feat: add plan skill — comprehensive AARRR marketing plan generator

A new skill (`/plan {client-name}`) that produces an exhaustive 13-section
Notion-paste-ready marketing plan structured by AARRR (Acquisition,
Activation, Retention, Referral, Revenue), customized to the client's
current budget, team, stage, and tooling stack, mapped to future
funding-stage capability unlocks.

Three-phase workflow:
- INIT: research + structured 10-topic intake; pulls data from wired
  MCPs (Ahrefs, GA4, Stripe, Customer.io, etc.); offers to run
  /audit-marketing first
- REVIEW: section-by-section interactive draft with user confirmation
  on each of the 13 sections; resumable across sessions
- FINALIZE: compile, verification pass (cross-references, machine paths,
  brand voice), and optional publish to a shared GitHub repo

The 13 sections:
1. Executive summary
2. Strategic frame
3. Current state (scored against the 17-section audit-marketing rubric)
4. Acquisition
5. Activation
6. Retention
7. Referral
8. Revenue
9. 90-day roadmap (AARRR-tagged, owner-assigned)
10. 12-month outlook (with funding-stage milestones)
11. Marketing operations stack (skills + MCPs per AARRR stage)
12. Tactical idea bank (all 139 ideas from `marketing-ideas` mapped to
    AARRR + client-specific status: Now / Q2 / Q3+ / Q4+ / Skip)
13. Measurement, RACI, open decisions, appendix

References:
- methodology.md — full three-phase workflow
- plan-template.md — 13-section template with per-section guidance
- aarrr-framework.md — AARRR primer + diagnostic rules for which stage
  is the binding constraint
- current-state-rubric.md — 17-section audit-marketing rubric mapped
  to AARRR
- ops-stack-mapping.md — all 26+ marketing skills + MCP/API integrations
  mapped to AARRR stages
- idea-cross-reference.md — all 139 marketing-ideas mapped to AARRR
  with timing defaults
- funding-stage-unlocks.md — 5 standard funding tiers (pre-seed through
  Series B+) with budget profiles and capability unlocks
- measurement-framework.md — north-star patterns by business model,
  leading indicators by AARRR stage, review cadence
- client-types.md — variations by client archetype (B2B SaaS, D2C
  consumer app, hybrid hardware+software, marketplace, dev tool,
  deep-tech/clinical, commerce)
- example-olo.md — canonical reference plan from a real fCMO engagement

Updates:
- plugin.json + marketplace.json bumped to 2.3.0
- marketplace description updated to 43 skills
- VERSIONS.md entry added

