Growth Track

Growth Tracking SOP

Boundary

This skill (growth-track) = WHAT to track. The business metrics dashboard: defines metrics (AARRR, North Star), manages budgets, designs experiments, and generates weekly reports.

Not this skill — use `data-decide` instead for HOW to interpret data: cohort analysis methodology, A/B test statistical rigor, vanity vs actionable metric evaluation, event taxonomy design, and data-driven decision frameworks.

Section 1: AARRR Funnel Tracking

Reference: Dave McClure, "Pirate Metrics."

Define each stage metric for the specific product. If metrics are not yet defined, work with the user to set them.

Acquisition

• Primary metric: new signups per week/month
• CAC by channel: cost to acquire one user from each source (organic search, social, paid, referral, direct)
• Channel breakdown: what % of signups come from each channel?
• Tracking: analytics dashboard (Google Analytics, Plausible, PostHog) + UTM parameters from content-distribute

Activation

• Primary metric: % of signups who complete the key activation action
• Define "activated": the moment a user first experiences core value (e.g., first project created, first query run, first integration connected)
• Time-to-value: median time from signup to activation — shorter is better
• Tracking: product analytics events (PostHog, Mixpanel, or custom)

Retention

• Primary metrics: Day 1, Day 7, Day 30 return rates
• Churn rate: % of users who stop using the product per month
• Tracking: product analytics cohort reports
• For cohort analysis methodology and interpretation, use data-decide

Revenue

• MRR (Monthly Recurring Revenue): total recurring revenue
• ARPU (Average Revenue Per User): MRR / paying users
• Free-to-paid conversion: % of free users who convert to paid
• Expansion revenue: upgrades, add-ons, usage-based growth
• Tracking: payment provider dashboard (Stripe, Lemon Squeezy, etc.)

Referral

• Invite rate: % of users who invite at least one other person
• Viral coefficient (k): invites sent per user x conversion rate of invites. k > 1 = viral growth.
• Referral channel: word of mouth, share feature, affiliate program
• Tracking: referral tracking system or UTM-tagged invite links

Use Playwright MCP to pull metrics from analytics dashboards, payment providers, and other tools. Take screenshots for user review.

Section 2: North Star Metric

Reference: Sean Ellis, "Hacking Growth."

Define the North Star

Choose ONE metric that captures the core value users get from the product. This is NOT revenue — it's the thing that, when it grows, means users are getting more value.

Examples:

• Slack: daily active users who send messages
• Airbnb: nights booked
• Spotify: time spent listening

Format: "[Metric name]: [number] per [time period]"

Define Input Metrics

Identify 3-4 metrics that directly feed into the North Star:

Track Daily/Weekly

• Update North Star metric daily (automated if possible)
• Review input metrics weekly
• If North Star stalls for 2+ weeks, investigate which input metric is the bottleneck

Section 3: Budget Management

Track All Spending

Maintain a running cost table:

Monthly Burn Rate

• Total monthly spend (infrastructure + tools + marketing + other)
• Months of runway remaining (if bootstrapped: revenue - costs = net)
• Flag if burn rate increases >20% month-over-month without proportional revenue growth

CAC by Channel

For each acquisition channel:

LTV:CAC Ratio

• LTV (Lifetime Value): ARPU x average customer lifespan in months
• Target ratio: 3:1 or higher
• Decision rules:
• LTV:CAC > 3:1 — scale this channel, invest more
• LTV:CAC 1:1 to 3:1 — optimize before scaling
• LTV:CAC < 1:1 — kill this channel after 30-day test confirms the ratio

Section 4: Experiment Tracking

Experiment Format

For every growth experiment, define BEFORE running:

Experiment: [Name]
Hypothesis: If we [specific action], then [metric] will [direction] by [amount]
Duration: [max 2 weeks]
Success Criteria: [metric] reaches [target] by end of experiment
Effort: [hours estimated]

Running Experiments

1. Only run 1-2 experiments simultaneously (more = confounding variables) 2. Measure the specific metric defined in the hypothesis — not vanity metrics 3. Don't stop early on positive results (survivorship bias) — run for full duration 4. Document result immediately after completion:

Result: PASS / FAIL
Actual outcome: [metric] changed by [amount] (expected [amount])
Learning: [what we now know that we didn't before]
Next action: [scale it / iterate / kill it / new experiment]

Store All Experiments

In auto memory (memory/growth_metrics.md), store:

• Experiment name, hypothesis, duration
• Result (pass/fail)
• Actual vs expected outcome
• Key learning
• Follow-up action taken

This prevents re-running failed experiments and builds institutional knowledge.

Section 5: Weekly Growth Review

Every Monday, generate a growth report:

1. Funnel Snapshot

2. Biggest Drop-Off

Identify the funnel stage with the worst conversion rate or biggest decline. This is the focus for the week.

Format: "This week focus on [stage] because [specific data point showing the problem]."

3. Experiment Status

• Active experiments: status update
• Completed experiments: result summary
• Proposed experiments: for user approval

4. Budget Check

• Monthly spend vs budget
• Any unexpected cost increases
• CAC trend by channel

Use Playwright MCP to pull data from analytics dashboards, payment providers, and ad platforms. Compile into the report format above.

Section 6: Partnership & Channel Growth

Integration Partnerships

Build integrations with complementary products and list on their marketplace or directory. Each integration = a distribution channel you don't own but benefit from. Prioritize platforms with active marketplaces (Zapier, Slack, Notion, etc.) — being listed puts you in front of users already looking for solutions.

Affiliate Program

Offer 20-30% recurring commission on referred customers. Tools: Rewardful, FirstPromoter, or simple Stripe referral links. Only launch after product-market fit — don't pay to acquire users for a leaky bucket. Start with a small group of aligned affiliates (power users, niche bloggers) rather than opening to everyone.

Co-Marketing

Find non-competing products serving the same audience. Tactics: guest blog posts, shared webinars, newsletter swaps, joint case studies. Zero cost, mutual benefit. The best co-marketing partners are products your users already use alongside yours.

Marketplace & Directory Listings

Submit to every relevant directory: Product Hunt, AlternativeTo, G2, Capterra, SaaSHub, and niche-specific directories. Each listing = a permanent SEO backlink + discovery channel. Maintain listings actively — update screenshots, respond to reviews, keep descriptions current.

Partnership Qualification

Only pursue partnerships where the partner's audience is your target user. "They're big" is not a reason to partner. Before committing time, verify: (1) their users have the problem you solve, (2) there's a natural integration point or shared workflow, (3) the partnership is mutually beneficial, not one-sided.

Store active partnerships and their performance in auto memory (memory/partnerships.md) with: partner name, type (integration/affiliate/co-marketing/listing), date started, and referral metrics.

Next Steps

Report to user: "Funnel: [biggest drop-off stage]. North Star: [metric] = [value]. Experiments: [N active]"

Suggested next steps (user decides):

• Acquisition problem → "Run community-engage or content-create"
• Activation problem → "Run product-eval"
• Retention problem → "Run support-ops"
• Revenue problem → "Run finance-ops or sales-close"
• Feature pivot needed → "Run roadmap-steer"