Operations

No Support Analytics: Flying Blind on Your Biggest Cost

Most support teams can tell you how many tickets they got and almost nothing about what those tickets were about. That single gap means every investment decision, from headcount to automation, is made on intuition.

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Published September 10, 2026 · Reviewed by the Fidiora team

Short answer

If you cannot say which topics drive your volume and cost, every decision about staffing, automation, and documentation is a guess. The minimum useful reporting set is volume by topic, cost per resolution, reopen rate, and arrival rate against resolution rate.

Key takeaways

Reporting quality depends entirely on tagging discipline.
Four metrics answer most support questions: topic volume, cost per resolution, reopens, and flow.
Automated classification beats manual tagging for consistency.
Without topic data, automation gets pointed at whatever someone remembers.

Signs you have this problem

You can report volume but not topics
Tagging is inconsistent or skipped under pressure
Leadership asks questions the reports cannot answer
Automation is aimed at whatever the loudest person remembers
Nobody knows which topics cost the most

Why it happens

No tag taxonomy, or one nobody maintains
Manual tagging under handle-time pressure
Reports built around activity rather than outcomes
No owner for support reporting
Tools that report messages rather than issues

Without topic-level data you cannot prioritise anything. Content gets written for the wrong subjects, automation targets the wrong workflows, and headcount requests are argued on volume rather than on cost. The team works hard on the wrong things and cannot prove otherwise.

The Fix

How to fix it

Build a small tag taxonomy that maps to decisions

Fifteen to forty tags is plenty. If two tags never lead to different actions, merge them. A taxonomy nobody can hold in their head is the same as no taxonomy.

Automate classification

Agents under time pressure tag inconsistently, which corrupts the data you are trying to build. Automated classification is more consistent even when it is occasionally less nuanced.

Report four things, well

Volume by topic, cost per resolution, reopen rate, and arrival rate against resolution rate. Those four answer most operational questions and each one drives a specific action.

Give reporting an owner

Reports that nobody owns are reports nobody trusts. Name someone responsible for the definitions and for the monthly review.

Get classification as a by-product

Fidiora classifies every conversation consistently as part of handling it, so your reporting data is the same data the system acted on rather than a separate manual step.

How Fidiora Helps

Fidiora produces reliable topic data without asking anyone to tag anything. Because it classifies conversations to route and answer them, the reporting is a by-product of the work rather than an extra task that gets skipped whenever the queue is busy.

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FAQ

Questions

What support metrics actually matter?

Volume by topic, cost per resolution, reopen rate, and arrival rate against resolution rate. Those four cover prioritisation, efficiency, quality, and capacity, which is most of what you need to decide anything.

Should tagging be manual or automatic?

Automatic for the primary category, because consistency matters more than nuance and manual tagging degrades under time pressure. Keep a small manual layer for things only a human would notice.

How many tags should we use?

Enough to distinguish topics that lead to different decisions, usually fifteen to forty. If you cannot say what you would do differently for two tags, they should be one.