Total skills: 43.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
Corey Haines
2026-05-27 17:38:31 -07:00
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# Measurement Framework — KPIs, North Stars, Cadence
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.
## The north-star principle
A north star is one metric that captures the business-model thesis at the highest level. It should:
- Be derivable from the funnel + revenue model
- Move slowly enough to be a strategic compass (not whipsawed by weekly noise)
- Trade off correctly against other metrics — improving the north star should generally improve the business
Don't default to "ARR" or "MRR" alone. Those are outcomes, not norths. Pick something that captures the business model.
## North-star patterns by business model
### B2B SaaS (subscription)
- **Net Revenue Retention (NRR)** — keeps existing customers + expansion in focus
- Alternative: "Logo retention × expansion ARR"
- Why: ARR alone hides churn / lets gross-add growth mask product fit problems
### D2C consumer app (subscription)
- **Blended LTV / blended CAC** — keeps unit economics honest as paid layer scales
- Alternative: "Day-35 paid users from cohort × LTV"
- Why: monthly subscription metrics are volatile; cohort × LTV smooths it
### Hybrid hardware + software (e.g., Olo)
- **Blended LTV / blended CAC across hardware + software** — captures the wedge thesis
- Alternative: "Hardware-buyers-to-subscriber conversion × blended margin"
- Why: hardware revenue isn't free (cost to make); subscription revenue isn't expensive to acquire if hardware funds it
### Marketplace (two-sided)
- **Liquidity ratio × take-rate** — captures both sides + monetization
- Alternative: "Monthly transacting users × take-rate × repeat frequency"
- Why: GMV alone doesn't capture whether the marketplace is becoming a habit
### Developer tool / open source
- **Weekly active developers × paid-conversion** — captures both adoption and monetization
- Alternative: "Weekly active orgs × seats per org × ARPU"
### Content / media business
- **Daily active readers / listeners × ad revenue per session** — captures both reach and monetization
- Alternative: "Subscriber count × retention × ARPU"
### Commerce (DTC, non-subscription)
- **Repeat purchase rate × AOV × frequency** — captures monetization layered on quality of customer
- Alternative: "Customer LTV / CAC × payback period"
## Leading indicators by AARRR stage
After the north star, every plan needs leading indicators per AARRR stage. These move faster than the north star and trigger investigations.
### Acquisition leading indicators
- Organic visits/month, total + per pillar (SEO health)
- App Store / Play Store visit-to-install rate (ASO health)
- Founder-led social channel growth → email subscriber conversion (LinkedIn / X / Substack funnels)
- Event-to-app conversion rate (event ROI)
- Ambassador-attributed visits (referral funnel)
- Paid CAC by channel (when paid is firing)
### Activation leading indicators
- Day 1 / Day 7 / Day 35 → paid conversion rate
- Onboarding session-completion rate
- First key-action completion (post-signup activation event)
- App Store conversion rate (install → trial → paid)
- Trial → paid conversion rate
### Retention leading indicators
- Day 30 / Day 60 / Day 90 retention
- Monthly churn rate (gross + net)
- Lifecycle email engagement (open / click / unsubscribe by flow)
- Hardware → app activation rate (for hybrid businesses)
- Win-back / reactivation rate
### Referral leading indicators
- Ambassador-attributed new subs (via Dub or similar)
- Share-after-value moment rate (% of users sharing)
- Two-sided referral completion rate
- Guides program referrals (when live)
- NPS score (if surveyed)
### Revenue leading indicators
- ARPU by cohort
- Annual plan adoption %
- Cohort LTV by source
- Plan mix shifts
- Eye-mask / hardware attach rate (for hybrid)
- Expansion revenue (B2B)
## Review cadence
The plan should specify three rhythms:
### Weekly (operational sync)
- **Who:** fCMO ↔ founder (CEO usually)
- **Duration:** 30 min
- **Format:** AARRR scoreboard (current vs. last week numbers across the leading indicators) + this week's ships + blockers
- **Output:** Action items, decisions made
### Monthly (metrics review)
- **Who:** fCMO + founder + extended team (CXO, product lead, designer if applicable)
- **Duration:** 6090 min
- **Format:** Full metrics review + comparison against quarterly KPI targets + qualitative learnings + idea bank reprioritization
- **Output:** Possible plan adjustments, hire decisions
### Quarterly (plan recalibration)
- **Who:** fCMO + founders + key advisors
- **Duration:** 23 hours
- **Format:** Full plan review against 90-day and 12-month outcomes, channel-level analysis, funding-stage transition check, recalibration of next 90 days
- **Output:** Updated plan (could be v2 / v3 document iteration)
## KPI target setting
For each quarter in Section 10, the plan must include 35 specific KPI targets. These should be:
- **Specific** — not "improve retention," but "Day 30 retention from 22% → 30%"
- **Measurable** — pull from a wired data source
- **Stretch but plausible** — based on funnel state + historical patterns
- **Decision-triggering** — if missed, what does that mean? (Adjust strategy, kill a channel, etc.)
### KPI target patterns by quarter
**Q1 (foundation quarter):**
- Mostly *bedrock* metrics — fixing leaks. "Headphones-gate conversion drop reverses." "Day 1 → paid +2550%."
- Some *foundation* metrics — laying tracks. "4 SEO pillars staked." "App Store rewrite shipped."
- Avoid bold growth targets — the foundations aren't in yet
**Q2 (validation quarter):**
- Mostly *validation* metrics — does what we built work? "Paid CAC < $X blended." "Organic traffic 1,5003,500/mo."
- Some *cohort* metrics — do new cohorts behave better? "Day 7 retention for Q2 cohort vs. Q1."
**Q3 (scaling quarter):**
- Mostly *scaling* metrics — how far does it go? "Paid scaling to $2030K/mo with CAC steady." "First B2B install reference case live."
- Some *capability* metrics — what new things are live? "First Guides pilot launched."
**Q4 (compound quarter):**
- Mostly *compound* metrics — is the flywheel turning? "50%+ of new subs from non-paid channels." "Ambassador-driven 1525% of new subs."
- Some *narrative* metrics — does the Series A story write itself? "Blended LTV/CAC > 3."
## Kill criteria
For every channel or initiative, the plan should specify when to stop. Often missing from plans, kill criteria force discipline.
Examples:
- "If a paid channel has CAC > 2× target after 30 days at meaningful spend, pause."
- "If onboarding Variant 3 doesn't show statistically meaningful lift (or directional lift + congruent qualitative signal) after 4 weeks, move to Variant 1."
- "If lifecycle Flow 4 has open rate < 12% after 6 weeks, redo subject lines + audience segmentation."
## Guardrail metrics
Some metrics get a hard guardrail (cannot drop below threshold). Useful for protecting brand or unit economics during aggressive growth.
Examples:
- "Brand voice complaint rate > 1% of customer feedback triggers content review."
- "Paid CAC > $X for two consecutive months pauses paid scaling pending audit."
- "App Store rating drops below 4.5 triggers product review."
## Data sources mapping
The plan should name where each metric comes from. This makes it auditable.
| Metric | Source |
|---|---|
| Organic traffic | GA4 / Ahrefs |
| App Store conversion | App Store Connect |
| Funnel conversion (Day N → paid) | Internal analytics (Mixpanel / Amplitude) or App Store Connect cohort export |
| Retention | Customer.io segments + product analytics |
| MRR / ARR | Stripe (via MCP if wired) |
| Plan mix | Stripe |
| Lifecycle email metrics | Customer.io |
| Ambassador attribution | Dub.co |
| Hardware → app activation | Shopify + App Store + internal join |
| NPS | Survey tool (Customer.io / Typeform / SurveyMonkey) |
## When data isn't wired
If a metric can't currently be measured, flag it in Section 13's open decisions. Example:
> "Hardware → app activation rate not currently visible in the App Store dashboard. Requires Shopify ↔ App Store Connect join. Q1 work item."
A plan with un-measurable goals is a plan that can't be validated. Surface the instrumentation work explicitly.
## Reporting cadence + automation
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.
For Tier 1 clients, a simple weekly metrics email to the team (Markdown table, generated via skills + MCPs) costs nothing and creates discipline.
For Tier 2+ clients, consider a real dashboard (Hex, Metabase, Looker, or internal tool).