/metrics-track

MCP Tools (use if available)

• kb_search(query)

  — find PostHog methodology, analytics patterns

Methodology Reference

• Relative metrics vs niche benchmarks — compare against your own trajectory, not vanity averages
• Kill/iterate/scale decision rules — data-driven thresholds for product decisions (see step 7 below)

Steps

1. Parse project from

   $ARGUMENTS

   .
   • Read PRD for features, ICP, monetization model.
   • Read CLAUDE.md for stack (iOS/Web/both).
   • If empty: ask via AskUserQuestion.
2. Detect platform:
   • iOS app → PostHog iOS SDK events
   • Web app → PostHog JS SDK events
   • Both → cross-platform identity (shared user ID across platforms)
3. Load PostHog methodology:
   • If MCP available:

     kb_search("PostHog analytics events funnel identity")

   • Otherwise: check project docs for existing analytics configuration
   • Extract: event naming conventions, identity resolution, funnel pattern
4. Define event funnel based on PRD features:
   Standard funnel stages (adapt per product):

   Awareness → Acquisition → Activation → Revenue → Retention → Referral

   Map to concrete events:

   Stage	Event Name	Trigger	Properties
   Awareness	page_viewed	Landing page visit	source , utm_*
   Acquisition	app_installed or signed_up	First install/signup	platform , source
   Activation	core_action_completed	First key action	feature , duration_ms
   Revenue	purchase_completed	First payment	plan , amount , currency
   Retention	session_started	Return visit (D1/D7/D30)	session_number , days_since_install
   Referral	invite_sent	Shared or referred	channel , referral_code

5. Forced reasoning — metrics selection: Before defining KPIs, write out:
   • North Star Metric: The ONE number that matters most (e.g., "weekly active users who completed core action")
   • Leading indicators: What predicts the North Star? (e.g., "activation rate D1")
   • Lagging indicators: What confirms success? (e.g., "MRR", "retention D30")
   • Vanity metrics to AVOID: (e.g., total downloads without activation)
6. Set KPI benchmarks per stage:

   KPI	Target	Kill Threshold	Scale Threshold	Source
   Landing → Signup	3-5%	< 1%	> 8%	Industry avg
   Signup → Activation	20-40%	< 10%	> 50%	Product benchmark
   D1 Retention	25-40%	< 15%	> 50%	Mobile avg
   D7 Retention	10-20%	< 5%	> 25%	Mobile avg
   D30 Retention	5-10%	< 2%	> 15%	Mobile avg
   Trial → Paid	2-5%	< 1%	> 8%	SaaS avg

   Adjust based on product type (B2C vs B2B, free vs paid, mobile vs web).
7. Define decision rules (lean startup kill/iterate/scale):
   markdown

   ## Decision Framework
   
   **Review cadence:** Weekly (Fridays)
   
   ### KILL signals (any 2 = kill)
   - [ ] Activation rate < {kill_threshold} after 2 weeks
   - [ ] D7 retention < {kill_threshold} after 1 month
   - [ ] Zero organic signups after 2 weeks of distribution
   - [ ] CAC > 3x LTV estimate
   
   ### ITERATE signals
   - [ ] Metrics between kill and scale thresholds
   - [ ] Qualitative feedback suggests product-market fit issues
   - [ ] One stage of funnel is dramatically worse than others
   
   ### SCALE signals (all 3 = scale)
   - [ ] Activation rate > {scale_threshold}
   - [ ] D7 retention > {scale_threshold}
   - [ ] Organic growth > 10% week-over-week

8. Generate PostHog implementation snippets:

   For iOS (Swift):

   swift

   // Event tracking examples
   PostHogSDK.shared.capture("core_action_completed", properties: [
       "feature": "scan_receipt",
       "duration_ms": elapsed
   ])

   For Web (TypeScript):

   typescript

   // Event tracking examples
   posthog.capture('signed_up', {
       source: searchParams.get('utm_source') ?? 'direct',
       plan: 'free'
   })

9. Write metrics plan to

   docs/metrics-plan.md

   :
   markdown

   # Metrics Plan: {Project Name}
   
   **Generated:** {YYYY-MM-DD}
   **Platform:** {iOS / Web / Both}
   **North Star:** {north star metric}
   
   ## Event Funnel
   
   | Stage | Event | Properties |
   |-------|-------|------------|
   {event table from step 4}
   
   ## KPIs & Thresholds
   
   | KPI | Target | Kill | Scale |
   |-----|--------|------|-------|
   {benchmark table from step 6}
   
   ## Decision Rules
   
   {framework from step 7}
   
   ## Implementation
   
   ### PostHog Setup
   - Project: {project name} (EU region)
   - SDK: {posthog-ios / posthog-js}
   - Identity: {anonymous → identified on signup}
   
   ### Code Snippets
   {snippets from step 8}
   
   ## Dashboard Template
   - Funnel: {stage1} → {stage2} → ... → {stageN}
   - Retention: D1 / D7 / D30 cohort chart
   - Revenue: MRR trend + trial conversion
   
   ---
   *Generated by /metrics-track. Implement events, then review weekly.*

10. Output summary — North Star metric, key thresholds, first event to implement.

Notes

• PostHog EU hosting for privacy compliance
• Use

  $set

  for user properties,

  capture

  for events
• Identity: start anonymous,

  identify()

  on signup with user ID
• Cross-platform: same PostHog project, same user ID → unified journey
• Review dashboard weekly, make kill/iterate/scale decision monthly

Common Issues

Wrong platform detected

KPI thresholds too aggressive

docs/metrics-plan.md

PostHog SDK not in project

pnpm add posthog-js

posthog-ios