analytics_skill

Overview

This skill helps product teams become data-driven by defining meaningful metrics, building dashboards, running A/B tests, and making decisions based on evidence. It focuses on north-star selection, funnel and engagement metrics, dashboard architecture for different stakeholders, experiment design, and practical troubleshooting. Use it to align product work to measurable business outcomes.

How this skill works

I guide you through selecting a single North Star metric, mapping funnel metrics from acquisition to revenue, and calculating core revenue and retention measures (MRR, ARR, ARPU, LTV, churn). I define dashboard layouts for executive, product, finance, and health use cases and provide A/B test planning templates that include hypothesis, sample sizing, duration, and significance thresholds. I also surface common metric pitfalls, cadence for reviews, and concrete recovery steps when data or experiments fail.

When to use it

• When defining a North Star metric to align teams
• When instrumenting funnels and onboarding to improve activation
• Before running A/B tests to ensure proper design and sample size
• When building dashboards for executives, product, finance, or ops
• When diagnosing churn, LTV/CAC, or inconsistent data sources
• When planning metric review cadence (daily/weekly/monthly/quarterly)

Best practices

• Choose one North Star that directly ties to value and revenue
• Track both acquisition efficiency (CAC) and retention (LTV) to avoid misleading growth
• Keep dashboards focused: 5–7 KPIs per audience with clear owners
• Design A/B tests with pre-defined success metric, 95% confidence, and sufficient sample size
• Segment results and use cohorts to distinguish correlation from causation
• Establish a single source of truth for metric definitions and instrumentation

Example use cases

• Optimize signup funnel: measure visitors → signups → free-to-paid and run CTA placement experiments
• Improve onboarding: track onboarding completion, time-to-first-value, and Day 1/7 retention cohorts
• Executive weekly summary: MRR, new customers, churn, NPS, and engagement vs targets
• Finance monthly review: CAC, LTV, gross margin, CAC payback, and revenue by segment
• Health monitoring: realtime uptime, error rate, p95 response time, and support backlog