Corey Haines
27f06a2b7b
Three new substantive frameworks integrated from Founding Marketing (Corey Haines book) into the marketing-plan skill. Bumps marketing-plan from 1.0.0 to 1.1.0. New reference files: - references/budget-planning.md (168 lines) — two scientific methods for setting the marketing budget: Method 1 Revenue-Based (5-40% of ARR with conservative/standard/aggressive postures) and Method 2 Goal-Based (formula: [(New ARR / (ARPC * 12)) * CAC] / annual retention rate). Includes the 3-3-2-2-2 VC growth path (3x in years 1-2, 2x in years 3-7 from $1M ARR), the 10-20% experimental buffer rule, blended CAC calculation (must include salaries, content, tools, retainers - not just paid spend), and the forecasting reality check (no startup under $100M ARR reliably hits monthly forecasts). - references/growth-patterns.md (148 lines) — the real shape of SaaS growth. Phase identification ($0-10K, $10K-100K, $100K-1M, $1M+) with binding constraints per phase. Linear vs step-function vs layered S-curve growth patterns. Channel x Product x Market S-curve layering principle (start the next curve before the current one plateaus). Includes the "long slow SaaS ramp of death" framing and the case against the exponential-growth myth. - references/team-and-agency-model.md (278 lines) — strategy in-house, execution outsourced principle. Three core marketing functions (Growth = demand engine, Product = story engine, Content = trust engine). pi-shaped marketer framework (vs T-shaped) with high-leverage skill-set combinations. Title progression (Manager -> Lead -> Director -> VP -> Chief) — don't inflate the first hire. Agency selection framework (Individual contractors / Small niche / Small generalist). Three-stage scaling model (Early / Growth / Scale) with internal-vs-external ratio guidance. Enhanced existing files to wire in the new frameworks: - SKILL.md (244 -> 270 lines) — new sections "Setting the budget scientifically," "Growth patterns," "Team and agency model" with pointers to the new reference docs. Expanded "What every plan must customize" from 7 items to 9 (added unit economics + phase of growth). Description still 949 chars (under 1024). - references/funding-stage-unlocks.md — Related docs pointer block. - references/measurement-framework.md — Related docs pointer block, new "Anchoring against the VC growth path" section, new "Forecasting reality check" section. - references/methodology.md — Intake 5 (Team) now probes for pi-shaped vs T-shaped vs tactical-only marketing owner. Intake 6 (Budget) now probes for blended CAC, ARPC, retention rate. - references/plan-template.md — Section 3 adds Phase of SaaS Growth. Section 8 adds required unit economics table. Section 10 adds budget-method framing block at top + per-quarter S-curve position field. Section 11 adds RACI table mapping the three core functions to internal-owner and external-executor. Total new content: ~600 lines across three new reference docs plus ~120 lines of integration edits. SKILL.md remains well under the 500-line convention (270). Validates: 43/43 skills pass validate-skills.sh. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
214 lines
11 KiB
Markdown
214 lines
11 KiB
Markdown
# Measurement Framework — KPIs, North Stars, Cadence
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Every plan needs a measurement section that tells the team how to know if the plan is working. This doc is the source for Section 13's measurement subsection.
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**Related docs:**
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- `growth-patterns.md` — the 3-3-2-2-2 VC growth path (3× in years 1–2, 2× in years 3–7 from $1M ARR) and which phase of SaaS growth the company is in ($0–10K / $10K–100K / $100K–1M+)
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- `budget-planning.md` — CAC calculation (blended, not paid-only) and the forecasting reality check (forecasts under $100M ARR are educated guesses, not precise predictions)
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## The north-star principle
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A north star is one metric that captures the business-model thesis at the highest level. It should:
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- Be derivable from the funnel + revenue model
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- Move slowly enough to be a strategic compass (not whipsawed by weekly noise)
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- Trade off correctly against other metrics — improving the north star should generally improve the business
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Don't default to "ARR" or "MRR" alone. Those are outcomes, not norths. Pick something that captures the business model.
