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.