GTM Metrics Framework
The numbers that tell you the truth about the system.
Workflow
Step 1Metric Definition
ObjectiveDefine which metrics matter for GTM success
InputOKRs, strategy, business goals, customer needs
OutputComprehensive metric definition
Key activities
Identify leading and lagging indicators, define metric names/descriptions, identify owners
Decision points
Which metrics truly matter? Leading vs. lagging? Actionable?
Tools: Metric framework templatesRoles: Analytics (definition), GTM leadership (strategy input), Finance (business input)
Success: 15-20 key metrics defined with descriptions
Quality gate: Metrics defined and agreed as key indicators
Why it matters
- Teams optimize what's measured. A bad metric set drives the wrong behavior; the right one turns the operating model into a steering wheel.
Best practices
- Measure leading AND lagging indicators — pipeline health AND revenue.
- Define every calculation exactly; two teams computing the "same" number differently is a data governance failure.
- Set baselines first, then targets.
- Review the metric set quarterly — kill vanity metrics.
Common mistakes
- Dashboard of 40 metrics, none owned.
- Vanity metrics that feel good and mean nothing.
- No single source of truth for definitions.
Key questions
- Which 10 numbers, if they moved, would tell us the system is working?
- Who owns each one?
Agents that drive this
Pipeline AuditorAttribution
Tools we use · alternates in [ ]
Metabase[ Looker Studio, Power BI, Grafana ]Supabase[ Postgres, Firebase ]Google Analytics[ Plausible, Mixpanel ]