growth-analytics-dashboard_skill

Overview

This skill helps teams set up a growth analytics framework, design KPI dashboards, and run cohort and funnel analyses to enable data-driven decisions. It focuses on measurable outcomes like CAC/LTV, retention, and MRR while providing repeatable processes for experimentation and forecasting. Use it to align stakeholders on metrics and to operationalize growth work across product, marketing, and executive audiences.

How this skill works

The skill defines a 5-category KPI framework (Acquisition, Activation, Revenue, Retention, Referral) and recommends metric frequency and priority. It prescribes dashboard patterns for executive, product, marketing, and sales audiences, plus analyses: cohort retention, funnel breakdowns, A/B testing, and churn/revenue forecasting. It also embeds a 4-week PDCA sprint to iterate on hypotheses and actions.

When to use it

• Design a KPI dashboard for execs, product, marketing, or sales
• Run cohort or funnel analysis to diagnose retention or conversion drops
• Estimate CAC, LTV, and LTV/CAC to validate unit economics
• Set up A/B tests and interpret results against statistical criteria
• Build churn or revenue forecasts for planning and prioritization

Best practices

• Start with a small set of high-priority KPIs aligned to business goals (5–10 metrics)
• Design separate dashboards per audience with tailored cadence and metric count
• Instrument events and sources consistently to enable cohort and funnel analysis
• Use a PDCA sprint (4 weeks) to structure experiments and measure impact
• Adopt clear success criteria for tests (sample size, duration, p-value, minimum lift)
• Translate risk scores and forecasts into concrete playbooks for follow-up actions

Example use cases

• Build an executive dashboard showing MRR, Churn, NPS, CAC, and LTV/CAC updated weekly
• Diagnose a 60% drop between Interest and Evaluation with funnel analysis and prioritize fixes
• Run cohort retention tracking to measure onboarding changes and report W4 improvement
• Design an A/B test for CTA changes with defined sample size and success thresholds
• Implement churn prediction scoring to trigger proactive outreach for high-risk users