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## North-star patterns by business model
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### B2B SaaS (subscription)
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- **Net Revenue Retention (NRR)** — keeps existing customers + expansion in focus
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- Alternative: "Logo retention × expansion ARR"
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- Why: ARR alone hides churn / lets gross-add growth mask product fit problems
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### D2C consumer app (subscription)
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- **Blended LTV / blended CAC** — keeps unit economics honest as paid layer scales
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- Alternative: "Day-35 paid users from cohort × LTV"
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- Why: monthly subscription metrics are volatile; cohort × LTV smooths it
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### Hybrid hardware + software (e.g., Quietude)
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- **Blended LTV / blended CAC across hardware + software** — captures the wedge thesis
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- Alternative: "Hardware-buyers-to-subscriber conversion × blended margin"
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- Why: hardware revenue isn't free (cost to make); subscription revenue isn't expensive to acquire if hardware funds it
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### Marketplace (two-sided)
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- **Liquidity ratio × take-rate** — captures both sides + monetization
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- Alternative: "Monthly transacting users × take-rate × repeat frequency"
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- Why: GMV alone doesn't capture whether the marketplace is becoming a habit
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### Developer tool / open source
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- **Weekly active developers × paid-conversion** — captures both adoption and monetization
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- Alternative: "Weekly active orgs × seats per org × ARPU"
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### Content / media business
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- **Daily active readers / listeners × ad revenue per session** — captures both reach and monetization
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- Alternative: "Subscriber count × retention × ARPU"
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### Commerce (DTC, non-subscription)
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- **Repeat purchase rate × AOV × frequency** — captures monetization layered on quality of customer
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- Alternative: "Customer LTV / CAC × payback period"
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## Leading indicators by AARRR stage
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After the north star, every plan needs leading indicators per AARRR stage. These move faster than the north star and trigger investigations.
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### Acquisition leading indicators
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- Organic visits/month, total + per pillar (SEO health)
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- App Store / Play Store visit-to-install rate (ASO health)
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- Founder-led social channel growth → email subscriber conversion (LinkedIn / X / Substack funnels)
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- Event-to-app conversion rate (event ROI)
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- Ambassador-attributed visits (referral funnel)
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- Paid CAC by channel (when paid is firing)
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### Activation leading indicators
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- Day 1 / Day 7 / Day 35 → paid conversion rate
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- Onboarding session-completion rate
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- First key-action completion (post-signup activation event)
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- App Store conversion rate (install → trial → paid)
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- Trial → paid conversion rate
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### Retention leading indicators
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- Day 30 / Day 60 / Day 90 retention
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- Monthly churn rate (gross + net)
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- Lifecycle email engagement (open / click / unsubscribe by flow)
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- Hardware → app activation rate (for hybrid businesses)
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- Win-back / reactivation rate
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### Referral leading indicators
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- Ambassador-attributed new subs (via Dub or similar)
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- Share-after-value moment rate (% of users sharing)
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- Two-sided referral completion rate
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- Guides program referrals (when live)
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- NPS score (if surveyed)
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### Revenue leading indicators
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- ARPU by cohort
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- Annual plan adoption %
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- Cohort LTV by source
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- Plan mix shifts
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- Eye-mask / hardware attach rate (for hybrid)
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- Expansion revenue (B2B)
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## Review cadence
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The plan should specify three rhythms:
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### Weekly (operational sync)
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- **Who:** fCMO ↔ founder (CEO usually)
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- **Duration:** 30 min
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- **Format:** AARRR scoreboard (current vs. last week numbers across the leading indicators) + this week's ships + blockers
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- **Output:** Action items, decisions made
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### Monthly (metrics review)
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- **Who:** fCMO + founder + extended team (CXO, product lead, designer if applicable)
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- **Duration:** 60–90 min
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- **Format:** Full metrics review + comparison against quarterly KPI targets + qualitative learnings + idea bank reprioritization
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- **Output:** Possible plan adjustments, hire decisions
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### Quarterly (plan recalibration)
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- **Who:** fCMO + founders + key advisors
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- **Duration:** 2–3 hours
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- **Format:** Full plan review against 90-day and 12-month outcomes, channel-level analysis, funding-stage transition check, recalibration of next 90 days
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- **Output:** Updated plan (could be v2 / v3 document iteration)
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## KPI target setting
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For each quarter in Section 10, the plan must include 3–5 specific KPI targets. These should be:
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- **Specific** — not "improve retention," but "Day 30 retention from 22% → 30%"
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- **Measurable** — pull from a wired data source
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- **Stretch but plausible** — based on funnel state + historical patterns
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- **Decision-triggering** — if missed, what does that mean? (Adjust strategy, kill a channel, etc.)
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### KPI target patterns by quarter
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**Q1 (foundation quarter):**
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- Mostly *bedrock* metrics — fixing leaks. "Headphones-gate conversion drop reverses." "Day 1 → paid +25–50%."
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- Some *foundation* metrics — laying tracks. "4 SEO pillars staked." "App Store rewrite shipped."
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- Avoid bold growth targets — the foundations aren't in yet
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**Q2 (validation quarter):**
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- Mostly *validation* metrics — does what we built work? "Paid CAC < $X blended." "Organic traffic 1,500–3,500/mo."
