Data

Metrics Definition Studio

Create standardised metric definitions with clear calculations, units, and data sources. Generate documentation for your analytics team.

Estimated time: 3-8 min
Difficulty level: Intermediate
Privacy: Runs locally
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5000ms CPU256MB RAM64KB in · 256KB outEducational, no sensitive data
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Metric Definition Best Practices

Why Define Metrics?

Standardised metric definitions ensure everyone in your organisation understands exactly what a metric measures, how it's calculated, and where the data comes from. This prevents misinterpretation and enables consistent decision-making.

Elements of a Good Definition

  • Clear name that is unambiguous and includes the acronym if it is common
  • Business definition that explains what it measures in plain language
  • Technical calculation that gives an exact formula or SQL
  • Units such as count, percentage, currency
  • Data source that says where the underlying data lives

Common Metric Types

  • Counts such as DAU, MAU, transactions
  • Rates such as conversion rate, error rate, churn
  • Ratios such as LTV to CAC, revenue per user
  • Percentiles such as P95 latency, median response time
  • Aggregates such as total revenue, average order value

Governance Tips

Maintain a central metrics catalog. Assign metric owners responsible for accuracy. Version your definitions and track changes over time. Review metrics quarterly to ensure they remain relevant.