Customer support analytics that drafts the fix

What it prevents is measuring the wrong thing. Volume and speed are easy to count and nearly useless on their own — they tell you the queue moved, not what the queue was about. A fast team answering the same avoidable question two hundred times looks excellent on a response-time chart.

Numbers that don’t flatter

Each conversation carries exactly one topic. That sounds like a limitation and is actually the thing that keeps every figure on the page true — a thread counted under two subjects would inflate both volumes and let one customer’s rating weigh twice.

The CSAT column is deliberately withheld until a topic has at least three responses, for everyone including admins. The average of a single response is that customer’s private rating wearing a disguise, and two is barely better. Below the floor the column shows a dash and tells you which reason applies — nobody has rated this yet, or the number is being held back to protect an individual.

Coverage is measured rather than assumed, too: an article has to genuinely be about a topic to count as covering it, not merely mention it in passing. And when the check itself fails, the topic keeps its last known coverage instead of dropping to “gap” and sending you off to rewrite something that already exists.