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- Some *cohort* metrics — do new cohorts behave better? "Day 7 retention for Q2 cohort vs. Q1."
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**Q3 (scaling quarter):**
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- Mostly *scaling* metrics — how far does it go? "Paid scaling to $20–30K/mo with CAC steady." "First B2B install reference case live."
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- Some *capability* metrics — what new things are live? "First Guides pilot launched."
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**Q4 (compound quarter):**
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- Mostly *compound* metrics — is the flywheel turning? "50%+ of new subs from non-paid channels." "Ambassador-driven 15–25% of new subs."
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- Some *narrative* metrics — does the Series A story write itself? "Blended LTV/CAC > 3."
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## Anchoring against the VC growth path
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For VC-backed clients past $1M ARR, anchor 12-month and multi-year targets against the **3-3-2-2-2 rule** (3× in years 1 and 2, then 2× in years 3 through 7). Hitting it is rare; most companies don't. Anchoring against it forces the plan to either match it and show how, or explicitly defend choosing a slower trajectory. Full table and context in `growth-patterns.md`.
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For non-VC-backed companies (bootstrapped, founder-funded, profit-focused), the 3-3-2-2-2 doesn't apply. Use linear-pattern targets ("$X MRR added per month") or step-function targets ("$Y revenue jump after the enterprise tier launches") instead.
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## Forecasting reality check
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A plan derives a budget and an annual goal. It does not produce a 12-month month-by-month forecast that's reliably accurate to the dollar.
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**Unless the company is publicly traded, all forecasts are educated guesses.** No startup under $100M ARR consistently hits month-by-month forecasts. Quarterly review is when the plan adjusts — not when variance is treated as failure.
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What the plan commits to honestly:
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- The annual goal is a defensible direction-of-travel
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- The budget is the resource commitment that makes the goal plausible
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- The 90-day roadmap (Section 9) is what's actionable now
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- Month-to-month projection is illustrative, not promised
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Founders who over-engineer the forecast end up explaining variance every month instead of executing. The plan should resist this — name the annual target, the quarterly KPIs, and the kill criteria. Don't promise the month.
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Full context in `budget-planning.md`.
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## Kill criteria
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For every channel or initiative, the plan should specify when to stop. Often missing from plans, kill criteria force discipline.
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Examples:
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- "If a paid channel has CAC > 2× target after 30 days at meaningful spend, pause."
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- "If onboarding Variant 3 doesn't show statistically meaningful lift (or directional lift + congruent qualitative signal) after 4 weeks, move to Variant 1."
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- "If lifecycle Flow 4 has open rate < 12% after 6 weeks, redo subject lines + audience segmentation."
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## Guardrail metrics
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Some metrics get a hard guardrail (cannot drop below threshold). Useful for protecting brand or unit economics during aggressive growth.
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Examples:
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- "Brand voice complaint rate > 1% of customer feedback triggers content review."
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- "Paid CAC > $X for two consecutive months pauses paid scaling pending audit."
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- "App Store rating drops below 4.5 triggers product review."
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## Data sources mapping
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The plan should name where each metric comes from. This makes it auditable.
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| Metric | Source |
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| Organic traffic | GA4 / Ahrefs |
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| App Store conversion | App Store Connect |
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| Funnel conversion (Day N → paid) | Internal analytics (Mixpanel / Amplitude) or App Store Connect cohort export |
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| Retention | Customer.io segments + product analytics |
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| MRR / ARR | Stripe (via MCP if wired) |
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| Plan mix | Stripe |
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| Lifecycle email metrics | Customer.io |
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| Ambassador attribution | Dub.co |
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| Hardware → app activation | Shopify + App Store + internal join |
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| NPS | Survey tool (Customer.io / Typeform / SurveyMonkey) |
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## When data isn't wired
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If a metric can't currently be measured, flag it in Section 13's open decisions. Example:
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> "Hardware → app activation rate not currently visible in the App Store dashboard. Requires Shopify ↔ App Store Connect join. Q1 work item."
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A plan with un-measurable goals is a plan that can't be validated. Surface the instrumentation work explicitly.
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## Reporting cadence + automation
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Where possible, auto-generate the metrics review rather than building it manually each time. Stripe MCP + GA4 MCP + Customer.io MCP can pull most of what's needed.
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For Tier 1 clients, a simple weekly metrics email to the team (Markdown table, generated via skills + MCPs) costs nothing and creates discipline.
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For Tier 2+ clients, consider a real dashboard (Hex, Metabase, Looker, or internal tool).
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