Billing and reporting

Analytics and quality

Published October 8, 2026 · Reviewed by the Fidiora team

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In short

Measure Fidiora by genuine resolution, not deflection. Track resolution rate, response time, handoff reasons, and handoff quality, and pair the numbers with a weekly review of a sample of AI-resolved conversations. Questions Fidiora could not answer show you which help docs to write next.

Resolution, not deflection

Fidiora analytics separate deflection from real resolution. A deflected conversation never reached a human, which includes customers who simply gave up. A resolved conversation ended with the customer helped. The two can move in opposite directions, so the number to manage is resolution rate. See deflection vs. resolution and containment rate vs. resolution rate.

The core metrics

Fidiora analytics cover resolution rate, response time, and deflection versus real resolution. The other measures below come from your weekly review and, where you use one, your helpdesk.

  • Resolution rate. The share of conversations Fidiora closes without a human, under the resolution definition. It should climb steadily as your docs improve.
  • Handoff rate and reasons. How often Fidiora hands off, and which trigger fired: request for a human, low confidence, sensitive topic, frustration, VIP rule.
  • Response time. Time to first reply, for AI and for humans after a handoff. See first response time.
  • Handoff quality. How often agents ask customers to repeat information, and time from handoff to first human reply.
  • Customer satisfaction. CSAT on AI-resolved and on handed-off conversations, tracked separately.
  • Reopens. Resolved conversations that came back. A rising reopen rate suggests incomplete answers.

Read handoffs the right way

A high handoff rate is not bad by itself. Handoffs on sensitive or undocumented questions are the system working. Handoffs on questions your docs already cover point to a content or retrieval problem: the article is unclear, split across pages, or uses different words from your customers. Group handoffs by reason each week and you will know exactly where to act.

A weekly quality review

  1. Sample AI-resolved conversations

    Read a sample of conversations Fidiora resolved this week. Check each for a correct, complete answer, the right cited source, and your tone.

  2. Read flagged handoffs

    Read handoffs triggered by frustration or repeated failure. Ask whether the handoff should have happened earlier.

  3. List the content gaps

    Group low-confidence handoffs by topic. The largest groups are the help articles to write next.

  4. Fix and re-sync

    Correct or remove the sources behind any wrong answers, write the missing articles, and re-sync your knowledge sources.

  5. Record what changed

    Note the fixes and watch next week's numbers on those topics. This is how you know the loop is working.

Report to the business

Leadership usually wants three numbers: resolutions this month, cost per resolution, and the effect on the team's queue. Add satisfaction on AI-resolved conversations so the story is about customers helped, not tickets avoided. If you want a template, see support KPI dashboard and how to measure AI support quality.

Questions

What is a good resolution rate?
It depends on how much of your volume is documented, repetitive questions. Focus on the trend: resolution rate should rise as you close content gaps, while answer accuracy stays high.
Is a high handoff rate a problem?
Not on its own. Look at the reasons. Handoffs on sensitive or undocumented topics are correct. Handoffs on documented questions mean the content needs work.
How many conversations should we review each week?
Enough to spot patterns. Read every handoff flagged for frustration plus a regular sample of AI-resolved conversations, and spot-check any topic affected by a recent product or policy change.
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