--- name: pmm-metrics version: 1.0.0 description: > Defines a North Star Metric and 3-5 Input Metrics, then builds a capped 8-16 metric scorecard across Financial, Customer, Product & GTM, and Process & Growth, flagging vanity and unowned metrics. Trigger on: "what should we measure", "North Star metric", "build a PMM scorecard", "what metrics should I track", "define our key metrics", "set up a metrics framework". metadata: author: Stefanos Karakasis context: brain-dependent quality_gate: true last_updated: 2026-09-14 --- # PMM Metrics ## How This Works Picks one North Star Metric that predicts customer value and revenue, names the 3-5 Input Metrics that move it, then rounds out a scorecard across four categories (Financial, Customer, Product & GTM, Process & Growth), capped at 2-4 metrics per category — 8-16 total, small enough that a team actually updates it every 1-2 weeks instead of abandoning it by Q2. Every target and current value comes from the user — this skill doesn't invent numbers. If brain Section 2 (ICP/Beachhead) is loaded, it uses that to check whether a metric is a real leading indicator for the confirmed segment or just generic. Output is chat-only, disposable — the brain has no Metrics section to write to (all 6 existing sections are claimed), same treatment `experiment-ideas` (pmm-growth) gives its output. **Step 0** — Load brain Sections 1 (Product), 2 (ICP/Beachhead) if present, and guardrails from `/context/meta-patterns.md`. **Step 1** — Classify the business game: Attention, Transaction, or Productivity. **Step 2** — Define the North Star Metric and validate it against 7 criteria. **Step 3** — Define 3-5 Input Metrics that most directly move the North Star. **Step 4** — Build the supporting scorecard: 2-4 metrics per category across Financial, Customer, Product & GTM, and Process & Growth, each with a target, weight, and cadence. **Step 5** — Self-check the full set against sprawl and vanity-metric traps. **Step 6** — Deliver the scorecard as a markdown table the user saves themselves — this skill has no durable output file of its own. **Step 7** — Learning Close: log the session to `/context/skill-sessions.md`. --- ## Trigger - **When:** Choosing a North Star Metric, building a measurement framework from scratch, auditing an existing metrics list that's sprawled past what anyone tracks, or preparing a scorecard for leadership/exec reporting. - **Not for:** Quarterly OKRs once metrics exist → `pmm-okrs` (pmm-execution) expresses target *change* in metrics this skill defines; run this skill first if no North Star exists yet. Launch tier assignment → `go-to-market-strategy`. Pressure-testing one experiment's hypothesis → `experiment-doc` (pmm-execution) — feed it this skill's metric as the guardrail, don't invent a new one. Post-launch metrics review → `retro` (pmm-execution) looks backward at what this skill's scorecard already tracks. - **Example prompts:** - "What should we be measuring?" - "Help me define our North Star metric" - "Build a PMM scorecard for leadership" - "What metrics should Product Marketing track?" - "Our metrics list has 25 things on it and nobody updates it" - "Set up a measurement framework for Q1" --- ## Inputs - **Args:** Business model description (how revenue is made, what customers do in-product), current metrics being tracked (if any), reporting cadence and audience (team-level vs. exec-level). - **Defaults:** No brain and no business context given → ask directly (Step 1). Brain exists → load Section 1/2 silently, ask only for what isn't already on file. - **Context keys:** - `/foundation/brain.md` — optional. Section 1 (Product) informs business-game classification; Section 2 (ICP/Beachhead) informs which Customer and Product & GTM metrics are actual leading indicators for the confirmed segment vs. generic. - `/context/meta-patterns.md` — optional; guardrails from prior metrics sessions. - **Brain contract:** Reads Sections 1, 2. Writes nothing — the brain's sections are all claimed; adding a Metrics section is a `product-marketing-context` schema change, out of scope here. Scorecard is chat-only output, same as `experiment-ideas`. --- ## Connectors (Optional) | Connector | What it adds | |---|---| | `~~product analytics` | Activation and adoption metrics | | `~~CRM` | Funnel conversion data | | `~~marketing analytics` | Cross-channel performance | | `~~email marketing` | Lifecycle email metrics | | `~~cloud storage` | Metric sheets and past reports | > **No connectors?** Paste the material and I'll work from that. The output has the same shape. > Pulled facts are drafts: each is tagged with category, tool and date, and nothing is written until you confirm. --- ## Pre-flight - Load `/foundation/brain.md` Sections 1, 2 if it exists — silently. - Load `/context/meta-patterns.md` if it exists, and surface any guardrail that has fired 2+ times in prior metrics sessions. - If no brain found: surface once, non-blocking — "No brain found. I'll ask directly about your business model and customer segment instead. Metrics will be less sharply targeted without ICP/beachhead context — run `product-marketing-context` first for a tighter fit, or continue now." - **No hard block.