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Data

Analytics Use Cases

Use analytics to understand verification volume, pass rates, evidence-source mix, build friction, and staff priorities.

Who uses it

Guild owners, managers, analysts

Where it lives

Dashboard > Analytics

Goal

Staff can turn verification history into decisions about builds, onboarding, and roster readiness.

Before You Start

  • Analytics view permission.
  • Enough completed checks to make trends meaningful.
  • A question you want the data to answer.

Steps

1

Pick the decision first

Analytics is most useful when you start with a decision: which build is failing often, which activity needs help, which evidence source causes the most review work, or whether a guild is improving over time.

2

Read pass rate with context

A low pass rate can mean members are underprepared, the build spec is too strict, the evidence instructions are unclear, or parsing needs tuning. Pair pass rate with review queue, OCR Insights, and support ticket trends.

3

Compare evidence sources

Mixed-evidence guilds should watch whether OCR, Markdown, TONL, or other supported evidence sources create different failure patterns. This helps decide whether to change default evidence guidance.

4

Use drill-downs to act

When a metric looks off, jump to the related build, verification list, data inventory family, or OCR Insights page. Analytics should produce an action, not just a number.

Launch Checklist

  • The date range matches the period you care about.
  • The pack/activity/build filters match the guild workflow.
  • Evidence source mix is checked before blaming a build.
  • Follow-up action is recorded or assigned.

Common Pitfalls

  • Treating a small launch sample as a stable trend.
  • Comparing OCR and export-based checks without accounting for evidence quality.
  • Ignoring small sample sizes.

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