Catalog
concept#Analytics#Product#Data

Business Metric

A quantifiable measure used to track business performance and to inform operational and strategic decisions.

A business metric is a quantifiable measure used to assess the performance or health of business processes and outcomes.
Established
Medium

Classification

  • Medium
  • Business
  • Organizational
  • Intermediate

Technical context

Analytics platforms (e.g., Google Analytics)Data warehouse / lakeReporting and BI tools

Principles & goals

Metrics must be clearly defined and documented.Metrics should be directly linked to strategic objectives.Reliable data sources and repeatable calculations are required.
Discovery
Enterprise, Domain, Team

Use cases & scenarios

Compromises

  • Gaming metrics instead of focusing on real value.
  • Short-term optimization of KPIs at the expense of long-term goals.
  • Loss of trust due to inconsistent measurement methods.
  • Prioritize a few well-defined core metrics.
  • Version and document metric definitions.
  • Conduct regular reviews to validate and adjust.

I/O & resources

  • Raw transaction and event data
  • Goal definitions and business rules
  • Reference and master data
  • KPI dashboards and reports
  • Alerts and escalation rules
  • Actionable recommendations and priorities

Description

A business metric is a quantifiable measure used to assess the performance or health of business processes and outcomes. It links strategic objectives to operational data, enabling monitoring and informed decisions. Clear definitions, reliable measurement methods and regular review are essential to ensure validity and actionability.

✔

  • Enable objective assessment of actions and progress.
  • Support data-driven decisions and prioritization.
  • Provide transparency to stakeholders and promote accountability.

✖

  • Over-specific metrics can neglect context.
  • Faulty data sources lead to incorrect conclusions.
  • Too many measures cause analysis paralysis.

  • Conversion rate

    Ratio of visitors to completed goals (e.g., purchases).

  • Customer Lifetime Value (CLV)

    Expected contribution of a customer over the entire relationship.

  • Churn rate

    Share of customers leaving within a period.

E‑commerce conversion rate

Measuring visitor-to-buyer share per campaign to optimize checkout processes.

Customer Lifetime Value (CLV)

Forecast of a customer's total contribution margin over the relationship to guide investments.

Net Promoter Score (NPS)

Customer satisfaction metric used to derive product and service improvements.

1

Define objectives and decision questions

2

Select and define relevant metrics

3

Connect data sources and implement calculations

4

Introduce dashboards, SLAs and review processes

⚠️ Technical debt & bottlenecks

  • Outdated ETL pipelines with inconsistent transformations.
  • Missing metadata and metric glossary.
  • Monolithic reporting architecture without scalable data layers.
Inaccurate data sourcesInconsistent definitionsLack of analytics capacity
  • Increasing click-through rate via misleading UI elements instead of real value.
  • Rewarding employees solely on short-term metrics.
  • Ignoring sampling errors in A/B tests.
  • Loss of context when aggregating across heterogeneous groups.
  • Unaccounted lag effects between action and outcome.
  • Premature causal assumptions from correlations.
Data analysis and statisticsDomain knowledge of the business areaData engineering and ETL skills
Data quality and availabilityReal-time vs. batch requirementsScalability of measurement and reporting processes
  • • Legal data privacy constraints
  • • Technical limitations of data collection
  • • Organizational silos and responsibility issues