** This skill runs entirely from user-stated business context; brain absence degrades precision, not capability. --- ## Steps ### Step 1 — Classify the Business Game Ask, or infer from brain Section 1 if loaded: > "How do customers primarily get value from your product — by spending > time in it, by transacting through it, or by getting something done > more efficiently with it?" Classify into exactly one: | Game | Core question | Examples | |---|---|---| | **Attention** | How much time do customers spend using the product? | Content platforms, social tools, media | | **Transaction** | How many transactions occur between customers and the platform? | Marketplaces, payment platforms, e-commerce infra | | **Productivity** | How efficiently can someone complete their work or achieve their goal? | Most B2B SaaS — collaboration, workflow, ops tools | State the classification with one sentence of rationale — never assume silently. Most B2B SaaS lands in Productivity; treat that as a hypothesis to confirm, not a default to skip past. --- ### Step 2 — Define the North Star Metric A North Star Metric (NSM) is **not** multiple metrics, a revenue/LTV number, an OKR, or a strategy. It **is** a single, customer-centric KPI reflecting the value customers get from the product — a leading indicator of long-term business success. Propose one candidate matched to Step 1's business game, then validate it against all seven criteria before confirming: 1. **Easy to Understand** — clear enough that everyone in the org comprehends it without a footnote. 2. **Customer-Centric** — reflects value delivered to customers, not just revenue or internal activity. 3. **Sustainable Value** — indicates habits and long-term engagement, not a one-time spike. 4. **Vision Alignment** — represents meaningful progress toward the company's stated vision or mission. 5. **Quantitative** — measurable with clear, numeric tracking. 6. **Actionable** — teams can directly influence it through product, marketing, and operational changes. 7. **Leading Indicator** — predicts future business success and revenue growth, rather than lagging behind it. **Score each criterion Pass/Fail with one line of evidence.** 2+ fails → reject and propose an alternative, never deliver a failing NSM with caveats. Revenue and ARR usually fail #2 (Customer-Centric); NPS often fails #7 (Leading Indicator) without a longitudinal retention/expansion link. Name the specific failure — not a generic "that's not customer-centric." --- ### Step 3 — Define Input Metrics Define 3-5 Input Metrics — leading indicators that most directly move the North Star. Each must: - Move more easily, short-term, than the NSM itself - Have a stated causal link to the NSM, not just topical proximity - Point to where optimization effort should concentrate For each: **Metric**, **Why it drives the NSM** (causal, one sentence), **Who owns moving it** (PMM, Product, Sales, CS). If brain Section 2 (ICP/Beachhead) is loaded, check each against the confirmed segment — generic enough to apply to any customer? Flag it `[GENERIC — not segment-specific]` rather than including it silently. --- ### Step 4 — Build the Supporting Scorecard Select **2-4 metrics per category, 8-16 total** — past that, the scorecard stops getting updated by Q2. Reference list below, not a requirement to use all of it: **Financial** ARR/Revenue/Bookings · Qualified pipeline ($ and count, by stage) · Pipeline sourced from PMM-influenced campaigns · Win rate · Average deal size · Time to close · Expansion revenue (upsell/cross-sell share) · Product-level revenue · Market penetration in target segment **Customer** NPS / CSAT · New customer reviews (count + score, e.g. G2/Capterra) · Customer advocacy (case studies, reference customers) · Engagement in sales/customer calls · DAU/MAU (post-launch or feature-specific) **Product & GTM** Messaging & positioning effectiveness (win/loss feedback, message testing) · Sales enablement efficacy (% of calls using PMM content) · Content & thought leadership engagement · Competitive edge (battlecard usage, win rate vs. named competitor) · Market leadership (analyst recognition) · Feature/product adoption rate · New use case discovery **Process & Growth** GTM planning and MRD/PRD creation velocity · Feedback loop efficiency with GTM team · Asset utilization (content actually used vs. produced) · Funnel conversion rate at each stage (MQL→SQL, SQL→Opp, Opp→Closed) · Pricing & packaging effectiveness For each metric: **Name**, plain-language **Definition**, **Target**, **Weight** (sums to 100% across the full scorecard, not per category), **Cadence** (default biweekly). Present as a table, grouped by category, with a subtotal weight shown per category. --- ### Step 5 — Self-Check Against Sprawl and Vanity Metrics Before delivering, check the full set: - **≤16 total metrics.** Over that, cut — ask which 2 matter least, don't just append. - **Every metric has a named owner.** No owner, no metric. - **No duplicate metrics worded differently** (e.g. "content engagement" vs. "thought leadership engagement") — merge or cut. - **Every category has ≥1 metric** — zero means Step 4 was skipped for it; flag and revisit. - **Weights sum to exactly 100%.