support again, when conversations require human assistance, and what each successful resolution costs.<\/p>\n

This guide explains which metrics to track, how to measure them, and how to build a reporting process that helps improve customer support rather than simply make automation look successful.<\/p>\n

\"AI<\/figure>\n

<\/h2>\n
\n
\n

Table of Contents<\/p>\nToggle<\/span><\/path><\/svg><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n