| name | tracking-marketing-metrics |
| description | Use when marketing lacks a metrics hierarchy connecting activity to business outcomes, when attribution is last-click or nonexistent, when marketing and sales report different numbers, when dashboards are ignored or full of vanity metrics, or when leading indicators are not tracked. Use when decisions are made on gut feel instead of data. |
| user-invocable | true |
| metadata | {"version":"1.0.0"} |
Marketing Metrics & Attribution
Overview
Measurement is the feedback loop that makes everything else work. This skill builds the metrics hierarchy, hybrid attribution model, dashboard blueprints, leading indicator framework, and review cadences that turn data into decisions.
When to Use
- Marketing reports vanity metrics (traffic, MQLs) while pipeline is unclear
- Attribution is last-click or does not exist
- Marketing and sales track different numbers and argue about lead quality
- No leading indicators are tracked to forecast next quarter
- AI search and dark social create attribution blind spots
- Dashboards exist but nobody checks them or they do not drive decisions
- Preparing to scale past $5M ARR and need measurement infrastructure
Don't use when: You have a functioning three-tier metrics hierarchy, hybrid attribution model, and established review cadences producing weekly decisions.
Quick Reference
| Phase | Duration | Output |
|---|
| Metrics audit and hierarchy design | Day 1-2 | Metrics hierarchy by tier and business outcome |
| Attribution model design | Day 3-4 | Hybrid attribution model specification |
| Pipeline and revenue metrics build | Day 5-6 | Pipeline velocity, conversion, CAC, and NRR metrics |
| Dashboard blueprint | Day 7-8 | Dashboard specs for board, leadership, and ops |
| Leading indicator framework | Day 9-10 | Leading indicators, thresholds, and alert rules |
| Review cadence design | Day 11-12 | Weekly, monthly, and quarterly review templates |
Core Deliverables
- Metrics Hierarchy -- Three-tier structure mapped to seven business outcomes
- Hybrid Attribution Model -- Multi-touch plus self-reported plus AI-enriched layers
- Pipeline and Revenue Metrics -- Velocity score, conversion targets, CAC suite, NRR suite
- Dashboard Blueprint -- Board, leadership, and ops dashboards with shared definitions
- Leading Indicator Framework -- Predictive indicators with early warning thresholds
- Review Cadence Templates -- Weekly, monthly, and quarterly review agendas
Common Mistakes
- Celebrating vanity metrics (traffic growth) while pipeline is flat
- Relying solely on last-click attribution (punishes relationship-building)
- Letting marketing and sales measure different things
- Measuring everything instead of limiting to decision-driving metrics
- Chasing perfect attribution instead of directional accuracy
- Skipping self-reported attribution (misses 30-50% of B2B influence)
- Setting MQL volume targets instead of measuring pipeline
- Reporting without recommendations
Integration
Feeds into: managing-marketing-ops, and loops back to all skills for optimization
Refresh: Metrics hierarchy quarterly. Attribution model audit quarterly. Shared definitions every 6 months. Leading indicator validation quarterly. AI citation tracking monthly. Full measurement audit annually.
See workflow.md for detailed phase-by-phase execution, attribution model specs, pipeline velocity formulas, dashboard diagrams, and review cadence templates.