** - Flag anything trackable but not actionable by a named function — `[VANITY — no owner can move this]`. --- ### Step 6 — Deliver the Scorecard Present the finished set — NSM, Input Metrics, and categorized scorecard table — as the session's final chat output. State plainly that this is disposable: "Copy this into your tracker of choice (the [Product Marketing Scorecard template](https://deep-visage-02d.notion.site/Product-Marketing-Scorecard-26df5957c92880f6b1d8c7b15d1e8c6f) works well for ongoing tracking) — this skill doesn't save it for you." --- ### Step 7 — Learning Close End every completed session by appending one entry to `/context/skill-sessions.md`, in the format defined in `product-marketing-context/.claude-plugin/skill-sessions-format.md` (Type A — execution session): ```yaml type: execution skill: pmm-metrics session_date: [YYYY-MM-DD] pattern: [one falsifiable statement about what happened this session, or "none"] source: [surprised / wrong / missing / N/A] ``` Write this row directly — do not ask the user for permission. This is the only durable write this skill makes — see Step 6: the scorecard itself is chat-only, disposable output. If nothing notable happened this session, still write the row with `pattern: none`. --- ## Outputs - **Files written:** `/context/skill-sessions.md` — one row per session (Step 7). Nothing else — see Step 6. - **Chat output format:** Business game → NSM with 7-criteria scoring → Input Metrics with causal rationale and owners → categorized scorecard table → self-check results. - **External side effects:** N/A - **Next skill:** After delivery, check `product-marketing-context/.claude-plugin/next-skill-map.md` for "After pmm-metrics" and surface it as a question — never auto-run. --- ## Verification - Business game classified with rationale, not assumed. - NSM scored against all 7 criteria individually, not aggregated. - 3-5 Input Metrics, each with causal link and named owner. - Scorecard: 8-16 metrics across all 4 categories, each with target, weight, cadence. - Weights sum to exactly 100%. - Sprawl/vanity self-check run and shown. - Scorecard delivered with the explicit "not saved for you" note (Step 6). - Session logged (Step 7). --- ## Commands ### /classify Run Step 1 only — classify the business game and stop. Useful when the user wants the framework concept without building a full scorecard yet. ``` /classify ``` ### /north-star Run Steps 1-3 only — business game, NSM, and Input Metrics. Skips the broader scorecard. ``` /north-star ``` ### /scorecard Run Step 4 only, assuming NSM and Input Metrics are already defined (stated inline in this session). Builds the supporting scorecard directly. ``` /scorecard ``` ### /audit Pressure-test an existing metrics list the user provides — apply Step 5 sprawl/vanity self-check against it directly, without redefining the NSM. ``` /audit ``` --- ## Operating Rules - **NSM is singular.** Never present more than one as interchangeable options — pick one, name why the runner-up lost. - **Revenue-shaped metrics fail customer-centric by default.** Challenge any NSM that's really a revenue or company-health metric in disguise. - **Every metric needs a named owner.** Unowned is a chart, not a management tool. - **Cap the scorecard at 16.** Cut before adding. - **Weights sum to 100%, shown explicitly.** Never leave weighting as an exercise for the user. - **State output is disposable.** No brain section to write to — never imply otherwise. - **Business game is stated, never assumed** — even the obvious cases. - **Flag generic and vanity metrics visibly** — never quietly drop or quietly include them. --- ## Quality Gate | Check | Standard | Pass = | |---|---|---| | Business game classified | Explicit classification + rationale stated | Yes | | NSM scored on all 7 criteria | Each criterion Pass/Fail with evidence, not aggregate | Yes | | NSM is singular and customer-centric | One metric, not revenue-shaped | Yes | | Input Metrics count | 3-5, each with causal rationale and owner | Yes | | Scorecard size | 8-16 total metrics across 4 categories | Yes | | Every category populated | ≥1 metric per category or explicit flag if skipped | Yes | | Weights sum to 100% | Shown explicitly in output | Yes | | Sprawl/vanity self-check ran | Results shown, not silently passed | Yes | | Disposable-output note shown | User told explicitly this isn't saved for them | Yes | | Learning Close ran | `/context/skill-sessions.md` has a new row for this session | Yes | --- ## Do Not Use For - **pmm-okrs** (pmm-execution) — quarterly OKRs once metrics exist; this skill defines *what* to measure, not the quarter's target change. - **go-to-market-strategy** — launch tier and channel strategy; feed it this skill's metrics as success-metric inputs, don't substitute. - **experiment-doc** (pmm-execution) — pressure-testing one hypothesis; its guardrail metric should come from this skill's scorecard. - **retro** (pmm-execution) — reviewing how metrics performed after a launch; this skill defines the framework, retro looks backward at it.