Design, implement, and operate a PMM measurement system. Synthesizes Reforge's metric constellation, OKR (Doerr), and the F.A.C.T.S. + MAYO frameworks. Output is a measurement blueprint sized to the team's data maturity.
When to use
Pre-OKR season. After a reorg. When PMM and sales pipeline numbers do not reconcile. When the team has many dashboards and no shared source of truth.
Steps
- Audit current state. Inventory data sources, tracking tools, reporting gaps.
- Define business-aligned goals. Translate company OKRs into measurable PMM goals.
- Select the metric constellation (Balfour/Reforge). Choose output metrics across retention, engagement, monetization. Decompose each into input metrics.
- Map metrics to PMM workstreams. Messaging, launches, enablement, CI, campaigns. Assign KPIs.
- Choose attribution model. Blend MMM (strategic), MTA (tactical), incrementality (confidence). Match to sales-cycle length and data maturity.
- Design the KPI dashboard. Stakeholder-specific views: exec, PMM team, cross-functional.
- Set reporting cadence. Weekly / monthly / quarterly tied to actual decision forums. Reports arrive BEFORE the meetings where decisions get made.
- Integrate data sources. CRM + analytics + ad platforms + PMM tools into unified reporting.
- Establish baselines and targets. Use historical data. No aspirational guesses.
- Build feedback loops. Review, refine, retire metrics as priorities shift.
Frameworks
- Metric constellation: Output metrics across retention/engagement/monetization, with input metrics decomposed under each, and tradeoff metrics monitored opposite each.
- OKR: Objectives + 2–5 Key Results.
- F.A.C.T.S. (PMA): Focus, Alignment, Commitment, Tracking, Stretching.
- MAYO (Dock): Motions, Actions, Yield, Outcomes.
- Three-workstream PMM model: Value-Based Messaging / Product GTM / Revenue Enablement.
- Launch KPI hierarchy: Awareness → Engagement → Adoption → Revenue, tiered T0–T3.
Quality gates
- Every KPI traces to revenue, pipeline, or customer value. No orphan vanity metrics.
- Output metrics cover all three dimensions (retention, engagement, monetization).
- Input metrics are actionable, the team can directly influence them.
- Tradeoff metrics monitored alongside primary metrics.
- Attribution model matches actual sales-cycle length.
- Cadence matches decision rhythm.
- Baselines from historical data, not guesses.
- Sales/product/finance agree on shared definitions.
- Quarterly review and retire/replace cycle defined.
Common failure modes
- Single north-star fixation. Hides problems in the other dimensions.
- Output metrics without input metrics. You detect problems too late.
- Vanity metrics masquerading as KPIs.
- Composite metrics that merge dissimilar actions and hide tradeoffs.
- No attribution plan before launch. Tracking added post-go-live cannot prove impact.
- 50+ KPIs creating paralysis. Focus on 3–7 per workstream.
- Misaligned MQL definitions across marketing/sales.
- Short-termism, measuring performance only, ignoring brand and long-term pipeline.
- Static framework that never gets revisited.
- Siloed reporting tools.
- Optimizing conversion rates while absolute counts shrink (Optimise for absolute count of users reaching each stage, not stage conversion rates).
- Calling experiment wins before long-term holdouts evaporate (30–40% of growth experiments with short-term lift show no incremental value at one year).
- Running tests that won't reach significance in a month (Don't test what won't reach sample size in a month, pre/post is fine).
Outputs
- North-star metric constellation.
- OKR structure.
- KPI dashboard spec with stakeholder views.
- Reporting cadence + review forums.
- Attribution model selection with rationale.
- PMM metrics by deliverable type.
- Baselines + targets.
- Data integration requirements.